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20232026
most citedKnowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

31 citations · 54 across the 11 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.CL2024★ 1 cited

MINTQA: A Multi-Hop Question Answering Benchmark for Evaluating LLMs on New and Tail Knowledge

Jie He, Nan Hu, Wanqiu Long +2

Large language models (LLMs) have demonstrated impressive capabilities in various reasoning tasks but face significant challenges with complex, knowledge-intensive multi-hop querie…

cs.CL2024

Atomic Fact Decomposition Helps Attributed Question Answering

Zhichao Yan, Jiapu Wang, Jiaoyan Chen +3

Attributed Question Answering (AQA) aims to provide both a trustworthy answer and a reliable attribution report for a given question. Retrieval is a widely adopted approach, includ…

cs.CL2024

CoTKR: Chain-of-Thought Enhanced Knowledge Rewriting for Complex Knowledge Graph Question Answering

Yike Wu, Yi Huang, Nan Hu +4

Recent studies have explored the use of Large Language Models (LLMs) with Retrieval Augmented Generation (RAG) for Knowledge Graph Question Answering (KGQA). They typically require…

cs.AI2024★ 4 cited

Start from Zero: Triple Set Prediction for Automatic Knowledge Graph Completion

Wen Zhang, Yajing Xu, Peng Ye +5

Knowledge graph (KG) completion aims to find out missing triples in a KG. Some tasks, such as link prediction and instance completion, have been proposed for KG completion. They ar…

cs.CL2024★ 1 cited

Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs

Junjie Wang, Mingyang Chen, Binbin Hu +10

Improving the performance of large language models (LLMs) in complex question-answering (QA) scenarios has always been a research focal point. Recent studies have attempted to enha…

cs.CL2024

TacoERE: Cluster-aware Compression for Event Relation Extraction

Yong Guan, Xiaozhi Wang, Lei Hou +4

Event relation extraction (ERE) is a critical and fundamental challenge for natural language processing. Existing work mainly focuses on directly modeling the entire document, whic…

cs.AI2024★ 31 cited

Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

Zhuo Chen, Yichi Zhang, Yin Fang +12

Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the semantic web community's exploration into multi-modal dimensions unlocking new avenues for…

cs.CL2024★ 1 cited

Can LLMs Evaluate Complex Attribution in QA? Automatic Benchmarking using Knowledge Graphs

Nan Hu, Jiaoyan Chen, Yike Wu +6

Attributed Question Answering (AQA) has attracted wide attention, but there are still several limitations in evaluating the attributions, including lacking fine-grained attribution…