Web本身LM具有初步的文本生成能力，进一步使用「in-context learning/chain of thought」等各种方法来进一步提升在模型知识库检索的效果，使用instruction tuning等方法来优化模型知识库的布局。 step3：如何让答案看起来更合理、更符合人类社会的规则？ WebApr 11, 2024 · Large language models (LLMs) are able to do accurate classification with zero or only a few examples (in-context learning). We show a prompting system that enables regression with uncertainty for in-context learning with frozen LLM (GPT-3, GPT-3.5, and GPT-4) models, allowing predictions without features or architecture tuning. By …
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WebApr 12, 2024 · Here, we performed the optimization using the synthesis procedure of catalysts to predict properties. Working with natural language mitigates difficulty synthesizability since the literal synthesis procedure is the model's input. We showed that in-context learning could improve past a model context window (maximum number of … WebApr 10, 2024 · The In-Context Learning (ICL) is to understand a new task via a few demonstrations (aka. prompt) and predict new inputs without tuning the models. While it has been widely studied in NLP, it is still a relatively new area of research in computer vision. To reveal the factors influencing the performance of visual in-context learning, this paper … rhymes with hence
[2301.00234] A Survey on In-context Learning - arxiv.org
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