10 papers
DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent
Tongzhou Wu, Yuhao Wang, Xinyu Ma +4
Deep-research agents are capable of executing multi-step web exploration, targeted retrieval, and sophisticated question answering. Despite their powerful capabilities, deep-resear…
Reinforced Informativeness Optimization for Long-Form Retrieval-Augmented Generation
Yuhao Wang, Ruiyang Ren, Yucheng Wang +4
Long-form question answering (LFQA) requires open-ended long-form responses that synthesize coherent, factually grounded content from multi-source evidence. This makes reinforcemen…
ArbGraph: Conflict-Aware Evidence Arbitration for Reliable Long-Form Retrieval-Augmented Generation
Qingying Niu, Yuhao Wang, Ruiyang Ren +2
Retrieval-augmented generation (RAG) remains unreliable in long-form settings, where retrieved evidence is noisy or contradictory, making it difficult for RAG pipelines to maintain…
Emulating Clinician Cognition via Self-Evolving Deep Clinical Research
Ruiyang Ren, Yuhao Wang, Yunsen Liang +8
Clinical diagnosis is a complex cognitive process, grounded in dynamic cue acquisition and continuous expertise accumulation. Yet most current artificial intelligence (AI) systems…
QCAgent: An agentic framework for quality-controllable pathology report generation from whole slide image
Rundong Wang, Wei Ba, Ying Zhou +8
Recent methods for pathology report generation from whole-slide image (WSI) are capable of producing slide-level diagnostic descriptions but fail to ground fine-grained statements…
BEE-RAG: Balanced Entropy Engineering for Retrieval-Augmented Generation
Yuhao Wang, Ruiyang Ren, Yucheng Wang +4
With the rapid advancement of large language models (LLMs), retrieval-augmented generation (RAG) has emerged as a critical approach to supplement the inherent knowledge limitations…