RbtAct uses rebuttals to supervise training of models that generate actionable, perspective-specific review feedback, yielding gains in actionability over baselines on a new 75K dataset.
This includes the use of inappropriate or missing evaluation metrics, insufficient analysis of results, or inconsistencies between reported results and the paper’s claims
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RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation
RbtAct uses rebuttals to supervise training of models that generate actionable, perspective-specific review feedback, yielding gains in actionability over baselines on a new 75K dataset.