2 citations · 2 across the 4 of their papers we have counts for
4 papers
Don't Think Twice! Over-Reasoning Impairs Confidence Calibration
Romain Lacombe, Kerrie Wu, Eddie Dilworth
Large Language Models deployed as question answering tools require robust calibration to avoid overconfidence. We systematically evaluate how reasoning capabilities and budget affe…
Non-Canonical Crosslinks Confound Evolutionary Protein Structure Models
Romain Lacombe
Evolution-based protein structure prediction models have achieved breakthrough success in recent years. However, they struggle to generalize beyond evolutionary priors and on seque…
Accelerating the Generation of Molecular Conformations with Progressive Distillation of Equivariant Latent Diffusion Models
Romain Lacombe, Neal Vaidya
Recent advances in fast sampling methods for diffusion models have demonstrated significant potential to accelerate generation on image modalities. We apply these methods to 3-dime…
ClimateX: Do LLMs Accurately Assess Human Expert Confidence in Climate Statements?
Romain Lacombe, Kerrie Wu, Eddie Dilworth
Evaluating the accuracy of outputs generated by Large Language Models (LLMs) is especially important in the climate science and policy domain. We introduce the Expert Confidence in…