13 citations · 32 across the 20 of their papers we have counts for
6 papers · 1 filter
A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applications
Minhua Lin, Zongyu Wu, Zhichao Xu +6
The advent of large language models (LLMs) has transformed information access and reasoning through open-ended natural language interaction. However, LLMs remain limited by static…
DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules
Junjie Xu, Jiahao Zhang, Mangal Prakash +2
Geometric graph neural networks (GNNs) that respect E(3) symmetries have achieved strong performance on small molecule modeling, but they face scalability and expressiveness challe…
GPR: Empowering Generation with Graph-Pretrained Retriever
Xiaochen Wang, Zongyu Wu, Yuan Zhong +3
Graph retrieval-augmented generation (GRAG) places high demands on graph-specific retrievers. However, existing retrievers often rely on language models pretrained on plain text, l…
Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models
Zongyu Wu, Minhua Lin, Zhiwei Zhang +4
Large vision-language models (LVLMs) have demonstrated outstanding performance in many downstream tasks. However, LVLMs are trained on large-scale datasets, which can pose privacy…
How Far are LLMs from Real Search? A Comprehensive Study on Efficiency, Completeness, and Inherent Capabilities
Minhua Lin, Hui Liu, Xianfeng Tang +7
Search plays a fundamental role in problem-solving across various domains, with most real-world decision-making problems being solvable through systematic search. Drawing inspirati…
LanP: Rethinking the Impact of Language Priors in Large Vision-Language Models
Zongyu Wu, Yuwei Niu, Hongcheng Gao +12
Large Vision-Language Models (LVLMs) have shown impressive performance in various tasks. However, LVLMs suffer from hallucination, which hinders their adoption in the real world. E…