activity
20242026
collaborators

10 papers

cs.CR2026

Safe-FedLLM: Delving into the Safety of Federated Large Language Models

Mingxiang Tao, Yu Tian, Wenxuan Tu +3

Federated learning (FL) addresses privacy and data-silo issues in the training of large language models (LLMs). Most prior work focuses on improving the efficiency of federated lea…

cs.AI2026

ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox

Yuanyang Li, Xue Yang, Longyue Wang +2

Current LLM agents are proficient at calling isolated APIs but struggle with the "last mile" of commercial software automation. In real-world scenarios, tools are not independent;…

cs.CL2026

DiffER: Diffusion Entity-Relation Modeling for Reversal Curse in Diffusion Large Language Models

Shaokai He, Kaiwen Wei, Xinyi Zeng +5

The "reversal curse" refers to the phenomenon where large language models (LLMs) exhibit predominantly unidirectional behavior when processing logically bidirectional relationships…

cs.CL2025

ComfyUI-R1: Exploring Reasoning Models for Workflow Generation

Zhenran Xu, Yiyu Wang, Xue Yang +5

AI-generated content has evolved from monolithic models to modular workflows, particularly on platforms like ComfyUI, enabling customization in creative pipelines. However, craftin…

cs.CL2025

ComfyUI-Copilot: An Intelligent Assistant for Automated Workflow Development

Zhenran Xu, Xue Yang, Yiyu Wang +7

We introduce ComfyUI-Copilot, a large language model-powered plugin designed to enhance the usability and efficiency of ComfyUI, an open-source platform for AI-driven art creation.…

cs.CL2025

From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling

Zhengyu Chen, Yudong Wang, Teng Xiao +5

Recent advancements in improving the reasoning capabilities of Large Language Models have underscored the efficacy of Process Reward Models (PRMs) in addressing intermediate errors…