3 papers
cs.LG2026
Affordances Enable Partial World Modeling with LLMs
Khimya Khetarpal, Gheorghe Comanici, Jonathan Richens +5
Full models of the world require complex knowledge of immense detail. While pre-trained large models have been hypothesized to contain similar knowledge due to extensive pre-traini…
stat.ML2025
DataRater: Meta-Learned Dataset Curation
Dan A. Calian, Gregory Farquhar, Iurii Kemaev +9
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…
cs.AI2025
Mastering Board Games by External and Internal Planning with Language Models
John Schultz, Jakub Adamek, Matej Jusup +13
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 a…