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20232026
most citedSequential Query Encoding For Complex Query Answering on Knowledge Graphs

5 citations · 11 across the 39 of their papers we have counts for

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Showing 2024 · cs.CLShow all

5 papers · 2 filters

cs.CL2024

ComparisonQA: Evaluating Factuality Robustness of LLMs Through Knowledge Frequency Control and Uncertainty

Qing Zong, Zhaowei Wang, Tianshi Zheng +2

The rapid development of LLMs has sparked extensive research into their factual knowledge. Current works find that LLMs fall short on questions around low-frequency entities. Howev…

cs.CL2024

KnowShiftQA: How Robust are RAG Systems when Textbook Knowledge Shifts in K-12 Education?

Tianshi Zheng, Weihan Li, Jiaxin Bai +2

Retrieval-Augmented Generation (RAG) systems show remarkable potential as question answering tools in the K-12 Education domain, where knowledge is typically queried within the res…

cs.CL2024★ 1 cited

Evaluating and Enhancing LLMs Agent based on Theory of Mind in Guandan: A Multi-Player Cooperative Game under Imperfect Information

Yauwai Yim, Chunkit Chan, Tianyu Shi +4

Large language models (LLMs) have shown success in handling simple games with imperfect information and enabling multi-agent coordination, but their ability to facilitate practical…

cs.CL2024★ 1 cited

CLR-Fact: Evaluating the Complex Logical Reasoning Capability of Large Language Models over Factual Knowledge

Tianshi Zheng, Jiaxin Bai, Yicheng Wang +4

While large language models (LLMs) have demonstrated impressive capabilities across various natural language processing tasks by acquiring rich factual knowledge from their broad t…

cs.CL2024

Text-Tuple-Table: Towards Information Integration in Text-to-Table Generation via Global Tuple Extraction

Zheye Deng, Chunkit Chan, Weiqi Wang +5

The task of condensing large chunks of textual information into concise and structured tables has gained attention recently due to the emergence of Large Language Models (LLMs) and…