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20242026
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cs.CL2026

VizRAG: Enhancing Retrieval-Augmented Generation with Hypergraph Visualization

Yanbin Wei, Yang Chen, Renling Gan +7

Hypergraph-based RAG systems surpass traditional graph-based approaches by organizing complex n-ary atomic facts among entities, rather than relying solely on binary relationships.…

cs.CL2026

HyperGVL: Benchmarking and Improving Large Vision-Language Models in Hypergraph Understanding and Reasoning

Yanbin Wei, Chun Kang, Siwei Li +11

Large Vision-Language Models (LVLMs) consistently require new arenas to guide their expanding boundaries, yet their capabilities with hypergraphs remain unexplored. In the real wor…

cs.CL2025

Harnessing Adaptive Topology Representations for Zero-Shot Graph Question Answering

Yanbin Wei, Jiangyue Yan, Chun Kang +4

Large Multimodal Models (LMMs) have shown generalized zero-shot capabilities in diverse domain question-answering (QA) tasks, including graph QA that involves complex graph topolog…

cs.CL2025

DynamicMind: A Tri-Mode Thinking System for Large Language Models

Wei Li, Yanbin Wei, Qiushi Huang +4

Modern large language models (LLMs) often struggle to dynamically adapt their reasoning depth to varying task complexities, leading to suboptimal performance or inefficient resourc…

cs.CL2024

GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning

Yanbin Wei, Shuai Fu, Weisen Jiang +5

Large Language Models (LLMs) are increasingly used for various tasks with graph structures. Though LLMs can process graph information in a textual format, they overlook the rich vi…