arXiv AI
CWF: A Collaborative Writing Framework for Personalized and Reliable Popular Science Writing
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Co-FactChecker: A Framework for Human-AI Collaborative Claim Verification Using Large Reasoning Models
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Towards Automating Scientific Review with Google's Paper Assistant Tool
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AgentPanel: Toward a New Paradigm for Human--AI Collaboration in Exploring Scientific Questions
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AgentPanel: Toward a New Paradigm for Human--AI Collaboration in Exploring Scientific Questions
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Same Verdict, Different Readers: Personalizing Fact-Checking Explanations from Relative Preferences
The paper introduces PERPL, a framework for tailoring fact‑checking explanations to individual readers while preserving factual accuracy. It learns personalized rewriting from relative preferences of simulated LLM readers, using cross‑persona pairing to generate supervision and a progressive learning strategy to refine explanations beyond predefined styles. Experiments show PERPL outperforms larger general‑purpose LLMs in aligning with reader preferences while maintaining high factual fidelity.
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DeepSurvey: Agent-Oriented Automated Survey Generation with Analytical Depth and Citation Reliability
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