1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026
RAGShaper: Eliciting Sophisticated Agentic RAG Skills via Automated Data Synthesis
Zhengwei Tao, Bo Li, Jialong Wu +5
Agentic Retrieval-Augmented Generation (RAG) empowers large language models to autonomously plan and retrieve information for complex problem-solving. However, the development of r…
cs.CL2026
DocDancer: Towards Agentic Document-Grounded Information Seeking
Qintong Zhang, Xinjie Lv, Jialong Wu +8
Document Question Answering (DocQA) focuses on answering questions grounded in given documents, yet existing DocQA agents lack effective tool utilization and largely rely on closed…
cs.AI2025★ 1 cited
DataGovBench: Benchmarking LLM Agents for Real-World Data Governance Workflows
Zhou Liu, Zhaoyang Han, Guochen Yan +5
Data governance ensures data quality, security, and compliance through policies and standards, a critical foundation for scaling modern AI development. Recently, large language mod…