8 papers · 1 filter
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…
CAST: Non-Privileged Clipped Asymmetric Self-Teaching with Advantage Flipping for GRPO
Yang Li, Gongle Xue, Yijia Guo +3
Reinforcement learning with verifiable rewards (RLVR), especially Group Relative Policy Optimization (GRPO), has been widely used to improve reasoning in large language models. How…
Beyond Mode Collapse: Distribution Matching for Diverse Reasoning
Xiaozhe Li, Yang Li, Xinyu Fang +10
On-policy reinforcement learning methods like GRPO suffer from mode collapse: they exhibit reduced solution diversity, concentrating probability mass on a single solution once disc…
What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents
Xiaozhe Li, Tianyi Lyu, Yang Li +6
Reinforcement learning can train LLM agents from sparse task rewards, but long-horizon credit assignment remains challenging: a single success-or-failure signal must be distributed…
LACE: Lattice Attention for Cross-thread Exploration
Yang Li, Zirui Zhang, Yang Liu +1
Current large language models reason in isolation. Although it is common to sample multiple reasoning paths in parallel, these trajectories do not interact, and often fail in the s…
Forge: Quality-Aware Reinforcement Learning for NP-Hard Optimization in LLMs
Xiaozhe Li, Xinyu Fang, Shengyuan Ding +5
Large Language Models (LLMs) have achieved remarkable success on reasoning benchmarks through Reinforcement Learning with Verifiable Rewards (RLVR), excelling at tasks such as math…