2 citations · 3 across the 8 of their papers we have counts for
9 papers
A Heuristic Perspective on Debiasing Language Models
Tian Lan, Yemin Wang, Chuancheng Shi +6
Language models (LMs) often acquire various biases during pre-training and may express them in interactions, potentially causing social harm. Existing methods often rely on counter…
S-Path-RAG: Semantic-Aware Shortest-Path Retrieval Augmented Generation for Multi-Hop Knowledge Graph Question Answering
Rong Fu, Yemin Wang, Tianxiang Xu +5
We present S-Path-RAG, a semantic-aware shortest-path Retrieval-Augmented Generation framework designed to improve multi-hop question answering over large knowledge graphs. S-Path-…
FinToolBench: Evaluating LLM Agents for Real-World Financial Tool Use
Jiaxuan Lu, Kong Wang, Yemin Wang +9
The integration of Large Language Models (LLMs) into the financial domain is driving a paradigm shift from passive information retrieval to dynamic, agentic interaction. While gene…
RoboRouter: Training-Free Policy Routing for Robotic Manipulation
Yiteng Chen, Zhe Cao, Hongjia Ren +9
Research on robotic manipulation has developed a diverse set of policy paradigms, including vision-language-action (VLA) models, vision-action (VA) policies, and code-based composi…
Fat-Cat: Document-Driven Metacognitive Multi-Agent System for Complex Reasoning
Tong Yang, Yemin Wang, Chaoning Zhang +1
The effectiveness of LLM-based agents is often limited not by model capacity alone, but by how efficiently contextual information is utilized at runtime. Existing agent frameworks…
Spiking Neural-Invariant Kalman Fusion for Accurate Localization Using Low-Cost IMUs
Yaohua Liu, Qiao Xu, Binkai Ou
Low-cost inertial measurement units (IMUs) are widely utilized in mobile robot localization due to their affordability and ease of integration. However, their complex, nonlinear, a…
Beyond Static Tools: Test-Time Tool Evolution for Scientific Reasoning
Jiaxuan Lu, Ziyu Kong, Yemin Wang +10
The central challenge of AI for Science is not reasoning alone, but the ability to create computational methods in an open-ended scientific world. Existing LLM-based agents rely on…
How to make Medical AI Systems safer? Simulating Vulnerabilities, and Threats in Multimodal Medical RAG System
Kaiwen Zuo, Zelin Liu, Raman Dutt +4
Large Vision-Language Models (LVLMs) augmented with Retrieval-Augmented Generation (RAG) are increasingly employed in medical AI to enhance factual grounding through external clini…
3D CoCa: Contrastive Learners are 3D Captioners
Ting Huang, Zeyu Zhang, Yemin Wang +1
3D captioning, which aims to describe the content of 3D scenes in natural language, remains highly challenging due to the inherent sparsity of point clouds and weak cross-modal ali…