7 citations · 17 across the 14 of their papers we have counts for
6 papers · 1 filter
Process Reward Informed Tree Rollout for Effective Multi-Turn RL
Xintong Li, Sha Li, Yuwei Zhang +8
Reinforcement learning (RL) has become a key approach for training LLM agents, yet popular methods such as GRPO/RLOO rely on multiple independently sampled complete trajectories fo…
HERO: Hindsight-Enhanced Reflection from Environment Observations for Agentic Self-Distillation
Haoran Liu, Yuwei Zhang, Xiyao Li +2
Reinforcement learning typically improves multi-turn agent capabilities through the terminal outcome of the trajectories, which makes it difficult to determine credit assignments f…
CoMem: Context Management with A Decoupled Long-Context Model
Yuwei Zhang, Chengyu Dong, Shuowei Jin +11
Context management enables agentic models to solve long-horizon tasks through iterative summarization of previous interaction histories. However, this process typically incurs subs…
ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation
Zhongkai Yu, Yichen Lin, Chenyang Zhou +12
Existing API-based agentic systems for RTL code generation are fundamentally misaligned with industrial practice: they assume a golden testbench is available at generation time, re…
Learning with Rare Success but Rich Feedback via Reflection-Enhanced Self-Distillation
Yuwei Zhang, Sha Li, Changlong Yu +9
Enabling Large Language Models (LLMs) to continuously improve from environmental interactions is a central challenge in post-training. While on-policy self-distillation offers a pr…
RISE: Rule-Driven SQL Dialect Translation via Query Reduction
Xudong Xie, Yuwei Zhang, Wensheng Dou +5
Translating SQL dialects across different relational database management systems (RDBMSs) is crucial for migrating RDBMS-based applications to the cloud. Traditional SQL dialect tr…