We have 4 of 9 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
The second KDD Day on AI Reasoning brings together researchers and practitioners from academia and industry to examine how large language models and foundation models can be made more capable, reliable, interpretable, and efficient.
RG-OPD bridges sparse verifier rewards and dense teacher logits, preserving token-level supervision while filtering misleading teacher signals, and produces stronger distilled students, outperforming both vanilla reverse-KL distillation and the recent TSD-KD baseline.
This work proposes AHEAD, a step-aware framework that matches different supervision sources to different step types and solves tasks within tighter interaction budgets than outcome-only RL and prior self-distillation baselines.
Large language models and foundation models are increasingly embedded in reasoning systems that plan, invoke tools, use memory, gather evidence, and iteratively refine their outputs. The second KDD Day on AI Reasoning brings together researchers and practitioners from academia and industry to examine how these systems...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
