In-Context Learning (ICL)

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• A Survey on In-context Learning | Q. Dong, L. Li, D. Dai, C. Zheng, Z. Wu, B. Chang, X. Sun, J. Xu, L. Li, Z. Sui - arXiv Cornell University
• Generative AI ... Conversational AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's Bing ... You ...Google's Bard ... Baidu's Ernie
• Capabilities
  • Video/Image ... Vision ... Colorize ... Image/Video Transfer Learning
  • End-to-End Speech ... Synthesize Speech ... Speech Recognition
• Discriminative vs. Generative
• Assistants ... Agents ... Negotiation ... HuggingGPT ... LangChain
• Context-based learning | Wikipedia

In-context learning (ICL) is a new paradigm in natural language processing (NLP) where large language models (LLMs) make predictions based on contexts augmented with just a few training examples1. LLMs are able to extract patterns from the examples provided in the context and use them to perform many complex NLP tasks. - In-context Learning - A New Paradigm in NLP? | The Global NLP Lab