Diffusion-based localized editing framework for faithful summarization of evolving contexts, introducing the StreamSum benchmark and showing tradeoffs in faithfulness, speed, and preservation.
W.; Burnsky, J.; Vincent, J
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A proposed pipeline shows LLMs introduce detectable race and gender biases when summarizing life narratives, creating potential for representational harm in research.
LaMSUM is a novel multi-level LLM framework with voting methods for extractive summarization of large incident report collections that outperforms prior extractive methods.
citing papers explorer
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Detect, Remask, Repair: Diffusion Editing for Faithful Summarization of Evolving Contexts
Diffusion-based localized editing framework for faithful summarization of evolving contexts, introducing the StreamSum benchmark and showing tradeoffs in faithfulness, speed, and preservation.
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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.
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LaMSUM: Amplifying Voices Against Harassment through LLM Guided Extractive Summarization of User Incident Reports
LaMSUM is a novel multi-level LLM framework with voting methods for extractive summarization of large incident report collections that outperforms prior extractive methods.