Princeton trains 4B LLM to 2700 Elo in chess with move explanations
Read original source →arxiv.orgA 4B-parameter language model reached 2700 Elo in chess while explaining its moves, with no plateau when training stopped. The team says the technique — a natural-language analogue of the AlphaZero algorithm — applies to other games, robotics, and computer use.
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Language Models that Play Chess and Explain Their Movesarxiv.org
Princeton researchers train a 4B LLM to reach 2700 Elo in chess (with no signs of a plateau when they stopped training) and can explain its moves accurately. They say the training technique can also be applied to other games, robotics, and computer usefixupx.com
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