collaborators

6 papers

cs.CV2026

Fixed Anchors Are Not Enough: Dynamic Retrieval and Persistent Homology for Dataset Distillation

Muquan Li, Hang Gou, Yingyi Ma +3

Decoupled dataset distillation (DD) compresses large corpora into a few synthetic images by matching a frozen teacher's statistics. However, current residual-matching pipelines rel…

cs.LG2026

KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation

Qizhi Chen, Chao Qi, Yihong Huang +5

Graph-based Retrieval-Augmented Generation (GraphRAG) constructs the Knowledge Graph (KG) from external databases to enhance the timeliness and accuracy of Large Language Model (LL…

cs.LG2026

Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization

Rongzheng Wang, Yihong Huang, Muquan Li +6

Large Language Models (LLMs) have advanced the field of Combinatorial Optimization through automated heuristic generation. Instead of relying on manual design, this LLM-Driven Heur…

cs.IR2025

NeuroPath: Neurobiology-Inspired Path Tracking and Reflection for Semantically Coherent Retrieval

Junchen Li, Rongzheng Wang, Yihong Huang +3

Retrieval-augmented generation (RAG) greatly enhances large language models (LLMs) performance in knowledge-intensive tasks. However, naive RAG methods struggle with multi-hop ques…

cs.CL2025

DSAS: A Universal Plug-and-Play Framework for Attention Optimization in Multi-Document Question Answering

Jiakai Li, Rongzheng Wang, Yizhuo Ma +3

While large language models (LLMs) show considerable promise across various fields, they have notable limitations in handling multi-document question answering (Multi-doc QA) tasks…

cs.AI2025

GraphCogent: Mitigating LLMs' Working Memory Constraints via Multi-Agent Collaboration in Complex Graph Understanding

Rongzheng Wang, Shuang Liang, Qizhi Chen +6

Large language models (LLMs) show promising performance on small-scale graph reasoning tasks but fail when handling real-world graphs with complex queries. This phenomenon arises f…