5 citations · 5 across the 5 of their papers we have counts for
5 papers
Tabular Foundation Models are Strong Graph Anomaly Detectors
Yunhui Liu, Tieke He, Yongchao Liu +3
Graph anomaly detection (GAD), which aims to identify abnormal nodes that deviate from the majority, has become increasingly important in high-stakes Web domains. However, existing…
EviNote-RAG: Enhancing RAG Models via Answer-Supportive Evidence Notes
Yuqin Dai, Guoqing Wang, Yuan Wang +13
Retrieval-Augmented Generation (RAG) has advanced open-domain question answering by incorporating external information into model reasoning. However, effectively leveraging externa…
Careful Queries, Credible Results: Teaching RAG Models Advanced Web Search Tools with Reinforcement Learning
Yuqin Dai, Shuo Yang, Guoqing Wang +10
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating up-to-date external knowledge, yet real-world web environments present unique challenges.…
AIGT: AI Generative Table Based on Prompt
Mingming Zhang, Zhiqing Xiao, Guoshan Lu +5
Tabular data, which accounts for over 80% of enterprise data assets, is vital in various fields. With growing concerns about privacy protection and data-sharing restrictions, gener…
XUAT-Copilot: Multi-Agent Collaborative System for Automated User Acceptance Testing with Large Language Model
Zhitao Wang, Wei Wang, Zirao Li +7
In past years, we have been dedicated to automating user acceptance testing (UAT) process of WeChat Pay, one of the most influential mobile payment applications in China. A system…