:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang, Haoran, Khalid, Maryam, Wu, Qiong, Gao, Jian, Cao, Cheng
Formato:	Preprint
Publicado:	2026
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	https://arxiv.org/abs/2601.02574
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

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

Multimodal Large Language Models to Support Real-World Fact-Checking
por: Geng, Jiahui, et al.
Publicado: (2024)

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

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

Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification
por: Fadeeva, Ekaterina, et al.
Publicado: (2024)

TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checking
por: Hang, Ching Nam, et al.
Publicado: (2025)

BiCon-Gate: Consistency-Gated De-colloquialisation for Dialogue Fact-Checking
por: Park, Hyunkyung, et al.
Publicado: (2026)

Consistency Checks for Language Model Forecasters
por: Paleka, Daniel, et al.
Publicado: (2024)

Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
por: Rahman, Subhey Sadi, et al.
Publicado: (2025)

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

Scalable Best-of-N Selection for Large Language Models via Self-Certainty
por: Kang, Zhewei, et al.
Publicado: (2025)

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

Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling
por: Yang, Linyao, et al.
Publicado: (2023)

FactReasoner: A Probabilistic Approach to Long-Form Factuality Assessment for Large Language Models
por: Marinescu, Radu, et al.
Publicado: (2025)

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

Application and Optimization of Large Models Based on Prompt Tuning for Fact-Check-Worthiness Estimation
por: Yu, Yinglong, et al.
Publicado: (2025)

Surprising Efficacy of Fine-Tuned Transformers for Fact-Checking over Larger Language Models
por: Setty, Vinay
Publicado: (2024)

RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild
por: Xu, Danni, et al.
Publicado: (2025)

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

Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression
por: Huang, Jiameng, et al.
Publicado: (2025)

Certainty-Guided Reasoning in Large Language Models: A Dynamic Thinking Budget Approach
por: Nogueira, João Paulo, et al.
Publicado: (2025)

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

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

Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance
por: Xiong, Kai, et al.
Publicado: (2024)

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

Atomic Fact-Checking Increases Clinician Trust in Large Language Model Recommendations for Oncology Decision Support: A Randomized Controlled Trial
por: Adams, Lisa C., et al.
Publicado: (2026)

Consistency Is the Key: Detecting Hallucinations in LLM Generated Text By Checking Inconsistencies About Key Facts
por: Gupta, Raavi, et al.
Publicado: (2025)

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

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

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

ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking
por: Wu, Yutao, et al.
Publicado: (2025)

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

Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate
por: Xiong, Kai, et al.
Publicado: (2023)

Probabilistic Token Alignment for Large Language Model Fusion
por: Zeng, Runjia, et al.
Publicado: (2025)

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

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

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

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

Veracity: An Open-Source AI Fact-Checking System
por: Curtis, Taylor Lynn, et al.
Publicado: (2025)