71 citations · 76 across the 5 of their papers we have counts for
5 papers
A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential
Wei Tang, Yixin Cao, Jiahao Ying +4
Retrieval-Augmented Generation (RAG) is an effective solution to supplement necessary knowledge to large language models (LLMs). Targeting its bottleneck of retriever performance,…
Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models
Jiahao Ying, Yixin Cao, Yushi Bai +7
Large language models (LLMs) have achieved impressive performance across various natural language benchmarks, prompting a continual need to curate more difficult datasets for large…
FedMKGC: Privacy-Preserving Federated Multilingual Knowledge Graph Completion
Wei Tang, Zhiqian Wu, Yixin Cao +2
Knowledge graph completion (KGC) aims to predict missing facts in knowledge graphs (KGs), which is crucial as modern KGs remain largely incomplete. While training KGC models on mul…
UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction
Wei Tang, Benfeng Xu, Yuyue Zhao +4
Relational triple extraction is challenging for its difficulty in capturing rich correlations between entities and relations. Existing works suffer from 1) heterogeneous representa…
Time-aware Path Reasoning on Knowledge Graph for Recommendation
Yuyue Zhao, Xiang Wang, Jiawei Chen +4
Reasoning on knowledge graph (KG) has been studied for explainable recommendation due to it's ability of providing explicit explanations. However, current KG-based explainable reco…