AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-art AI video generation models~(AIVGMs) have become increasingly difficult to discern using conventional evaluation criteria, such as visual fidelity and semantic instru...
Zi-Heng Jia, Jia-Ying Qian, Zi-Cheng Zhang et al.· 0 citations
RePair is introduced, guided by three principles---Validity, Minimality, and Locality---which mines false positives bidirectionally, applies LLM-guided counterfactual editing, and trains with a local hard-pair contrastive objective.
Si-Yi Liu, Xiao-Rong Zhu, En-Jun Du et al.· 0 citations
Large vision-language models used as listwise rerankers must jointly process visual tokens from tens of candidates per query, making token pruning essential for practical deployment. Existing pruning methods retain tokens by attention saliency, yet we show that saliency is systematically misaligned with ranking contrib...
Si-Yi Liu, Han-Jun Yang, Chen-Chen Zhang et al.· 1 citation
ELBench is introduced, the first benchmark to evaluate all four requirements (General Capability, Safety and Trustworthiness, Basic Education, and High-Level Cultivation) on the same models under a common protocol, combining curated public sources with newly synthesized safety and cultivation data.
Yi-Lin Jiang, Xiao-Rong Zhu, Fei Tan et al.· 0 citations
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