CLIPScore uses a web-pretrained CLIP model to evaluate image captions without references and achieves higher human correlation than CIDEr or SPICE.
Newsclippings: Automatic generation of out-of-context multimodal media
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
representative citing papers
The XNote dataset and LVLM benchmarks demonstrate that current models face significant challenges in generating accurate, grounded Community Notes for image-based contextual deception.
Introduces claim-conditioned re-scoring (SIFT) and warranted supports proportion (WSP) metric, reporting accuracy recovery up to 27.6 points and WSP calibration at AUC 0.92 on FEVER, SciFact and other benchmarks.
RW-Post is an auditable benchmark linking social media posts to evidence from human fact-check articles for evaluating multimodal AI fact-checking across different evidence regimes.
RW-Post is an auditable text-image benchmark for real-world multimodal fact-checking that links posts to evidence traces from human fact-check articles and includes the AgentFact baseline for evaluation.
CRAVE is a new framework that clusters retrieved text and image evidence into narratives and uses an LLM judge to produce explained fact-checking verdicts.
citing papers explorer
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CLIPScore: A Reference-free Evaluation Metric for Image Captioning
CLIPScore uses a web-pretrained CLIP model to evaluate image captions without references and achieves higher human correlation than CIDEr or SPICE.
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XNote: Benchmarking Automated Community Notes Generation for Image-based Contextual Deception
The XNote dataset and LVLM benchmarks demonstrate that current models face significant challenges in generating accurate, grounded Community Notes for image-based contextual deception.
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The Warrant Gap: Claim-Conditioned Re-scoring for Fact-Checking
Introduces claim-conditioned re-scoring (SIFT) and warranted supports proportion (WSP) metric, reporting accuracy recovery up to 27.6 points and WSP calibration at AUC 0.92 on FEVER, SciFact and other benchmarks.
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RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild
RW-Post is an auditable benchmark linking social media posts to evidence from human fact-check articles for evaluating multimodal AI fact-checking across different evidence regimes.
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RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild
RW-Post is an auditable text-image benchmark for real-world multimodal fact-checking that links posts to evidence traces from human fact-check articles and includes the AgentFact baseline for evaluation.
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Fact-Checking with Contextual Narratives: Leveraging Retrieval-Augmented LLMs for Social Media Analysis
CRAVE is a new framework that clusters retrieved text and image evidence into narratives and uses an LLM judge to produce explained fact-checking verdicts.