43 citations · 60 across the 6 of their papers we have counts for
6 papers
DB3 Team's Solution For Meta KDD Cup' 25
Yikuan Xia, Jiazun Chen, Yirui Zhan +6
This paper presents the db3 team's winning solution for the Meta CRAG-MM Challenge 2025 at KDD Cup'25. Addressing the challenge's unique multi-modal, multi-turn question answering…
ER-RAG: Enhance RAG with ER-Based Unified Modeling of Heterogeneous Data Sources
Yikuan Xia, Jiazun Chen, Yirui Zhan +6
Large language models (LLMs) excel in question-answering (QA) tasks, and retrieval-augmented generation (RAG) enhances their precision by incorporating external evidence from diver…
Winning Solution For Meta KDD Cup' 24
Yikuan Xia, Jiazun Chen, Jun Gao
This paper describes the winning solutions of all tasks in Meta KDD Cup 24 from db3 team. The challenge is to build a RAG system from web sources and knowledge graphs. We are given…
APrompt4EM: Augmented Prompt Tuning for Generalized Entity Matching
Yikuan Xia, Jiazun Chen, Xinchi Li +1
Generalized Entity Matching (GEM), which aims at judging whether two records represented in different formats refer to the same real-world entity, is an essential task in data mana…
Model Degradation Hinders Deep Graph Neural Networks
Wentao Zhang, Zeang Sheng, Ziqi Yin +5
Graph Neural Networks (GNNs) have achieved great success in various graph mining tasks.However, drastic performance degradation is always observed when a GNN is stacked with many l…
Evaluating Deep Graph Neural Networks
Wentao Zhang, Zeang Sheng, Yuezihan Jiang +4
Graph Neural Networks (GNNs) have already been widely applied in various graph mining tasks. However, they suffer from the shallow architecture issue, which is the key impediment t…