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Showing 651–675 of 1282 papers

TitleStatusHype
Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource LimitationsCode0
Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generation—0
Can Large Language Models Detect Misinformation in Scientific News Reporting?—0
Compression Robust Synthetic Speech Detection Using Patched Spectrogram Transformer—0
MM-Soc: Benchmarking Multimodal Large Language Models in Social Media PlatformsCode0
Factual Consistency Evaluation of Summarisation in the Era of Large Language Models—0
Whispers in Grammars: Injecting Covert Backdoors to Compromise Dense Retrieval SystemsCode0
Detecting misinformation through Framing Theory: the Frame Element-based Model—0
AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM AnnotatorsCode0
Humans or LLMs as the Judge? A Study on Judgement BiasesCode0
Camouflage is all you need: Evaluating and Enhancing Language Model Robustness Against Camouflage Adversarial Attacks—0
Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse—0
Exploring Saliency Bias in Manipulation DetectionCode0
Explaining Veracity Predictions with Evidence Summarization: A Multi-Task Model ApproachCode0
Deepfake Detection and the Impact of Limited Computing CapabilitiesCode0
FACT-GPT: Fact-Checking Augmentation via Claim Matching with LLMs—0
In-Context Learning Can Re-learn Forbidden Tasks—0
An Examination on the Effectiveness of Divide-and-Conquer Prompting in Large Language Models—0
News Source Credibility Assessment: A Reddit Case Study—0
Stanceosaurus 2.0: Classifying Stance Towards Russian and Spanish Misinformation—0
The World of Generative AI: Deepfakes and Large Language Models—0
List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented GenerationCode0
Redefining "Hallucination" in LLMs: Towards a psychology-informed framework for mitigating misinformation—0
Hierarchical Multi-Label Classification of Online Vaccine Concerns—0
Vision-LLMs Can Fool Themselves with Self-Generated Typographic AttacksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TOKOFOUAverage F189.7—Unverified