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20212026
most citedSurvey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity

55 citations · 117 across the 26 of their papers we have counts for

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5 papers · 1 filter

cs.AI2025

NewtonBench: Benchmarking Generalizable Scientific Law Discovery in LLM Agents

Tianshi Zheng, Kelvin Kiu-Wai Tam, Newt Hue-Nam K. Nguyen +10

Large language models are emerging as powerful tools for scientific law discovery, a foundational challenge in AI-driven science. However, existing benchmarks for this task suffer…

cs.CL2025

InteGround: On the Evaluation of Verification and Retrieval Planning in Integrative Grounding

Cheng Jiayang, Qianqian Zhuang, Haoran Li +4

Grounding large language models (LLMs) in external knowledge sources is a promising method for faithful prediction. While existing grounding approaches work well for simple queries…

cs.CL2025

XToM: Exploring the Multilingual Theory of Mind for Large Language Models

Chunkit Chan, Yauwai Yim, Hongchuan Zeng +14

Theory of Mind (ToM), the ability to infer mental states in others, is pivotal for human social cognition. Existing evaluations of ToM in LLMs are largely limited to English, negle…

cs.CL2025

LogiDynamics: Unraveling the Dynamics of Inductive, Abductive and Deductive Logical Inferences in LLM Reasoning

Tianshi Zheng, Jiayang Cheng, Chunyang Li +6

Modern large language models (LLMs) employ diverse logical inference mechanisms for reasoning, making the strategic optimization of these approaches critical for advancing their ca…

cs.AI2025

Top Ten Challenges Towards Agentic Neural Graph Databases

Jiaxin Bai, Zihao Wang, Yukun Zhou +16

Graph databases (GDBs) like Neo4j and TigerGraph excel at handling interconnected data but lack advanced inference capabilities. Neural Graph Databases (NGDBs) address this by inte…