LG-CoTrain, an LLM-guided co-training method, outperforms classical semi-supervised baselines for crisis tweet classification in low-resource settings with 5-25 labeled examples per class.
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AttentionBender applies 2D transforms to cross-attention maps in video diffusion transformers, producing distributed distortions and glitch aesthetics that reveal entangled attention mechanisms while serving as both an XAI probe and creative tool.
LLMs achieve 64% accuracy detecting Wikipedia bias and remove 79% of words removed by editors when correcting, but produce high-recall low-precision edits rated more neutral by crowds than human versions.
citing papers explorer
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LLM-guided Semi-Supervised Approaches for Social Media Crisis Data Classification
LG-CoTrain, an LLM-guided co-training method, outperforms classical semi-supervised baselines for crisis tweet classification in low-resource settings with 5-25 labeled examples per class.
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AttentionBender: Manipulating Cross-Attention in Video Diffusion Transformers as a Creative Probe
AttentionBender applies 2D transforms to cross-attention maps in video diffusion transformers, producing distributed distortions and glitch aesthetics that reveal entangled attention mechanisms while serving as both an XAI probe and creative tool.
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Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms
LLMs achieve 64% accuracy detecting Wikipedia bias and remove 79% of words removed by editors when correcting, but produce high-recall low-precision edits rated more neutral by crowds than human versions.