In-context Learning - A New Paradigm in NLP?

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In this video, we focus on the topic of in-context learning (ICL). This video is based on a recent review paper on ICL.

ICL is an exciting new paradigm in NLP where large language models (LLMs) make predictions based on contexts augmented with just a few training examples. LLMs are able to extract patterns from the examples provided in the context, and use them to perform many complex NLP tasks.

Abstract: With the increasing ability of large language models (LLMs), in-context learning (ICL) has become a new paradigm for natural language processing (NLP), where LLMs make predictions only based on contexts augmented with a few training examples. It has been a new trend exploring ICL to evaluate and extrapolate the ability of LLMs. In this paper, we aim to survey and summarize the progress, challenges, and future work in ICL. We first present a formal definition of ICL and clarify its correlation to related studies. Then, we organize and discuss advanced techniques of ICL, including training strategies, prompting strategies, and so on. Finally, we present the challenges of ICL and provide potential directions for further research. We hope our work can encourage more research on uncovering how ICL works and improving ICL in future work.

#nlproc #nlp #artificialintelligence #ml #deeplearning

The NLP Lab

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That is a good thing imho, meaning wow well done! Share details of how you did the lip sync, etc. Nice agent too. Love the style and the coverage of this most important prompt based sidecar student model to a teacher model and presentation of context learning. I've been really using it and RLHF lately and can't believe how performant it is finding solutions to a well described problem. Kudos and keep up great coverage and excellent analysis on making it easier for others. --Much appreciated!! 🍮 yum

AaronWacker

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