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cs.AI2026
Procedural Memory Distillation: Online Reflection for Self-Improving Language Models
Ye Liu, Srijan Bansal, Bo Pang +6
Reinforcement learning with verifiable rewards (RLVR), along with recent selfdistillation variants such as SDPO, evaluates each rollout against a verifier and updates the policy fr…
cs.AI2025
Self-Abstraction from Grounded Experience for Plan-Guided Policy Refinement
Hiroaki Hayashi, Bo Pang, Wenting Zhao +6
Large language model (LLM) based agents are increasingly used to tackle software engineering tasks that require multi-step reasoning and code modification, demonstrating promising…
cs.AI2025
Reasoning Curriculum: Bootstrapping Broad LLM Reasoning from Math
Bo Pang, Deqian Kong, Silvio Savarese +2
Reinforcement learning (RL) can elicit strong reasoning in large language models (LLMs), yet most open efforts focus on math and code. We propose Reasoning Curriculum, a simple two…