NEW: Better In-Context Learning ICL, Improved RAG (Harvard)

New research for an improved In-Context Learning (ICL) of Large Language Models. Also improves the Augmentation part of a RAG system. Deep dive into the learning procedures of a transformer to optimize the learning behavior of AI for ICL. No expensive fine-tuning or pre-training. All right w/ authors: ICLR: IN-CONTEXT LEARNING OF REPRESENTATIONS Core Francisco Park, Andrew Lee, Ekdeep Singh Lubana, Yongyi Yang, Maya Okawa, Kento Nishi, Martin Wattenberg & Hidenori Tanaka CBS-NTT Program in Physics of Intelligence, Harvard University Department of Physics, Harvard University Physics & Informatics Lab, NTT Research Inc. SEAS, Harvard University CSE, University of Michigan, Ann Arbor #airesearch #harvarduniversity #harvard #coding #reasoning