Author

Philippe Modard

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#artificial intelligence Preprint Sep 2026

Benchmarking Prompt Optimization of Large Language Models With Chess

A chess benchmark built from 1,118 Lichess puzzles is introduced to study APO for frozen LLMs: it is used to evaluate six APO algorithms on eight target models, measuring not only baseline strength but also how much each model responds to optimization and whether optimized prompts transfer across models and to game pla...

Timothée Lesort, Alejandra López de Aberasturi-Gómez, Tristan Karch et al. · 0 citations

#small language model Preprint Aug 2026

Future Querying: Can LLMs Serve as Implicit Medical World Models?

This work introduces future querying, a paradigm that probes whether large language models can function as implicit medical world models by evaluating their ability to answer time-indexed clinical queries about a patient's future, and shows that small, locally fine-tuned open-weight models can match or approach larger...

Siri Willems, James Butterworth, L. Goetschalckx et al. · 0 citations