5 papers · 1 filter
Predicting Privileged Information Effectiveness for On-Policy Self-Distillation
Kaijian Zou, Emiliano Penaloza, MohammadHossein Rezaei +5
On-policy self-distillation (OPSD) enables large language models (LLMs) to learn from privileged information (PI) without a separate teacher model. However, prior work largely trea…
Rubric-Guided Self-Distillation: Post-Training Without Rubric Verifiers
MohammadHossein Rezaei, Anas Mahmoud, Zihao Wang +6
Rubrics have emerged as an alternative to RLVR in open-ended domains where a single ground-truth final answer is not available. Existing rubric-based training methods rely on an LL…
From Residuals to Reasons: LLM-Guided Mechanism Inference from Tabular Data
Mohammad R. Rezaei, Rahul G. Krishnan
A persistent challenge in machine learning for scientific applications is jointly achieving prediction and understanding. Statistical models excel on structured data but operate as…
SWE Atlas: Benchmarking Coding Agents Beyond Issue Resolution
Mohit Raghavendra, Soham Dan, Miguel Romero Calvo +12
We introduce SWE Atlas, a benchmark suite for coding agents spanning three professional software engineering workflows: Codebase Q&A (124 tasks), Test Writing (90 tasks), and Refac…
Process Rewards for Outcome-Guided Reasoning Steps in LLM Reinforcement Learning
Mohammad Rezaei, Jens Lehmann, Sahar Vahdati
Mathematical reasoning in large language models has improved substantially with reinforcement learning using verifiable rewards, where final answers can be checked automatically an…