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Reality Check: Natural Language Processing in the era of Large Language Models| title | Reality Check: Natural Language Processing in the era of Large Language Models |
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| start_date | 2024/05/15 |
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| schedule | 17h-18h |
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| online | no |
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| location_info | sur Zoom |
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| summary | Large language models (LLMs) contributed to a major breakthrough in NLP, both in terms of understanding natural language queries, commands or questions; and in generating relevant, coherent, grammatical, human-like text. LLMs like ChatGPT became a product used by many, for getting advice, writing essays, troubleshooting and writing code, creative writing, and more. This calls for a reality check: which NLP tasks did LLMs solve? What are the remaining challenges, and which new opportunities did LLMs create?
In this talk, I will discuss several areas of NLP that can benefit from but are still challenging for LLMs: grounding, i.e. interpreting language based on non-linguistic context; reasoning; and real-world applications. Finally, I will argue that the standard benchmarking and evaluation techniques used in NLP need to drastically change in order to provide a more realistic picture of current capabilities. |
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| responsibles | Bernard |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2024/05/13 12:57 UTC |
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