collaborators

5 papers

cs.CL2026

SrDetection: A Self-Referential Framework for Data Leakage Detection in Code Large Language Models

Shuaimin Li, Liyang Fan, Zeyang Li +9

Evaluating code large language models (Code LLMs) requires reliable detection of data leakage, where benchmark performance is artificially inflated by exposure to benchmark data du…

cs.LG2026

Reverse Flow Matching: A Unified Framework for Online Reinforcement Learning with Diffusion and Flow Policies

Zeyang Li, Sunbochen Tang, Navid Azizan

Diffusion and flow policies are gaining prominence in online reinforcement learning (RL) due to their expressive power, yet training them efficiently remains a critical challenge.…

cs.LG2026

HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization

Zeyang Li, Kaveh Alim, Navid Azizan

Diffusion and flow-matching have emerged as powerful methodologies for generative modeling, with remarkable success in capturing complex data distributions and enabling flexible gu…

cs.CL2026

Automatic Paper Reviewing with Heterogeneous Graph Reasoning over LLM-Simulated Reviewer-Author Debates

Shuaimin Li, Liyang Fan, Yufang Lin +5

Existing paper review methods often rely on superficial manuscript features or directly on large language models (LLMs), which are prone to hallucinations, biased scoring, and limi…

cs.LG2024

Safe Multi-Agent Reinforcement Learning with Convergence to Generalized Nash Equilibrium

Zeyang Li, Navid Azizan

Multi-agent reinforcement learning (MARL) has achieved notable success in cooperative tasks, demonstrating impressive performance and scalability. However, deploying MARL agents in…