16 citations · 17 across the 6 of their papers we have counts for
10 papers
Seeing Before Agreeing: Aligning Multi-Agent Consensus with Visual Evidence
Yuhan Wang, Shuochen Chang, Yalin Feng +8
Vision-language models (VLMs) have achieved strong performance on visual question answering (VQA). To mitigate individual hallucinations and blind spots, aggregating diverse perspe…
Dissecting Role Cognition in Medical LLMs via Neuronal Ablation
Xun Liang, Huayi Lai, Hanyu Wang +5
Large language models (LLMs) have gained significant traction in medical decision support systems, particularly in the context of medical question answering and role-playing simula…
Text2VectorSQL: Towards a Unified Interface for Vector Search and SQL Queries
Zhengren Wang, Dongwen Yao, Bozhou Li +7
The proliferation of unstructured data poses a fundamental challenge to traditional database interfaces. While Text-to-SQL has democratized access to structured data, it remains in…
CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation
Sizhe Wang, Zhengren Wang, Dongsheng Ma +5
Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components with iterative reuse of existing code…
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations
Ding Chen, Qingchen Yu, Pengyuan Wang +9
With the release of OpenAI's o1 model, reasoning models that adopt slow-thinking strategies have become increasingly common. Their outputs often contain complex reasoning, intermed…
MaintainCoder: Maintainable Code Generation Under Dynamic Requirements
Zhengren Wang, Rui Ling, Chufan Wang +5
Modern code generation has made significant strides in functional correctness and execution efficiency. However, these systems often overlook a critical dimension in real-world sof…
RARE: Retrieval-Augmented Reasoning Modeling
Zhengren Wang, Jiayang Yu, Dongsheng Ma +8
Domain-specific intelligence demands specialized knowledge and sophisticated reasoning for problem-solving, posing significant challenges for large language models (LLMs) that stru…
HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation
Hao Liu, Zhengren Wang, Xi Chen +4
Retrieval-Augmented Generation (RAG) systems often struggle with imperfect retrieval, as traditional retrievers focus on lexical or semantic similarity rather than logical relevanc…
A Comprehensive Survey on Imbalanced Data Learning
Xinyi Gao, Dongting Xie, Yihang Zhang +5
With the expansion of data availability, machine learning (ML) has achieved remarkable breakthroughs in both academia and industry. However, imbalanced data distributions are preva…
MRAMG-Bench: A Comprehensive Benchmark for Advancing Multimodal Retrieval-Augmented Multimodal Generation
Qinhan Yu, Zhiyou Xiao, Binghui Li +3
Recent advances in Retrieval-Augmented Generation (RAG) have significantly improved response accuracy and relevance by incorporating external knowledge into Large Language Models (…