Papers by Yangyang Liang

    1 papers
    AdaJudge: Adaptive Multi-Perspective Judging for Reward Modeling (2026.acl-long)

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    Challenge: Existing reward models rely on a static pooling strategy to condense sequences into scalar scores, which is ill-suited for fine-grained discrimination.
    Approach: They propose a framework that jointly adapts representation and aggregation to address these limitations by integrating a static inductive bias with a representational mismatch.
    Outcome: Experiments on RM-Bench and JudgeBench show that AdaJudge outperforms strong off-the-shelf reward models and traditional pooling baselines.

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