7 papers
Agentic Retrieval-Augmented Generation for Financial Document Question Answering
Yang Shu, Yingmin Liu, Zequn Xie
Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual narratives, and footnotes--scatter…
SlimSearcher: Training Efficiency-Aware Web Agents via Adaptive Reward Gating
Zequn Xie, Junjie Wang, Dan Yang +4
Deep research agents have demonstrated remarkable capabilities in complex information-seeking tasks, yet this power comes at a steep computational cost. Driven by accuracy-focused…
WebClipper: Efficient Evolution of Web Agents with Graph-based Trajectory Pruning
Junjie Wang, Zequn Xie, Dan Yang +9
Deep Research systems based on web agents have shown strong potential in solving complex information-seeking tasks, yet their search efficiency remains underexplored. We observe th…
Mitigating Hallucination on Hallucination in RAG via Ensemble Voting
Zequn Xie, Zhengyang Sun
Retrieval-Augmented Generation (RAG) aims to reduce hallucinations in Large Language Models (LLMs) by integrating external knowledge. However, RAG introduces a critical challenge:…
PeopleSearchBench: A Multi-Dimensional Benchmark for Evaluating AI-Powered People Search Platforms
Wei Wang, Tianyu Shi, Shuai Zhang +9
AI-powered people search platforms are increasingly used in recruiting, sales prospecting, and professional networking, yet no widely accepted benchmark exists for evaluating their…
Dynamic Uncertainty Learning with Noisy Correspondence for Text-Based Person Search
Zequn Xie, Haoming Ji, Chengxuan Li +1
Text-to-image person search aims to identify an individual based on a text description. To reduce data collection costs, large-scale text-image datasets are created from co-occurre…