3 papers
cs.AI2026
GRAIN: Bridging Name and Narrative Shifts in Real-World Graph Reasoning through Invariance-Rewarded Agentic RL
Zike Yuan, Han Zhang, Jianzhi Yan +10
Despite their potential in standardized graph tasks, Large Language Models (LLMs) remain brittle to real-world shifts in node identifiers and task formulation. While deterministic…
cs.LG2025
GEPO: Group Expectation Policy Optimization for Stable Heterogeneous Reinforcement Learning
Han Zhang, Ruibin Zheng, Zexuan Yi +16
As single-center computing approaches power constraints, decentralized training becomes essential. However, traditional Reinforcement Learning (RL) methods, crucial for enhancing l…
cs.LG2024
Correcting Large Language Model Behavior via Influence Function
Han Zhang, Zhuo Zhang, Yi Zhang +8
Recent advancements in AI alignment techniques have significantly improved the alignment of large language models (LLMs) with static human preferences. However, the dynamic nature…