:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Guo, Ruiling, Yang, Xinwei, Huang, Chen, Zhang, Tong, Hu, Yong
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	https://arxiv.org/abs/2509.03957
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MedFact: Benchmarking the Fact-Checking Capabilities of Large Language Models on Chinese Medical Texts
by: He, Jiayi, et al.
Published: (2025)

InFi-Check: Interpretable and Fine-Grained Fact-Checking of LLMs
by: Bai, Yuzhuo, et al.
Published: (2026)

MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents
by: Tang, Liyan, et al.
Published: (2024)

How LLMs Fail to Support Fact-Checking
by: Proma, Adiba Mahbub, et al.
Published: (2025)

Explore the Potential of LLMs in Misinformation Detection: An Empirical Study
by: Chen, Mengyang, et al.
Published: (2023)

Can LLMs Automate Fact-Checking Article Writing?
by: Sahnan, Dhruv, et al.
Published: (2025)

RealFactBench: A Benchmark for Evaluating Large Language Models in Real-World Fact-Checking
by: Yang, Shuo, et al.
Published: (2025)

FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMs
by: Sawczyn, Albert, et al.
Published: (2025)

Assessing the Potential of Generative Agents in Crowdsourced Fact-Checking
by: Costabile, Luigia, et al.
Published: (2025)

FinVet: A Collaborative Framework of RAG and External Fact-Checking Agents for Financial Misinformation Detection
by: Araya, Daniel Berhane, et al.
Published: (2025)

oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning
by: Xu, Ruiling, et al.
Published: (2025)

CSCD-NS: a Chinese Spelling Check Dataset for Native Speakers
by: Hu, Yong, et al.
Published: (2022)

ClaimCheck: Real-Time Fact-Checking with Small Language Models
by: Putta, Akshith Reddy, et al.
Published: (2025)

Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMs
by: Singhal, Ronit, et al.
Published: (2024)

Uncovering the Fragility of Trustworthy LLMs through Chinese Textual Ambiguity
by: Wu, Xinwei, et al.
Published: (2025)

Flames: Benchmarking Value Alignment of LLMs in Chinese
by: Huang, Kexin, et al.
Published: (2023)

CORRECT: Context- and Reference-Augmented Reasoning and Prompting for Fact-Checking
by: Zhang, Delvin Ce, et al.
Published: (2025)

LEAF: Learning and Evaluation Augmented by Fact-Checking to Improve Factualness in Large Language Models
by: Tran, Hieu, et al.
Published: (2024)

Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMs
by: Sahitaj, Premtim, et al.
Published: (2025)

OpenFactCheck: A Unified Framework for Factuality Evaluation of LLMs
by: Iqbal, Hasan, et al.
Published: (2024)

FactCHD: Benchmarking Fact-Conflicting Hallucination Detection
by: Chen, Xiang, et al.
Published: (2023)

BiDeV: Bilateral Defusing Verification for Complex Claim Fact-Checking
by: Liu, Yuxuan, et al.
Published: (2025)

Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs
by: Vladika, Juraj, et al.
Published: (2025)

Evaluating Evidence Attribution in Generated Fact Checking Explanations
by: Xing, Rui, et al.
Published: (2024)

Uncertainty-Aware Web-Conditioned Scientific Fact-Checking
by: Vinod, Ashwin, et al.
Published: (2026)

MetaSumPerceiver: Multimodal Multi-Document Evidence Summarization for Fact-Checking
by: Chen, Ting-Chih, et al.
Published: (2024)

DISC: Plug-and-Play Decoding Intervention with Similarity of Characters for Chinese Spelling Check
by: Qiao, Ziheng, et al.
Published: (2024)

Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checking
by: Warren, Greta, et al.
Published: (2025)

COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanations
by: Xing, Rui, et al.
Published: (2025)

From Chaos to Clarity: Claim Normalization to Empower Fact-Checking
by: Sundriyal, Megha, et al.
Published: (2023)

Leveraging LLM Parametric Knowledge for Fact Checking without Retrieval
by: Vazhentsev, Artem, et al.
Published: (2026)

Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables
by: Gong, Haisong, et al.
Published: (2024)

Multimodal Claim Extraction for Fact-Checking
by: Teo, Joycelyn, et al.
Published: (2026)

Decomposition Dilemmas: Does Claim Decomposition Boost or Burden Fact-Checking Performance?
by: Hu, Qisheng, et al.
Published: (2024)

Use of Retrieval-Augmented Large Language Model Agent for Long-Form COVID-19 Fact-Checking
by: Huang, Jingyi, et al.
Published: (2025)

Combining Evidence and Reasoning for Biomedical Fact-Checking
by: Barone, Mariano, et al.
Published: (2025)

Misinforming LLMs: vulnerabilities, challenges and opportunities
by: Zhou, Bo, et al.
Published: (2024)

Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts
by: Mujahid, Zain Muhammad, et al.
Published: (2025)

CFEVER: A Chinese Fact Extraction and VERification Dataset
by: Lin, Ying-Jia, et al.
Published: (2024)

Adversarial Attacks Against Automated Fact-Checking: A Survey
by: Liu, Fanzhen, et al.
Published: (2025)