4 citations · 8 across the 11 of their papers we have counts for
6 papers · 1 filter
Transformers for Complex Query Answering over Knowledge Hypergraphs
Hong Ting Tsang, Zihao Wang, Yangqiu Song
Complex Query Answering (CQA) has been extensively studied in recent years. In order to model data that is closer to real-world distribution, knowledge graphs with different modali…
Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question Answering
Yao Xu, Shizhu He, Jiabei Chen +6
To address the issues of insufficient knowledge and hallucination in Large Language Models (LLMs), numerous studies have explored integrating LLMs with Knowledge Graphs (KGs). Howe…
Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?
Qineng Wang, Zihao Wang, Ying Su +2
Recent progress in LLMs discussion suggests that multi-agent discussion improves the reasoning abilities of LLMs. In this work, we reevaluate this claim through systematic experime…
EntailE: Introducing Textual Entailment in Commonsense Knowledge Graph Completion
Ying Su, Tianqing Fang, Huiru Xiao +4
Commonsense knowledge graph completion is a new challenge for commonsense knowledge graph construction and application. In contrast to factual knowledge graphs such as Freebase and…
PipeNet: Question Answering with Semantic Pruning over Knowledge Graphs
Ying Su, Jipeng Zhang, Yangqiu Song +1
It is well acknowledged that incorporating explicit knowledge graphs (KGs) can benefit question answering. Existing approaches typically follow a grounding-reasoning pipeline in wh…
On the Discussion of Large Language Models: Symmetry of Agents and Interplay with Prompts
Qineng Wang, Zihao Wang, Ying Su +1
Two ways has been discussed to unlock the reasoning capability of a large language model. The first one is prompt engineering and the second one is to combine the multiple inferenc…