83 citations · 105 across the 11 of their papers we have counts for
15 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…
CiteVQA: Benchmarking Evidence Attribution for Trustworthy Document Intelligence
Dongsheng Ma, Jiayu Li, Zhengren Wang +10
Multimodal Large Language Models (MLLMs) have significantly advanced document understanding, yet current Doc-VQA evaluations score only the final answer and leave the supporting ev…
AgenticOCR: Parsing Only What You Need for Efficient Retrieval-Augmented Generation
Zhengren Wang, Dongsheng Ma, Huaping Zhong +4
The expansion of retrieval-augmented generation (RAG) into multimodal domains has intensified the challenge for processing complex visual documents, such as financial reports. Whil…
SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents
Danlong Yuan, Wei Wu, Enhan Zhao +4
Reinforcement learning (RL) has become a key paradigm for training software engineering (SWE) agents, but existing pipelines typically rely on per-task containers for isolation. At…
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…
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 (…
Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction
Qintong Zhang, Bin Wang, Victor Shea-Jay Huang +5
Document parsing (DP) transforms unstructured or semi-structured documents into structured, machine-readable representations, enabling downstream applications such as knowledge bas…
QAEncoder: Towards Aligned Representation Learning in Question Answering Systems
Zhengren Wang, Qinhan Yu, Shida Wei +6
Modern QA systems entail retrieval-augmented generation (RAG) for accurate and trustworthy responses. However, the inherent gap between user queries and relevant documents hinders…
KeyVideoLLM: Towards Large-scale Video Keyframe Selection
Hao Liang, Jiapeng Li, Tianyi Bai +7
Recently, with the rise of web videos, managing and understanding large-scale video datasets has become increasingly important. Video Large Language Models (VideoLLMs) have emerged…
Retrieval-Augmented Generation for AI-Generated Content: A Survey
Penghao Zhao, Hailin Zhang, Qinhan Yu +7
Advancements in model algorithms, the growth of foundational models, and access to high-quality datasets have propelled the evolution of Artificial Intelligence Generated Content (…