Jeremy Shar — accepted AI-conference papers

2025

DataRater: Meta-Learned Dataset Curation

Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa Zintgraf, Matteo Hessel, Jeremy Shar +6

NeurIPS 2025poster

The quality of foundation models depends heavily on their training data. Consequently, great efforts have been put into dataset curation. Yet most approaches rely on manual tuning of coarse-grained mixtures of large buckets of data, or filtering by hand-crafted heuristics. An approach that is ultima…

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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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