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Author

Kaisi Guan

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Preprint Oct 2026

SyncReward: Human-Aligned Synchronization Reward for Audio-Visual Generation

A comprehensive study spanning data, benchmarking, and reward modeling, which develops SyncReward, a reward model that combines semantic--temporal contrastive pretraining on real clips with human supervision on generated clips and achieves the strongest agreement with human ratings among the evaluated methods.

Kai-Si Guan, Ying Ba, Wen-Jing Wang et al. · 0 citations
Preprint Aug 2026

FATE: Frame-Level Audio-Visual Temporal Embedding

Across three tasks, FATE surpasses the strongest baseline on temporal and semantic retrieval by a large margin, matches fully supervised methods on event localization in a zero-shot setting, and achieves the best correlation with human judgments as a generation evaluation metric.

Kaisi Guan, Bingzi Zhang, Xihua Wang et al. · 0 citations

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