2 citations · 11 across the 51 of their papers we have counts for
5 papers · 1 filter
Fed-SE: Federated Self-Evolution for Privacy-Constrained Multi-Environment LLM Agents
Xiang Chen, Yuling Shi, Qizhen Lan +4
LLM agents are widely deployed in complex interactive tasks, yet privacy constraints often preclude centralized optimization and co-evolution across dynamic environments. Despite t…
H4G: Unlocking Faithful Inference for Zero-Shot Graph Learning in Hyperbolic Space
Heng Zhang, Tianyi Zhang, Zijun Liu +6
Text-attributed graphs are widely used across domains, offering rich opportunities for zero-shot learning via graph-text alignment. However, existing methods struggle with tasks re…
GraphShaper: Geometry-aware Alignment for Improving Transfer Learning in Text-Attributed Graphs
Heng Zhang, Tianyi Zhang, Yuling Shi +6
Graph foundation models represent a transformative paradigm for learning transferable representations across diverse graph domains. Recent methods leverage large language models to…
Attention as a Compass: Efficient Exploration for Process-Supervised RL in Reasoning Models
Runze Liu, Jiakang Wang, Yuling Shi +11
Reinforcement Learning (RL) has shown remarkable success in enhancing the reasoning capabilities of Large Language Models (LLMs). Process-Supervised RL (PSRL) has emerged as a more…
Pruning the Unsurprising: Efficient LLM Reasoning via First-Token Surprisal
Wenhao Zeng, Yaoning Wang, Chao Hu +4
Large Reasoning Models (LRMs) have demonstrated remarkable capabilities by scaling up the length of Chain-of-Thought (CoT). However, excessively long reasoning traces pose substant…