DualGuard uses adaptive dual-stream watermark signals to detect and trace both paraphrase and spoofing attacks in LLM outputs while preserving text quality.
Findings of the Association for Computational Linguistics
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A new 30k-instance semantic segmentation dataset plus block distillation with sink tokens, dropout, and weighted loss lets block-attention models reach near full-attention performance on long texts.
A proposed pipeline shows LLMs introduce detectable race and gender biases when summarizing life narratives, creating potential for representational harm in research.
citing papers explorer
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Towards Generalization of Block Attention via Automatic Segmentation and Block Distillation
A new 30k-instance semantic segmentation dataset plus block distillation with sink tokens, dropout, and weighted loss lets block-attention models reach near full-attention performance on long texts.
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Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives
A proposed pipeline shows LLMs introduce detectable race and gender biases when summarizing life narratives, creating potential for representational harm in research.