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cs.LG2026
Making Expert Reasoning Learnable with Self-Distillation
Ethan Mendes, Jungsoo Park, Alan Ritter
Improving the reasoning capabilities of large language models (LLMs) typically relies either on the model's ability to sample a correct solution to be reinforced or the existence o…
cs.LG2025
Language Models can Self-Improve at State-Value Estimation for Better Search
Ethan Mendes, Alan Ritter
Collecting ground-truth rewards or human demonstrations for multi-step reasoning tasks is often prohibitively expensive, particularly in interactive domains such as web tasks. We i…