Cannada A. Lewis — accepted AI-conference papers

2025

Mastering Board Games by External and Internal Planning with Language Models

John Schultz, Jakub Adamek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin +10

ICML 2025spotlight

Advancing planning and reasoning capabilities of Large Language Models (LLMs) is one of the key prerequisites towards unlocking their potential for performing reliably in complex and impactful domains. In this paper, we aim to demonstrate this across board games (Chess, Fischer Random / Chess960, Co…

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2024

Amortized Planning with Large-Scale Transformers: A Case Study on Chess

Anian Ruoss, Gregoire Deletang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt +4

NeurIPS 2024poster

This paper uses chess, a landmark planning problem in AI, to assess transformers’ performance on a planning task where memorization is futile — even at a large scale. To this end, we release ChessBench, a large-scale benchmark dataset of 10 million chess games with legal move and value annotations (…

Cited by 6 Source ↗PDF ↗code ↗Scholar ↗