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cs.AI2026
Evaluating Multiple LLM Generations with Validated Task Coverage
Florian Le Bronnec, Rio Yokota
Many LLM applications are most useful when they provide several candidate outputs for comparison, validation, or combination. Predominant evaluation settings, however, still focus…
cs.AI2026
LLMs as Acquisition Policies for Finite-Pool Materials Optimization: A Controlled Study
Dino-Rober Demir, Florian Le Bronnec, Rio Yokota
Discovering materials with desirable properties often requires searching large candidate spaces while experimental or computational evaluations remain costly. Active learning addre…