PluRule is a new multimodal multilingual benchmark showing that state-of-the-art vision-language models perform only marginally better than a trivial baseline at detecting specific rule violations in pluralistic online communities.
Proceedings of the 2024
3 Pith papers cite this work, alongside 15 external citations. Polarity classification is still indexing.
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Pith papers citing it
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representative citing papers
LLM hidden states encode enough information to predict chain-of-thought success before any reasoning tokens are generated, outperforming a text-only classifier.
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.
citing papers explorer
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PluRule: A Benchmark for Moderating Pluralistic Communities on Social Media
PluRule is a new multimodal multilingual benchmark showing that state-of-the-art vision-language models perform only marginally better than a trivial baseline at detecting specific rule violations in pluralistic online communities.
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Knowing Before Saying: LLM Representations Encode Information About Chain-of-Thought Success Before Completion
LLM hidden states encode enough information to predict chain-of-thought success before any reasoning tokens are generated, outperforming a text-only classifier.
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UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.