Imagen de Portada

Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Han, Chen, Zheng, Wenzhen, Tang, Xijin
Formato:	Preprint
Publicado:	2025
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Beyond Detection: Exploring Evidence-based Multi-Agent Debate for Misinformation Intervention and Persuasion
por: Han, Chen, et al.
Publicado: (2025)

TurQUaz at CheckThat! 2025: Debating Large Language Models for Scientific Web Discourse Detection
por: Saraç, Tarık, et al.
Publicado: (2025)

Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models
por: Lin, Hongzhan, et al.
Publicado: (2024)

Misinformation Detection using Large Language Models with Explainability
por: Patel, Jainee, et al.
Publicado: (2025)

Assisted Debate Builder with Large Language Models
por: Faugier, Elliot, et al.
Publicado: (2024)

Large Language Models and the Rationalist Empiricist Debate
por: King, David
Publicado: (2024)

An Empirical Analysis on Large Language Models in Debate Evaluation
por: Liu, Xinyi, et al.
Publicado: (2024)

Ensemble Debates with Local Large Language Models for AI Alignment
por: Sarabamoun, Ephraiem
Publicado: (2025)

Limits of Large Language Models in Debating Humans
por: Flamino, James, et al.
Publicado: (2024)

Exploring Health Misinformation Detection with Multi-Agent Debate
por: Chen, Chih-Han, et al.
Publicado: (2025)

Evaluating the Performance of Large Language Models via Debates
por: Moniri, Behrad, et al.
Publicado: (2024)

How does Misinformation Affect Large Language Model Behaviors and Preferences?
por: Peng, Miao, et al.
Publicado: (2025)

Tree-of-Debate: Multi-Persona Debate Trees Elicit Critical Thinking for Scientific Comparative Analysis
por: Kargupta, Priyanka, et al.
Publicado: (2025)

Fact4ac at the Financial Misinformation Detection Challenge Task: Reference-Free Financial Misinformation Detection via Fine-Tuning and Few-Shot Prompting of Large Language Models
por: Hoang, Cuong, et al.
Publicado: (2026)

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

Can Large Language Models Detect Misinformation in Scientific News Reporting?
por: Cao, Yupeng, et al.
Publicado: (2024)

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

MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language Models
por: Huo, Jiahao, et al.
Publicado: (2025)

Debate on Graph: a Flexible and Reliable Reasoning Framework for Large Language Models
por: Ma, Jie, et al.
Publicado: (2024)

R-Debater: Retrieval-Augmented Debate Generation through Argumentative Memory
por: Li, Maoyuan, et al.
Publicado: (2025)

OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models
por: Zheng, Hao, et al.
Publicado: (2025)

Uncertainty Resolution in Misinformation Detection
por: Orlovskiy, Yury, et al.
Publicado: (2024)

When in Doubt, Consult: Expert Debate for Sexism Detection via Confidence-Based Routing
por: Alajmi, Anwar, et al.
Publicado: (2025)

GroupDebate: Enhancing the Efficiency of Multi-Agent Debate Using Group Discussion
por: Liu, Tongxuan, et al.
Publicado: (2024)

Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate
por: Chern, Steffi, et al.
Publicado: (2024)

Explanation, Debate, Align: A Weak-to-Strong Framework for Language Model Generalization
por: Zakershahrak, Mehrdad, et al.
Publicado: (2024)

Evaluating Large Language Models in Crisis Detection: A Real-World Benchmark from Psychological Support Hotlines
por: Deng, Guifeng, et al.
Publicado: (2025)

Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection
por: Wahle, Jan Philip, et al.
Publicado: (2021)

Removal of Hallucination on Hallucination: Debate-Augmented RAG
por: Hu, Wentao, et al.
Publicado: (2025)

Depression Detection on Social Media with Large Language Models
por: Lan, Xiaochong, et al.
Publicado: (2024)

PD$^3$: A Project Duplication Detection Framework via Adapted Multi-Agent Debate
por: Bao, Dezheng, et al.
Publicado: (2025)

SNIFFER: Multimodal Large Language Model for Explainable Out-of-Context Misinformation Detection
por: Qi, Peng, et al.
Publicado: (2024)

Social Reasoning in Machines: Investigating Collective Truth-Seeking Dynamics in Large Language Model Debate
por: Pecher, Tom
Publicado: (2026)

Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
por: Wang, Haotian, et al.
Publicado: (2023)

Clickbait Detection via Large Language Models
por: Wang, Han, et al.
Publicado: (2023)

Debate Helps Weak-to-Strong Generalization
por: Lang, Hao, et al.
Publicado: (2025)

Systematic Biases in LLM Simulations of Debates
por: Taubenfeld, Amir, et al.
Publicado: (2024)

Can Large Language Models Understand Real-World Complex Instructions?
por: He, Qianyu, et al.
Publicado: (2023)

MultiAgent Collaboration Attack: Investigating Adversarial Attacks in Large Language Model Collaborations via Debate
por: Amayuelas, Alfonso, et al.
Publicado: (2024)

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