collaborators

9 papers

cs.CV2026

Topology-Aware Layer Pruning for Large Vision-Language Models

Pengcheng Zheng, Chaoning Zhang, Ya Wen +10

Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning, while recent extensions that incorporate visual inputs enable th…

cs.NE2026

Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models

Xudong Wang, Chaoning Zhang, Chenghao Li +10

Large Language Models (LLMs) have demonstrated strong capabilities in complex reasoning tasks, while recent prompting strategies such as Chain-of-Thought (CoT) have further elevate…

cs.CL2026

Transforming External Knowledge into Triplets for Enhanced Retrieval in RAG of LLMs

Xudong Wang, Chaoning Zhang, Qigan Sun +7

Retrieval-Augmented Generation (RAG) mitigates hallucination in large language models (LLMs) by incorporating external knowledge during generation. However, the effectiveness of RA…

cs.CL2026

TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models

Jiaquan Zhang, Qigan Sun, Chaoning Zhang +11

Enhancing the reasoning capability of large language models (LLMs) remains a core challenge in natural language processing. The Chain-of-Thought (CoT) paradigm dominates practical…

cs.AI2026

Efficient and Interpretable Multi-Agent LLM Routing via Ant Colony Optimization

Xudong Wang, Chaoning Zhang, Jiaquan Zhang +8

Large Language Model (LLM)-driven Multi-Agent Systems (MAS) have demonstrated strong capability in complex reasoning and tool use, and heterogeneous agent pools further broaden the…

cs.AI2026

Learning Global Hypothesis Space for Enhancing Synergistic Reasoning Chain

Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +9

Chain-of-Thought (CoT) has been shown to significantly improve the reasoning accuracy of large language models (LLMs) on complex tasks. However, due to the autoregressive, step-by-…