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These models are trained on vast amounts of text data and utilize machine learning techniques to perform a variety of language-related tasks by synthesizing information and answering to queries.\n\nLLMs are essential in Natural Language Processing (NLP) projects as they help in automating tasks such as text generation, translation, summarization, and more. Each LLM typically represents a sophisticated algorithm capable of producing human-like text based on the patterns it has learned from the training data.\n\n## 🤖 Key points about LLMs: \n\n* Some of the most well-known LLMs include OpenAI's GPT-4, Google's Gemini, and Facebook's RoBERTa.\n* LLMs are used in chatbots, virtual assistants, content creation, and language translation tools.\n* The effectiveness of an LLM depends on the quality and diversity of the text data it has been trained on.\n* The performance of LLMs is measured by their ability to generate coherent, contextually relevant, and grammatically correct text among others.\n* The development and deployment of LLMs raise ethical concerns related to bias, misinformation, and the impact on employment.\n\nUnlike basic language processing tools, LLMs are supposed to understand context, generate nuanced responses, and perform a variety of complex language tasks. Technologies like [Human-Assisted Machine Translation (HAMT)](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fhuman-assisted-mt) often integrate LLMs to achieve higher quality and more natural results.\n\n> *Learn more about LLMs and what they are able to do in the translation realm [in our blog](https:\u002F\u002Flocalazy.com\u002Ftags\u002Fai\u002F \"https:\u002F\u002Flocalazy.com\u002Ftags\u002Fai\u002F\").*","llm",[1894,1895,1898,1901,1904],{"id":1873,"slug":1879},{"id":1896,"slug":1897},293,"natural-language-processing-nlp",{"id":1899,"slug":1900},304,"language-modeling",{"id":1902,"slug":1903},439,"tiny-language-model-tlm",{"id":1905,"slug":1906},440,"small-language-model-slm",{"id":1883,"status":8,"owner":1887,"created_on":1888,"title":1908,"excerpt":1909,"content":1910,"slug":1884,"meta_title":764,"meta_description":764,"canonical":764,"related_terms":1911},"Neural Machine Translation (NMT)","A type of automated translation that uses artificial neural networks to predict the likelihood of a sequence of words, producing translations fast.\n","Neural Machine Translation (NMT) is an advanced approach to automated translation that uses artificial neural networks to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.\n\nNMT is a key component in the field of [machine translation](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fmachine-translation) and represents a significant advancement in [AI-powered translation](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fai-powered-translation) technology.\n\nUnlike earlier statistical methods, NMT can capture context and nuances in language, often resulting in more fluent and contextually appropriate translations.\n\n## 🧠 Key points about NMT:\n\n* NMT utilizes deep learning techniques, particularly Recurrent Neural Networks (RNNs) and transformers, to model the translation process. These systems learn to translate directly from source to target language without relying on extensive feature engineering.\n* While initially challenged by rare words, techniques like subword tokenization have improved NMT's ability to handle diverse vocabularies. NMT models can consider the entire input sentence, allowing for better handling of context and long-range dependencies.\n* Training NMT models typically requires significant computational resources and large parallel corpora.\n* Many NMT models incorporate attention mechanisms, allowing the system to focus on relevant parts of the input sentence when generating each word of the translation.\n* Pre-trained NMT models can be adapted to new language pairs or domains, reducing the need for extensive language-specific data.\n* Some models are trained on multiple language pairs simultaneously, enabling zero-shot translation between language pairs not seen during training.\n\nNMT has significantly improved the quality of machine translation across many language pairs and continues to be a primary focus of research and development in the field of AI-powered language technologies.",[1912,1913,1915,1916,1919,1922],{"id":244,"slug":316},{"id":278,"slug":1914},"machine-learning-ml",{"id":1873,"slug":1879},{"id":1917,"slug":1918},186,"statistical-machine-translation",{"id":1920,"slug":1921},187,"example-based-machine-translation",{"id":1923,"slug":1924},188,"hybrid-machine-translation",{"id":244,"status":8,"owner":1926,"created_on":1927,"title":1928,"excerpt":1929,"content":1930,"slug":316,"meta_title":764,"meta_description":764,"canonical":764,"related_terms":1931},"2bac48a8-b362-482f-b574-3bc71dca4c5b","2026-05-12T07:09:22.000Z","Machine translation (MT)","The process of translating using computational linguistics.","A machine translation engine is a software tool that translates a text from one language to another without the help of human translators.\n\nMachine translation, also known as MT, is widely used as the first round of translations and is frequently very effective for short strings. However, it can produce unsatisfactory results when context knowledge is required, and thus, a human review is always advised.\n\n### 💬 Methods used in machine translation\n\nMachine translation engines recently experienced huge improvements related to the advanced use of neural networks, but they generally rely on these different methods:\n\n* [Statistical machine translation (SMT)](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fstatistical-machine-translation\u002F \"https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fstatistical-machine-translation\u002F\")\n* [Example-based machine translation (EBMT)](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fexample-based-machine-translation \"https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fexample-based-machine-translation\")\n* [Hybrid machine translation (HMT)](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fhybrid-machine-translation \"https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fhybrid-machine-translation\")\n* [Neural machine translation (NMT)](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fneural-machine-translation\u002F \"https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fneural-machine-translation\u002F\")\n\nNeural machine translation (used by [AI-powered translation](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Fai-powered-translation) engines) is the most sophisticated type of instant translation today. It uses machine learning to improve its translation capabilities. As the engine translates more text with each request, the better results it produces with time by learning. Most instant translation services use this technology.\n\n### 🔍 What's the difference between HAMT and MAHT?\n\nWithin the realm of machine translation, it’s important to distinguish between **Human-Assisted Machine Translation (HAMT)** and **Machine-Assisted Human Translation (MAHT)**:\n\n* [**Human-Assisted Machine Translation (HAMT)**](\u002Fdictionary\u002Fhuman-assisted-mt): This process involves a human reviewing translations generated by machine translation (MT) engines. It is also known as MT plus post-editing and\u002For pre-editing. The machine handles the initial translation, which is then edited by a human to improve accuracy and context. This approach is useful for projects with repetitive content and where budget or time constraints are significant.\n* [**Machine-Assisted Human Translation (MAHT)**](\u002Fdictionary\u002Fmaht): In this method, human translators use computer software to aid their work. Translators receive machine translation suggestions, but they decide how to use them. This approach allows for high translation accuracy while benefiting from features like translation glossaries and memories, which enhance the efficiency and consistency of the translation process.\n\n### 🦾 MT engines available in Localazy \n\nLocalazy users can use the most popular and advanced [MT engines](https:\u002F\u002Flocalazy.com\u002Ffeatures\u002Fmachine-translation \"https:\u002F\u002Flocalazy.com\u002Ffeatures\u002Fmachine-translation\") to translate their content:\n\n* Amazon Translate (available for free)\n* Google Translate\n* DeepL\n* Azure Translator\n* OpenAI (ChatGPT), with your own API key\n\n> *Users can unlock different engines depending on the plan they buy. See our [pricing](https:\u002F\u002Flocalazy.com\u002Fpricing) and [docs](https:\u002F\u002Flocalazy.com\u002Fdocs\u002Fgeneral\u002Fadditional-mt-engines?srsltid=AfmBOoo--lURSBHDiHEoe3rYL3xSQHaZcTsl6kd7wwUYRGC-sGTTmG94 \"https:\u002F\u002Flocalazy.com\u002Fdocs\u002Fgeneral\u002Fadditional-mt-engines?srsltid=AfmBOoo--lURSBHDiHEoe3rYL3xSQHaZcTsl6kd7wwUYRGC-sGTTmG94\") for more details.*\n\n### 📚 Additional resources:\n\n* [What is machine translation?](https:\u002F\u002Fwww.gala-global.org\u002Fwhat-machine-translation)\n* [History of machine translation](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FHistory_of_machine_translation)",[1932,1934,1936,1938],{"id":441,"slug":1933},"maht",{"id":1681,"slug":1935},"mtpe-machine-translation-post-editing",{"id":1615,"slug":1937},"deepl",{"id":1939,"slug":1940},136,"human-assisted-mt",{"id":82,"status":1942,"owner":1926,"created_on":1943,"title":1944,"excerpt":1945,"content":1946,"slug":1947,"meta_title":7,"meta_description":7,"canonical":7,"related_terms":1948},"deleted","2022-03-17T12:22:55.000Z","HAMT","Human-Assisted Machine Translation, i.e., MT plus post-editing and\u002F\nor pre-editing;","HAMT stands for Human-Assisted Machine Translation. Primarily, all the translation tasks are being done by machine translation and then they are edited by human or vice versa. A high amount of MT eliminates expensive work and can be used especially in translation projects with repetitive content.","hamt",[],{"id":441,"status":8,"owner":1926,"created_on":1943,"title":1950,"excerpt":1951,"content":1952,"slug":1933,"meta_title":764,"meta_description":764,"canonical":764,"related_terms":1953},"MAHT","Machine-Assisted Human Translation, i.e., human uses computer for\nhelp as desired.","Machine-Assisted Human Translation is probably one of the most common approaches seen nowadays in a wide variety of translation projects. MAHT allows for high translation accuracy aided by computer software for increased efficiency. For example, translators are presented with machine translation suggestions, but it is on them whether and how they will use it.\n\nIn addition, other features of common translation management systems are here to help all translation project stakeholders, such as translation glossary or translation memory.",[1954,1956,1957,1958,1960,1962],{"id":22,"slug":1955},"translation",{"id":147,"slug":333},{"id":244,"slug":316},{"id":274,"slug":1959},"htlgi",{"id":154,"slug":1961},"translation-management-system-tms",{"id":269,"slug":254},{"id":436,"status":8,"owner":1926,"created_on":1888,"title":1964,"excerpt":1965,"content":1966,"slug":1967,"meta_title":764,"meta_description":764,"canonical":764,"related_terms":1968},"QA - Quality Assurance","The process of verifying that a localized product accurately delivers its intended functions to the end-user.","Quality assurance is the process of verifying that a product or service is up to standard and discovering whether it meets customer needs. Through the QA process, documentation is provided and tests are performed to detect differences between the original product being translated and its localized version. Information gleaned from these tests becomes a vital part of verifying that the released localized product can accurately deliver its intended function to the end-user.\n\nQuality assurance and testing are performed before any expensive product development actions are taken to avoid getting unpleasant surprises. To maintain high standards, it is good practice to involve quality assurance at all stages of the translation process by writing a quality plan, setting milestones, and testing.\n\n### 🔍 QA in localization\n\nQuality assurance in localization covers both functional checks and linguistic quality reviews. They make sure localized products are not only technically sound but also clear, consistent, and natural for the end user. Key areas of QA in localization include: \n\n* 🛠️ [**Localization QA**](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Flocalization-quality-assurance \"https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Flocalization-quality-assurance\") - Focuses on whether the product works as expected after translation. This involves checking layouts, placeholders, character encoding, and ensuring that translated text displays correctly without breaking the interface.\n\n\n* 📝 [**Linguistic QA (LQA)**](https:\u002F\u002Flocalazy.com\u002Fdictionary\u002Flinguistic-quality-assurance) - Evaluates the quality of the translation itself. It verifies that terminology matches the approved glossary, that the style aligns with project guidelines, and that the text is culturally appropriate and easy to read in the target language.\n\nThese two stages complement each other: localization QA is concerned with functionality, while LQA ensures readability and cultural accuracy. Together, they confirm that end users get the same experience in the localized product as in the original.\n\n### ➡️ How Localazy handles QA\n\nSome preventative QA measures for translation and localization in Localazy are:\n\n* Defining a [Glossary of terms](\u002Fdocs\u002Fgeneral\u002Fhow-to-define-your-glossary).\n* Uploading [Context Screenshots](\u002Fdocs\u002Fgeneral\u002Fscreenshots).\n* Appointing [trusted translators and reviewers](\u002Fdocs\u002Fgeneral\u002Fdefining-user-roles).\n* Translation & review interface with built-in checks for placeholders, missing tags, etc.\n\nTogether, these measures give teams a structured way to maintain quality while speeding up localization. By combining automation with human review, Localazy helps ensure that localized products are both accurate and reliable.\n\n> *Learn more about QA checks [in our docs](https:\u002F\u002Flocalazy.com\u002Fdocs\u002Fgeneral\u002Fqa-checks\u002F).*","qa-quality-assurance",[1969,1970,1972,1975],{"id":5,"slug":1833},{"id":428,"slug":1971},"continuous-improvement",{"id":1973,"slug":1974},282,"linguistic-quality-assurance",{"id":1976,"slug":1977},306,"localization-quality-assurance","LLMs like Claude, ChatGPT, or Mistral can sometimes get too conversational when you ask them for a translation. This means you won't always get a ready-to-use result or that you'll have to dig further to find a suitable one. Learn the reasons behind this - and discover ways to avoid it.","\u003Cp>What to do when a machine tries to outsmart you?\u003C\u002Fp>\u003Cp>Beat it at its own game. 👾\u003C\u002Fp>\u003Cp>Large language models are not always perfect. Depending on the model, LLMs tend to act in peculiar ways, e.g., \u003Ca href=\"https:\u002F\u002Fslator.com\u002Fgoogle-finds-refusal-to-translate-most-common-form-of-llm-verbosity\u002F\">by refusing to translate\u003C\u002Fa> your text or explaining the reasoning behind their translations. \u003Cstrong>That's what researchers call \u003Cem>verbosity\u003C\u002Fem>.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>What is \u003Cem>verbose\u003C\u002Fem> in LLMs?\u003C\u002Fp>\u003Cp>In \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2410.00863\">a paper\u003C\u002Fa> published on October 1, 2024, Google researchers explain that \u003Cem>verbosity\u003C\u002Fem> has become a common feature of LLMs. This phenomenon usually manifests as a refusal to translate, but there are other symptoms, too: when the model provides multiple translation options or when it includes additional comments along with the translated text.\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg\" class=\"kg-image\" alt loading=\"lazy\" width=\"2000\" height=\"1255\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1600\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 1600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw2400\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 2400w\" sizes=\"(min-width: 720px) 720px\">\u003C\u002Ffigure>\u003Ch2 id=\"why-are-llms-so-verbose\">💬 Why are LLMs so verbose? \u003Ca class=\"markdownit-header-anchor\" href=\"#why-are-llms-so-verbose\">🔗\u003C\u002Fa>\u003C\u002Fh2>\u003Cp>There are many reasons why Claude, GPT-4, Mistral & co. may adopt a conversational approach. Usually, LLMs refuse to translate the input in these four scenarios:\u003C\u002Fp>\u003Col>\u003Cli>❌ \u003Cstrong>Request for translation of non-natural language\u003C\u002Fstrong>\u003C\u002Fli>\u003Cli>©️ \u003Cstrong>Use of copyrighted content in the prompt\u003C\u002Fstrong>\u003C\u002Fli>\u003Cli>💣 \u003Cstrong>Detection of harmful content\u003C\u002Fstrong>\u003C\u002Fli>\u003Cli>🌪️ \u003Cstrong>Unclear content\u003C\u002Fstrong>\u003C\u002Fli>\u003C\u002Fol>\u003Cp>When you request context-sensitive translations, the LLMs may also provide comments along with the translated text or offer multiple translation options.\u003C\u002Fp>\u003Cp>Let's take a look at some examples to illustrate LLM verbosity.\u003C\u002Fp>\u003Ch3 id=\"1-copyrighted-content\">1. Copyrighted content \u003Ca class=\"markdownit-header-anchor\" href=\"#1-copyrighted-content\">🔗\u003C\u002Fa>\u003C\u002Fh3>\u003Cp>First, let's compare how GPT-4, Claude 3.5, and Mistral Large deal with copyrighted content.\u003C\u002Fp>\u003Cp>I asked the models to translate the first sentence of my favorite book. This is how each LLM responded to my request:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"1030\" height=\"315\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG 1030w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>The excerpt from \"The Lord of the Rings: The Fellowship of The Ring\" by Tolkien translated into Spanish by GPT-4.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-2-Claude-Tolkien.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"814\" height=\"335\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-2-Claude-Tolkien.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-2-Claude-Tolkien.JPG 814w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>The excerpt from \"The Lord of the Rings: The Fellowship of The Ring\" by Tolkien translated into Spanish by Claude 3.5.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-3-Mistral-Tolkien.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"843\" height=\"665\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-3-Mistral-Tolkien.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-3-Mistral-Tolkien.JPG 843w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>The excerpt from \"The Lord of the Rings: The Fellowship of The Ring\" by Tolkien translated into Spanish by Mistral Large.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>As you can see, only \u003Cstrong>Mistral was brave enough to indicate the intricacies of translating well-known literature\u003C\u002Fstrong>. It was also the only model that recognized the title and author. However, none of the models refused to translate the content due to potential copyright infringement.\u003C\u002Fp>\u003Cp>The models became more verbose when I typed a more modern text:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-4-Claude-Christina.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"921\" height=\"518\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-4-Claude-Christina.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-4-Claude-Christina.JPG 921w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>An attempt to translate the lyrics of \"Hurt\" by Christina Aguilera (2006) in Claude 3.5.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-5-Mistral-Christina.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"817\" height=\"586\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-5-Mistral-Christina.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-5-Mistral-Christina.JPG 817w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>An attempt to translate the lyrics of \"Hurt\" by Christina Aguilera (2006) in Mistral Large.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-6-Chat-gpt-Christina.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"888\" height=\"260\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-6-Chat-gpt-Christina.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-6-Chat-gpt-Christina.JPG 888w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 translates the lyrics of \"Hurt\" by Christina Aguilera (2006).\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>In this scenario, \u003Cstrong>only Claude refused to translate the content, citing copyright violation\u003C\u002Fstrong>. Mistral recognized the lyrics but\u003Cstrong> \u003C\u002Fstrong>translated the text into Spanish anyway, whereas GPT-4 seemed unconcerned about potential copyright infringement.\u003C\u002Fp>\u003Ch3 id=\"2-non-natural-language\">2. Non-natural language \u003Ca class=\"markdownit-header-anchor\" href=\"#2-non-natural-language\">🔗\u003C\u002Fa>\u003C\u002Fh3>\u003Cp>In the next test round, I prompted the models to translate a URL address and an incomplete phrase containing random characters. The general prompt in each model was still the same as above: \"Act as a professional English-Spanish (ES) translator. Translate the following content into Spanish\".\u003C\u002Fp>\u003Cp>This is how the models responded:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-7-Mistral-http.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"938\" height=\"206\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-7-Mistral-http.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-7-Mistral-http.JPG 938w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral Large refuses to translate a URL address.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-8-Chat-gpt-http-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"996\" height=\"232\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-8-Chat-gpt-http-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-8-Chat-gpt-http-1.JPG 996w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 refuses to translate a URL address.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-9-Claude-http.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"919\" height=\"265\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-9-Claude-http.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-9-Claude-http.JPG 919w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude refuses to translate a URL address, replying in Spanish.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>All three models decided that translating such content is mission impossible, which makes perfect sense\u003C\u002Fstrong>. In real-world scenarios, translators don't translate URLs either. However, each model justified the refusal differently, adopting a less or more talkative approach.\u003C\u002Fp>\u003Cp>Here's how the models reacted to phrases with random characters:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-10-Claude-chars.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"984\" height=\"245\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-10-Claude-chars.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-10-Claude-chars.JPG 984w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude provides a translation for an unclear phrase.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-11-Mistral-chars.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"862\" height=\"504\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-11-Mistral-chars.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-11-Mistral-chars.JPG 862w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral breaks down the phrase, trying to provide a possible translation.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-12-Chat-gpt-chars.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"881\" height=\"347\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-12-Chat-gpt-chars.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-12-Chat-gpt-chars.JPG 881w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 explains the phrase might be incomplete.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>In this scenario, \u003Cstrong>only Claude provided a direct translation instead of a comment\u003C\u002Fstrong>. GPT-4 and Mistral attempted to translate the phrase but explained that it might be incomplete.\u003C\u002Fp>\u003Ch3 id=\"3-unclear-or-confusing-content\">3. Unclear or confusing content \u003Ca class=\"markdownit-header-anchor\" href=\"#3-unclear-or-confusing-content\">🔗\u003C\u002Fa>\u003C\u002Fh3>\u003Cp>What happens when you ask an LLM to translate a gibberish text?\u003C\u002Fp>\u003Cp>It might engage in lengthy conversations. Here's an example:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-13-Mistral-verbs.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"961\" height=\"990\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-13-Mistral-verbs.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-13-Mistral-verbs.JPG 961w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral explaining why the phrase can't be translated.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-verbs-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"991\" height=\"531\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-1-Chatgpt-verbs-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-verbs-1.JPG 991w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 refuses to translate the content.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-15-Claude-verbs.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"893\" height=\"403\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-15-Claude-verbs.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-15-Claude-verbs.JPG 893w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude provides a literal translation.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>Each model acted differently\u003C\u002Fstrong>: Claude provided a useless output for the useless input, GPT-4 shortly declined to translate the phrase, and Mistral not only refused to translate the text but also offered a long-winded grammatical explanation.\u003C\u002Fp>\u003Ch3 id=\"4-context-sensitive-translation\">4. Context-sensitive translation \u003Ca class=\"markdownit-header-anchor\" href=\"#4-context-sensitive-translation\">🔗\u003C\u002Fa>\u003C\u002Fh3>\u003Cp>In the last round, I switched to another language and provided short phrases that may have double meanings. This was the response in each model:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-16-Chat-gpt-Hot-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"986\" height=\"694\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-16-Chat-gpt-Hot-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-16-Chat-gpt-Hot-1.JPG 986w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 provides Polish translations, randomly deciding on which context to choose.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-17-Mistral-Hot.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"796\" height=\"653\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-17-Mistral-Hot.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-17-Mistral-Hot.JPG 796w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral provides two options for both phrases.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-18-Claude-Hot.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"906\" height=\"499\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-18-Claude-Hot.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-18-Claude-Hot.JPG 906w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude refuses to translate the first phrase, claiming it doesn't feel comfortable completing this task. It also refuses to translate the second phrase, explaining that it goes against its values\u003C\u002Fem>.\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>Each model adopted a different approach\u003C\u002Fstrong>: GPT-4 translated the content without the context and Mistral provided more options to account for contextual subtleties, while Claude refused to undertake the task and asked if there was anything else it could help me with.\u003C\u002Fp>\u003Cblockquote>🎙️ Could these LLMs soon become good enough to replace translators? No one knows for sure but we gave our take in \u003Ca href=\"https:\u002F\u002Flocalazy.com\u002Fblog\u002Fs01-ep-03-bridging-the-gap-podcast\">this episode of Bridging the Gap podcast.\u003C\u002Fa>\u003C\u002Fblockquote>\u003Ch2 id=\"whats-wrong-with-verbosity\">🤔 What's wrong with verbosity? \u003Ca class=\"markdownit-header-anchor\" href=\"#whats-wrong-with-verbosity\">🔗\u003C\u002Fa>\u003C\u002Fh2>\u003Cp>There are cases when lengthy LLM responses might be problematic.\u003C\u002Fp>\u003Cp>The above examples show that the verbosity factor can vary across language pairs and LLMs. This, in turn, can lead to \u003Cstrong>an inconsistent user experience\u003C\u002Fstrong>. For example, users might receive concise translations for some language pairs but excessively verbose outputs for others. What's more, for the same input, different LLMs may generate responses with varying degrees of verbosity, making it challenging to predict the output quality. On top of that, extracting relevant content from the lengthy LLM responses might be time-consuming and frustrating. 🙇‍♀️ It can also lead to cognitive overload, which becomes particularly challenging in time-sensitive situations or when you work with technical or specialized content that already requires significant mental effort.\u003C\u002Fp>\u003Cp>In cases where LLMs refuse to translate due to perceived safety or copyright concerns, you are left without the translation you need, which may discourage you from using an LLM for translation purposes. In fact, \u003Cstrong>verbose LLM outputs often lead to lower-quality translations\u003C\u002Fstrong>. The paper mentioned above shows that highly verbose translations tend to be less accurate, introduce errors and redundancies, or deviate from the original meaning. This can significantly impact the usefulness and reliability of LLMs.\u003C\u002Fp>\u003Cp>Finally, overly verbose outputs can lead to\u003Cstrong> increased computational resources and time required for processing\u003C\u002Fstrong>, which can slow down applications and increase costs for users.\u003C\u002Fp>\u003Cblockquote>📚\u003Cstrong> Related\u003C\u002Fstrong>: \u003Ca href=\"https:\u002F\u002Flocalazy.com\u002Fblog\u002Fhow-to-use-chatgpt-to-your-advantage-in-translation-with-examples-gpt-series-1\">How to use ChatGPT to your advantage in translation (with examples)\u003C\u002Fa>\u003C\u002Fblockquote>\u003Ch2 id=\"3-tips-to-reduce-verbosity-bias-in-llms\">☝️3 tips to reduce verbosity bias in LLMs \u003Ca class=\"markdownit-header-anchor\" href=\"#3-tips-to-reduce-verbosity-bias-in-llms\">🔗\u003C\u002Fa>\u003C\u002Fh2>\u003Ch3 id=\"write-effective-prompts\">Write effective prompts \u003Ca class=\"markdownit-header-anchor\" href=\"#write-effective-prompts\">🔗\u003C\u002Fa>\u003C\u002Fh3>\u003Cp>What can you do to avoid Claude's, Mistral's, or ChatGPT's flowery language? When verbosity becomes a serious obstacle to your translation projects, you can take your prompting to the next level. \u003C\u002Fp>\u003Cp>For example, in the case of context-sensitive translations, the best approach is to provide precise context. This is how the prompts above can be modified to obtain more concise responses:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-20-Mistral-Context.png\" class=\"kg-image\" alt loading=\"lazy\" width=\"1204\" height=\"505\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-20-Mistral-Context.png 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-20-Mistral-Context.png 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-20-Mistral-Context.png 1204w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Polish translation in Mistral becomes more natural with a modified prompt.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-21-Claude-Context.png\" class=\"kg-image\" alt loading=\"lazy\" width=\"1282\" height=\"481\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-21-Claude-Context.png 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-21-Claude-Context.png 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-21-Claude-Context.png 1282w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude provides a more accurate translation when the prompt is more specific.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-22-GPT-Context.png\" class=\"kg-image\" alt loading=\"lazy\" width=\"1260\" height=\"585\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-22-GPT-Context.png 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-22-GPT-Context.png 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-22-GPT-Context.png 1260w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT also generates a context-aware translation once all details are provided.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>Each response is different, but all are correct\u003C\u002Fstrong>. The models followed the prompt precisely and generated contextually relevant responses. Mistral still added its verbose touch by including a comment, but it's not lengthy and shouldn't frustrate the impatient users.\u003C\u002Fp>\u003Ch3 id=\"avoid-gibberish-input\">Avoid gibberish input \u003Ca class=\"markdownit-header-anchor\" href=\"#avoid-gibberish-input\">🔗\u003C\u002Fa>\u003C\u002Fh3>\u003Cp>Effective prompts are not the only way out of the verbosity maze. Another key step is to \u003Cstrong>avoid requesting for translation of non-human language\u003C\u002Fstrong>, as this will always lead to confusion. LLMs won't translate URL links, snippets of programming code, or incomplete phrases made up of random characters. \u003C\u002Fp>\u003Cp>Simply put, don't expect LLMs to translate anything a human wouldn't translate. Teasing LLMs with incomplete, grammatically incorrect inputs such as \"has been are,\" as demonstrated above, is not a good idea either. To be on the safe side, make sure both your prompt and source text are of high quality.\u003C\u002Fp>\u003Cblockquote>Verbosity can become a serious obstacle to your translation projects. Working on better prompts and discarding non-human language in your inputs is helpful to reduce it\u003C\u002Fblockquote>\u003Ch3 id=\"adjust-settings-in-llms\">Adjust settings in LLMs \u003Ca class=\"markdownit-header-anchor\" href=\"#adjust-settings-in-llms\">🔗\u003C\u002Fa>\u003C\u002Fh3>\u003Cp>There's one more strategy you can follow to make Claude, Mistral, or ChatGPT less verbose: \u003Cstrong>tweak the settings\u003C\u002Fstrong>. ⚙️ For example, you can lower \u003Ca href=\"https:\u002F\u002Fmedium.com\u002F@marketing_novita.ai\u002Fwhat-are-large-language-model-settings-temperature-top-p-and-max-tokens-a482d8d817b2\">the temperature parameter\u003C\u002Fa> to reduce verbosity and make the model's outputs more focused.\u003C\u002Fp>\u003Cp>You can also adjust the top-p value to control the randomness of the model's outputs. A lower value (e.g., 0.7-0.8) might lead to more concise responses. However, \u003Ca href=\"https:\u002F\u002Fdocs.anthropic.com\u002Fen\u002Fapi\u002Fmessages\" rel=\"noopener noreferrer nofollow\">as stated in the documentation of  OpenAI, Anthropic\u003C\u002Fa> (developer of Claude), and Mistral AI, \u003Cstrong>you should either alter temperature or top_p, but not both\u003C\u002Fstrong>.\u003C\u002Fp>\u003Cp>Finally, in all three models, you can set a lower max tokens value to force the model to be more concise by limiting the length of its response. If you choose this approach, get ready for some in-depth tool exploration, as you won't be able to find these settings directly in the chat. For example, in Mistral, you can create a new agent under the tab La Plateforme, define the temperature and other values, test the prompts with your new settings, and finally deploy the new agent.\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"1477\" height=\"957\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG 1477w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>You can adjust the temperature settings in Mistral by creating a new agent under the La Plateforme tab.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>In most LLMs, top_p values and temperature can also be modified via API.\u003C\u002Fp>\u003Cp>This is how Mistral responded once I set the temperature to 0 in my new agent:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-24-Mistral-has-been-are-temp-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"764\" height=\"413\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-24-Mistral-has-been-are-temp-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-24-Mistral-has-been-are-temp-1.JPG 764w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>With the temperature set to 0, Mistral provides a less verbose response.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Ch2 id=\"final-thoughts\">✔️ Final thoughts \u003Ca class=\"markdownit-header-anchor\" href=\"#final-thoughts\">🔗\u003C\u002Fa>\u003C\u002Fh2>\u003Cp>While refusing to translate the content or providing extra comments might be helpful in some cases, long model responses are usually frustrating for users looking for quick solutions. Verbosity might be a challenge, but there are proven ways to overcome it. \u003Cstrong>So, next time you're wondering: \"Why is ChatGPT so verbose?\", be strategic.\u003C\u002Fstrong> Focus on refining your prompt engineering for translation, adjust the model settings, and ensure your input is free of copyrighted text or non-human language.\u003C\u002Fp>\u003Cp>With a few simple steps, you, too, can outsmart your machine.\u003C\u002Fp>\u003Cblockquote>🦾 Do you want to use OpenAI in your Localazy projects? Head over to \u003Cem>\u003Ca href=\"https:\u002F\u002Flocalazy.com\u002Fconsole\u002Fai\">Localazy Console > Localazy AI\u003C\u002Fa> and try it after adding your own token!\u003C\u002Fem>\u003C\u002Fblockquote>",{"id":286,"status":8,"created_on":1981,"modified_on":1982,"icon":1983,"header":1984,"description":1985,"button_label":1986,"link":1987},"2022-03-17T12:23:03.000Z","2023-01-19T11:50:04.000Z","member","Automate your localization today! ⚙️","Translate your project in a breeze, utilize the advanced features and fully automate your localization process with Localazy! ","Join Localazy","register",{"slug":1859,"id":1852,"uuid":1989,"title":1858,"html":1990,"comment_id":1852,"feature_image":1862,"featured":17,"visibility":1991,"email_recipient_filter":1992,"created_at":1993,"updated_at":1860,"published_at":1861,"custom_excerpt":1978,"codeinjection_head":7,"codeinjection_foot":7,"custom_template":7,"canonical_url":7,"authors":1994,"tags":2000,"primary_author":2051,"primary_tag":2052,"url":2053,"excerpt":1978,"reading_time":137,"access":17,"send_email_when_published":15,"og_image":7,"og_title":7,"og_description":7,"twitter_image":7,"twitter_title":7,"twitter_description":7,"meta_title":7,"meta_description":7,"email_subject":7,"frontmatter":7,"dictionary":1871,"cta":1980,"plainTags":1863},"d1448e91-c9ff-421f-ba0b-b5f60d0a471a","\u003Cp>What to do when a machine tries to outsmart you?\u003C\u002Fp>\u003Cp>Beat it at its own game. 👾\u003C\u002Fp>\u003Cp>Large language models are not always perfect. Depending on the model, LLMs tend to act in peculiar ways, e.g., \u003Ca href=\"https:\u002F\u002Fslator.com\u002Fgoogle-finds-refusal-to-translate-most-common-form-of-llm-verbosity\u002F\">by refusing to translate\u003C\u002Fa> your text or explaining the reasoning behind their translations. \u003Cstrong>That's what researchers call \u003Cem>verbosity\u003C\u002Fem>.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>What is \u003Cem>verbose\u003C\u002Fem> in LLMs?\u003C\u002Fp>\u003Cp>In \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2410.00863\">a paper\u003C\u002Fa> published on October 1, 2024, Google researchers explain that \u003Cem>verbosity\u003C\u002Fem> has become a common feature of LLMs. This phenomenon usually manifests as a refusal to translate, but there are other symptoms, too: when the model provides multiple translation options or when it includes additional comments along with the translated text.\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg\" class=\"kg-image\" alt loading=\"lazy\" width=\"2000\" height=\"1255\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1600\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 1600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw2400\u002F2024\u002F11\u002FAdobeStock_595764064.jpeg 2400w\" sizes=\"(min-width: 720px) 720px\">\u003C\u002Ffigure>\u003Ch2 id=\"%F0%9F%92%AC-why-are-llms-so-verbose\">💬 Why are LLMs so verbose?\u003C\u002Fh2>\u003Cp>There are many reasons why Claude, GPT-4, Mistral & co. may adopt a conversational approach. Usually, LLMs refuse to translate the input in these four scenarios:\u003C\u002Fp>\u003Col>\u003Cli>❌ \u003Cstrong>Request for translation of non-natural language\u003C\u002Fstrong>\u003C\u002Fli>\u003Cli>©️ \u003Cstrong>Use of copyrighted content in the prompt\u003C\u002Fstrong>\u003C\u002Fli>\u003Cli>💣 \u003Cstrong>Detection of harmful content\u003C\u002Fstrong>\u003C\u002Fli>\u003Cli>🌪️ \u003Cstrong>Unclear content\u003C\u002Fstrong>\u003C\u002Fli>\u003C\u002Fol>\u003Cp>When you request context-sensitive translations, the LLMs may also provide comments along with the translated text or offer multiple translation options.\u003C\u002Fp>\u003Cp>Let's take a look at some examples to illustrate LLM verbosity.\u003C\u002Fp>\u003Ch3 id=\"1-copyrighted-content\">1. Copyrighted content\u003C\u002Fh3>\u003Cp>First, let's compare how GPT-4, Claude 3.5, and Mistral Large deal with copyrighted content.\u003C\u002Fp>\u003Cp>I asked the models to translate the first sentence of my favorite book. This is how each LLM responded to my request:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"1030\" height=\"315\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-Tolkien-1.JPG 1030w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>The excerpt from \"The Lord of the Rings: The Fellowship of The Ring\" by Tolkien translated into Spanish by GPT-4.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-2-Claude-Tolkien.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"814\" height=\"335\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-2-Claude-Tolkien.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-2-Claude-Tolkien.JPG 814w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>The excerpt from \"The Lord of the Rings: The Fellowship of The Ring\" by Tolkien translated into Spanish by Claude 3.5.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-3-Mistral-Tolkien.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"843\" height=\"665\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-3-Mistral-Tolkien.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-3-Mistral-Tolkien.JPG 843w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>The excerpt from \"The Lord of the Rings: The Fellowship of The Ring\" by Tolkien translated into Spanish by Mistral Large.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>As you can see, only \u003Cstrong>Mistral was brave enough to indicate the intricacies of translating well-known literature\u003C\u002Fstrong>. It was also the only model that recognized the title and author. However, none of the models refused to translate the content due to potential copyright infringement.\u003C\u002Fp>\u003Cp>The models became more verbose when I typed a more modern text:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-4-Claude-Christina.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"921\" height=\"518\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-4-Claude-Christina.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-4-Claude-Christina.JPG 921w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>An attempt to translate the lyrics of \"Hurt\" by Christina Aguilera (2006) in Claude 3.5.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-5-Mistral-Christina.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"817\" height=\"586\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-5-Mistral-Christina.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-5-Mistral-Christina.JPG 817w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>An attempt to translate the lyrics of \"Hurt\" by Christina Aguilera (2006) in Mistral Large.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-6-Chat-gpt-Christina.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"888\" height=\"260\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-6-Chat-gpt-Christina.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-6-Chat-gpt-Christina.JPG 888w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 translates the lyrics of \"Hurt\" by Christina Aguilera (2006).\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>In this scenario, \u003Cstrong>only Claude refused to translate the content, citing copyright violation\u003C\u002Fstrong>. Mistral recognized the lyrics but\u003Cstrong> \u003C\u002Fstrong>translated the text into Spanish anyway, whereas GPT-4 seemed unconcerned about potential copyright infringement.\u003C\u002Fp>\u003Ch3 id=\"2-non-natural-language\">2. Non-natural language\u003C\u002Fh3>\u003Cp>In the next test round, I prompted the models to translate a URL address and an incomplete phrase containing random characters. The general prompt in each model was still the same as above: \"Act as a professional English-Spanish (ES) translator. Translate the following content into Spanish\".\u003C\u002Fp>\u003Cp>This is how the models responded:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-7-Mistral-http.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"938\" height=\"206\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-7-Mistral-http.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-7-Mistral-http.JPG 938w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral Large refuses to translate a URL address.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-8-Chat-gpt-http-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"996\" height=\"232\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-8-Chat-gpt-http-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-8-Chat-gpt-http-1.JPG 996w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 refuses to translate a URL address.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-9-Claude-http.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"919\" height=\"265\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-9-Claude-http.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-9-Claude-http.JPG 919w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude refuses to translate a URL address, replying in Spanish.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>All three models decided that translating such content is mission impossible, which makes perfect sense\u003C\u002Fstrong>. In real-world scenarios, translators don't translate URLs either. However, each model justified the refusal differently, adopting a less or more talkative approach.\u003C\u002Fp>\u003Cp>Here's how the models reacted to phrases with random characters:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-10-Claude-chars.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"984\" height=\"245\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-10-Claude-chars.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-10-Claude-chars.JPG 984w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude provides a translation for an unclear phrase.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-11-Mistral-chars.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"862\" height=\"504\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-11-Mistral-chars.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-11-Mistral-chars.JPG 862w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral breaks down the phrase, trying to provide a possible translation.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-12-Chat-gpt-chars.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"881\" height=\"347\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-12-Chat-gpt-chars.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-12-Chat-gpt-chars.JPG 881w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 explains the phrase might be incomplete.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>In this scenario, \u003Cstrong>only Claude provided a direct translation instead of a comment\u003C\u002Fstrong>. GPT-4 and Mistral attempted to translate the phrase but explained that it might be incomplete.\u003C\u002Fp>\u003Ch3 id=\"3-unclear-or-confusing-content\">3. Unclear or confusing content\u003C\u002Fh3>\u003Cp>What happens when you ask an LLM to translate a gibberish text?\u003C\u002Fp>\u003Cp>It might engage in lengthy conversations. Here's an example:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-13-Mistral-verbs.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"961\" height=\"990\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-13-Mistral-verbs.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-13-Mistral-verbs.JPG 961w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral explaining why the phrase can't be translated.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-verbs-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"991\" height=\"531\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-1-Chatgpt-verbs-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-1-Chatgpt-verbs-1.JPG 991w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 refuses to translate the content.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-15-Claude-verbs.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"893\" height=\"403\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-15-Claude-verbs.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-15-Claude-verbs.JPG 893w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude provides a literal translation.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>Each model acted differently\u003C\u002Fstrong>: Claude provided a useless output for the useless input, GPT-4 shortly declined to translate the phrase, and Mistral not only refused to translate the text but also offered a long-winded grammatical explanation.\u003C\u002Fp>\u003Ch3 id=\"4-context-sensitive-translation\">4. Context-sensitive translation\u003C\u002Fh3>\u003Cp>In the last round, I switched to another language and provided short phrases that may have double meanings. This was the response in each model:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-16-Chat-gpt-Hot-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"986\" height=\"694\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-16-Chat-gpt-Hot-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-16-Chat-gpt-Hot-1.JPG 986w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT-4 provides Polish translations, randomly deciding on which context to choose.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-17-Mistral-Hot.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"796\" height=\"653\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-17-Mistral-Hot.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-17-Mistral-Hot.JPG 796w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Mistral provides two options for both phrases.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-18-Claude-Hot.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"906\" height=\"499\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-18-Claude-Hot.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-18-Claude-Hot.JPG 906w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude refuses to translate the first phrase, claiming it doesn't feel comfortable completing this task. It also refuses to translate the second phrase, explaining that it goes against its values\u003C\u002Fem>.\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>Each model adopted a different approach\u003C\u002Fstrong>: GPT-4 translated the content without the context and Mistral provided more options to account for contextual subtleties, while Claude refused to undertake the task and asked if there was anything else it could help me with.\u003C\u002Fp>\u003Cblockquote>🎙️ Could these LLMs soon become good enough to replace translators? No one knows for sure but we gave our take in \u003Ca href=\"https:\u002F\u002Flocalazy.com\u002Fblog\u002Fs01-ep-03-bridging-the-gap-podcast\">this episode of Bridging the Gap podcast.\u003C\u002Fa>\u003C\u002Fblockquote>\u003Ch2 id=\"%F0%9F%A4%94-whats-wrong-with-verbosity\">🤔 What's wrong with verbosity?\u003C\u002Fh2>\u003Cp>There are cases when lengthy LLM responses might be problematic.\u003C\u002Fp>\u003Cp>The above examples show that the verbosity factor can vary across language pairs and LLMs. This, in turn, can lead to \u003Cstrong>an inconsistent user experience\u003C\u002Fstrong>. For example, users might receive concise translations for some language pairs but excessively verbose outputs for others. What's more, for the same input, different LLMs may generate responses with varying degrees of verbosity, making it challenging to predict the output quality. On top of that, extracting relevant content from the lengthy LLM responses might be time-consuming and frustrating. 🙇‍♀️ It can also lead to cognitive overload, which becomes particularly challenging in time-sensitive situations or when you work with technical or specialized content that already requires significant mental effort.\u003C\u002Fp>\u003Cp>In cases where LLMs refuse to translate due to perceived safety or copyright concerns, you are left without the translation you need, which may discourage you from using an LLM for translation purposes. In fact, \u003Cstrong>verbose LLM outputs often lead to lower-quality translations\u003C\u002Fstrong>. The paper mentioned above shows that highly verbose translations tend to be less accurate, introduce errors and redundancies, or deviate from the original meaning. This can significantly impact the usefulness and reliability of LLMs.\u003C\u002Fp>\u003Cp>Finally, overly verbose outputs can lead to\u003Cstrong> increased computational resources and time required for processing\u003C\u002Fstrong>, which can slow down applications and increase costs for users.\u003C\u002Fp>\u003Cblockquote>📚\u003Cstrong> Related\u003C\u002Fstrong>: \u003Ca href=\"https:\u002F\u002Flocalazy.com\u002Fblog\u002Fhow-to-use-chatgpt-to-your-advantage-in-translation-with-examples-gpt-series-1\">How to use ChatGPT to your advantage in translation (with examples)\u003C\u002Fa>\u003C\u002Fblockquote>\u003Ch2 id=\"%E2%98%9D%EF%B8%8F3-tips-to-reduce-verbosity-bias-in-llms\">☝️3 tips to reduce verbosity bias in LLMs\u003C\u002Fh2>\u003Ch3 id=\"write-effective-prompts\">Write effective prompts\u003C\u002Fh3>\u003Cp>What can you do to avoid Claude's, Mistral's, or ChatGPT's flowery language? When verbosity becomes a serious obstacle to your translation projects, you can take your prompting to the next level. \u003C\u002Fp>\u003Cp>For example, in the case of context-sensitive translations, the best approach is to provide precise context. This is how the prompts above can be modified to obtain more concise responses:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-20-Mistral-Context.png\" class=\"kg-image\" alt loading=\"lazy\" width=\"1204\" height=\"505\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-20-Mistral-Context.png 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-20-Mistral-Context.png 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-20-Mistral-Context.png 1204w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Polish translation in Mistral becomes more natural with a modified prompt.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-21-Claude-Context.png\" class=\"kg-image\" alt loading=\"lazy\" width=\"1282\" height=\"481\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-21-Claude-Context.png 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-21-Claude-Context.png 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-21-Claude-Context.png 1282w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>Claude provides a more accurate translation when the prompt is more specific.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-22-GPT-Context.png\" class=\"kg-image\" alt loading=\"lazy\" width=\"1260\" height=\"585\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-22-GPT-Context.png 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-22-GPT-Context.png 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-22-GPT-Context.png 1260w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>GPT also generates a context-aware translation once all details are provided.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>\u003Cstrong>Each response is different, but all are correct\u003C\u002Fstrong>. The models followed the prompt precisely and generated contextually relevant responses. Mistral still added its verbose touch by including a comment, but it's not lengthy and shouldn't frustrate the impatient users.\u003C\u002Fp>\u003Ch3 id=\"avoid-gibberish-input\">Avoid gibberish input\u003C\u002Fh3>\u003Cp>Effective prompts are not the only way out of the verbosity maze. Another key step is to \u003Cstrong>avoid requesting for translation of non-human language\u003C\u002Fstrong>, as this will always lead to confusion. LLMs won't translate URL links, snippets of programming code, or incomplete phrases made up of random characters. \u003C\u002Fp>\u003Cp>Simply put, don't expect LLMs to translate anything a human wouldn't translate. Teasing LLMs with incomplete, grammatically incorrect inputs such as \"has been are,\" as demonstrated above, is not a good idea either. To be on the safe side, make sure both your prompt and source text are of high quality.\u003C\u002Fp>\u003Cblockquote>Verbosity can become a serious obstacle to your translation projects. Working on better prompts and discarding non-human language in your inputs is helpful to reduce it\u003C\u002Fblockquote>\u003Ch3 id=\"adjust-settings-in-llms\">Adjust settings in LLMs\u003C\u002Fh3>\u003Cp>There's one more strategy you can follow to make Claude, Mistral, or ChatGPT less verbose: \u003Cstrong>tweak the settings\u003C\u002Fstrong>. ⚙️ For example, you can lower \u003Ca href=\"https:\u002F\u002Fmedium.com\u002F@marketing_novita.ai\u002Fwhat-are-large-language-model-settings-temperature-top-p-and-max-tokens-a482d8d817b2\">the temperature parameter\u003C\u002Fa> to reduce verbosity and make the model's outputs more focused.\u003C\u002Fp>\u003Cp>You can also adjust the top-p value to control the randomness of the model's outputs. A lower value (e.g., 0.7-0.8) might lead to more concise responses. However, \u003Ca href=\"https:\u002F\u002Fdocs.anthropic.com\u002Fen\u002Fapi\u002Fmessages\" rel=\"noopener noreferrer nofollow\">as stated in the documentation of  OpenAI, Anthropic\u003C\u002Fa> (developer of Claude), and Mistral AI, \u003Cstrong>you should either alter temperature or top_p, but not both\u003C\u002Fstrong>.\u003C\u002Fp>\u003Cp>Finally, in all three models, you can set a lower max tokens value to force the model to be more concise by limiting the length of its response. If you choose this approach, get ready for some in-depth tool exploration, as you won't be able to find these settings directly in the chat. For example, in Mistral, you can create a new agent under the tab La Plateforme, define the temperature and other values, test the prompts with your new settings, and finally deploy the new agent.\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"1477\" height=\"957\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG 1000w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-23-mistral-agent.JPG 1477w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>You can adjust the temperature settings in Mistral by creating a new agent under the La Plateforme tab.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Cp>In most LLMs, top_p values and temperature can also be modified via API.\u003C\u002Fp>\u003Cp>This is how Mistral responded once I set the temperature to 0 in my new agent:\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-card-hascaption\">\u003Cimg src=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-24-Mistral-has-been-are-temp-1.JPG\" class=\"kg-image\" alt loading=\"lazy\" width=\"764\" height=\"413\" srcset=\"https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2024\u002F11\u002FImage-24-Mistral-has-been-are-temp-1.JPG 600w, https:\u002F\u002Fghost.localazy.com\u002Fcontent\u002Fimages\u002F2024\u002F11\u002FImage-24-Mistral-has-been-are-temp-1.JPG 764w\" sizes=\"(min-width: 720px) 720px\">\u003Cfigcaption>\u003Cem>With the temperature set to 0, Mistral provides a less verbose response.\u003C\u002Fem>\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003Ch2 id=\"%E2%9C%94%EF%B8%8F-final-thoughts\">✔️ Final thoughts\u003C\u002Fh2>\u003Cp>While refusing to translate the content or providing extra comments might be helpful in some cases, long model responses are usually frustrating for users looking for quick solutions. Verbosity might be a challenge, but there are proven ways to overcome it. \u003Cstrong>So, next time you're wondering: \"Why is ChatGPT so verbose?\", be strategic.\u003C\u002Fstrong> Focus on refining your prompt engineering for translation, adjust the model settings, and ensure your input is free of copyrighted text or non-human language.\u003C\u002Fp>\u003Cp>With a few simple steps, you, too, can outsmart your machine.\u003C\u002Fp>\u003Cblockquote>🦾 Do you want to use OpenAI in your Localazy projects? Head over to \u003Cem>\u003Ca href=\"https:\u002F\u002Flocalazy.com\u002Fconsole\u002Fai\">Localazy Console > Localazy AI\u003C\u002Fa> and try it after adding your own token!\u003C\u002Fem>\u003C\u002Fblockquote>","public","none","2024-11-11T14:33:05.000+01:00",[1995],{"id":1854,"name":1855,"slug":1856,"profile_image":1857,"cover_image":7,"bio":1996,"website":1997,"location":1998,"facebook":7,"twitter":7,"meta_title":7,"meta_description":7,"url":1999},"Localization consultant, prompt engineer, and translator specializing in IT. 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