Towards Comprehensive Stage-wise Benchmarking of Large Language Models in Fact-Checking
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Hongzhan, Chen, Zixin, Shen, Zhiqi, Luo, Ziyang, Ye, Zhen, Ma, Jing, Chua, Tat-Seng, Xu, Guandong |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models
by: Wang, Shengkang, et al.
Published: (2024)
by: Wang, Shengkang, et al.
Published: (2024)
FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Models
by: Lin, Hongzhan, et al.
Published: (2025)
by: Lin, Hongzhan, et al.
Published: (2025)
ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use
by: Li, Kaixin, et al.
Published: (2025)
by: Li, Kaixin, et al.
Published: (2025)
AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness
by: Chen, Zixin, et al.
Published: (2025)
by: Chen, Zixin, et al.
Published: (2025)
MemeArena: Automating Context-Aware Unbiased Evaluation of Harmfulness Understanding for Multimodal Large Language Models
by: Chen, Zixin, et al.
Published: (2025)
by: Chen, Zixin, et al.
Published: (2025)
ScratchEval: Are GPT-4o Smarter than My Child? Evaluating Large Multimodal Models with Visual Programming Challenges
by: Fu, Rao, et al.
Published: (2024)
by: Fu, Rao, et al.
Published: (2024)
CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models
by: Lin, Hongzhan, et al.
Published: (2024)
by: Lin, Hongzhan, et al.
Published: (2024)
REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control
by: Kong, Chuyi, et al.
Published: (2025)
by: Kong, Chuyi, et al.
Published: (2025)
Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models
by: Lin, Hongzhan, et al.
Published: (2024)
by: Lin, Hongzhan, et al.
Published: (2024)
AMR-Evol: Adaptive Modular Response Evolution Elicits Better Knowledge Distillation for Large Language Models in Code Generation
by: Luo, Ziyang, et al.
Published: (2024)
by: Luo, Ziyang, et al.
Published: (2024)
Analyzing Temporal Complex Events with Large Language Models? A Benchmark towards Temporal, Long Context Understanding
by: Zhang, Zhihan, et al.
Published: (2024)
by: Zhang, Zhihan, et al.
Published: (2024)
SCTc-TE: A Comprehensive Formulation and Benchmark for Temporal Event Forecasting
by: Ma, Yunshan, et al.
Published: (2023)
by: Ma, Yunshan, et al.
Published: (2023)
A Comprehensive Evaluation of Large Language Models on Temporal Event Forecasting
by: Chang, He, et al.
Published: (2024)
by: Chang, He, et al.
Published: (2024)
GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse
by: Lin, Hongzhan, et al.
Published: (2024)
by: Lin, Hongzhan, et al.
Published: (2024)
ClarityEthic: Explainable Moral Judgment Utilizing Contrastive Ethical Insights from Large Language Models
by: Sun, Yuxi, et al.
Published: (2024)
by: Sun, Yuxi, et al.
Published: (2024)
Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks
by: Xu, Shicheng, et al.
Published: (2023)
by: Xu, Shicheng, et al.
Published: (2023)
Towards Natural Language-Guided Drones: GeoText-1652 Benchmark with Spatial Relation Matching
by: Chu, Meng, et al.
Published: (2023)
by: Chu, Meng, et al.
Published: (2023)
Towards Low-Resource Harmful Meme Detection with LMM Agents
by: Huang, Jianzhao, et al.
Published: (2024)
by: Huang, Jianzhao, et al.
Published: (2024)
CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?
by: Zhao, Yuwei, et al.
Published: (2024)
by: Zhao, Yuwei, et al.
Published: (2024)
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
by: He, Yingzhi, et al.
Published: (2025)
by: He, Yingzhi, et al.
Published: (2025)
Exploring the Impact of Personality Traits on Conversational Recommender Systems: A Simulation with Large Language Models
by: Zhao, Xiaoyan, et al.
Published: (2025)
by: Zhao, Xiaoyan, et al.
Published: (2025)
RealFactBench: A Benchmark for Evaluating Large Language Models in Real-World Fact-Checking
by: Yang, Shuo, et al.
Published: (2025)
by: Yang, Shuo, et al.
Published: (2025)
Towards Modality Generalization: A Benchmark and Prospective Analysis
by: Liu, Xiaohao, et al.
Published: (2024)
by: Liu, Xiaohao, et al.
Published: (2024)
DiffCoT: Diffusion-styled Chain-of-Thought Reasoning in LLMs
by: Cao, Shidong, et al.
Published: (2026)
by: Cao, Shidong, et al.
Published: (2026)
Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection
by: Li, Moxin, et al.
Published: (2024)
by: Li, Moxin, et al.
Published: (2024)
Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models
by: Koa, Kelvin J. L., et al.
Published: (2024)
by: Koa, Kelvin J. L., et al.
Published: (2024)
Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery
by: Yang, Chaoqun, et al.
Published: (2026)
by: Yang, Chaoqun, et al.
Published: (2026)
MMDocBench: Benchmarking Large Vision-Language Models for Fine-Grained Visual Document Understanding
by: Zhu, Fengbin, et al.
Published: (2024)
by: Zhu, Fengbin, et al.
Published: (2024)
MedFact: Benchmarking the Fact-Checking Capabilities of Large Language Models on Chinese Medical Texts
by: He, Jiayi, et al.
Published: (2025)
by: He, Jiayi, et al.
Published: (2025)
Compose Your Aesthetics: Empowering Text-to-Image Models with the Principles of Art
by: Jin, Zhe, et al.
Published: (2025)
by: Jin, Zhe, et al.
Published: (2025)
Towards Comprehensive Post Safety Alignment of Large Language Models via Safety Patching
by: Zhao, Weixiang, et al.
Published: (2024)
by: Zhao, Weixiang, et al.
Published: (2024)
MM-CRITIC: A Holistic Evaluation of Large Multimodal Models as Multimodal Critique
by: Zeng, Gailun, et al.
Published: (2025)
by: Zeng, Gailun, et al.
Published: (2025)
TrendFact: A Benchmark for Explainable Hotspot Perception in Fact-Checking with Natural Language Explanation
by: Zhang, Xiaocheng, et al.
Published: (2024)
by: Zhang, Xiaocheng, et al.
Published: (2024)
Towards Goal-oriented Intelligent Tutoring Systems in Online Education
by: Deng, Yang, et al.
Published: (2023)
by: Deng, Yang, et al.
Published: (2023)
A Study of Implicit Ranking Unfairness in Large Language Models
by: Xu, Chen, et al.
Published: (2023)
by: Xu, Chen, et al.
Published: (2023)
Aligning Large Language Models for Faithful Integrity Against Opposing Argument
by: Zhao, Yong, et al.
Published: (2025)
by: Zhao, Yong, et al.
Published: (2025)
EHRStruct: A Comprehensive Benchmark Framework for Evaluating Large Language Models on Structured Electronic Health Record Tasks
by: Yang, Xiao, et al.
Published: (2025)
by: Yang, Xiao, et al.
Published: (2025)
TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data
by: Zhu, Fengbin, et al.
Published: (2024)
by: Zhu, Fengbin, et al.
Published: (2024)
Large Language Model Empowered Recommendation Meets All-domain Continual Pre-Training
by: Ma, Haokai, et al.
Published: (2025)
by: Ma, Haokai, et al.
Published: (2025)
Generative Recommendation: Towards Next-generation Recommender Paradigm
by: Wang, Wenjie, et al.
Published: (2023)
by: Wang, Wenjie, et al.
Published: (2023)
Similar Items
-
MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models
by: Wang, Shengkang, et al.
Published: (2024) -
FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Models
by: Lin, Hongzhan, et al.
Published: (2025) -
ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use
by: Li, Kaixin, et al.
Published: (2025) -
AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness
by: Chen, Zixin, et al.
Published: (2025) -
MemeArena: Automating Context-Aware Unbiased Evaluation of Harmfulness Understanding for Multimodal Large Language Models
by: Chen, Zixin, et al.
Published: (2025)