iDiff is a dual-branch framework with an Answer Model for robust pairwise preference prediction via view decomposition and ensembles, and a Thinking Model for structured rationale generation using templates and answer-aware supervision, winning first place in the NTIRE 2026 RAIM challenge.
Rouge: A package for automatic eval- uation of summaries
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iDiff: Interpretable Difference-aware Framework for Pairwise Image Quality Assessment
iDiff is a dual-branch framework with an Answer Model for robust pairwise preference prediction via view decomposition and ensembles, and a Thinking Model for structured rationale generation using templates and answer-aware supervision, winning first place in the NTIRE 2026 RAIM challenge.