ViPER: Empowering the Self-Evolution of Visual Perception Abilities in Vision-Language Models
Juntian Zhang · Song Jin · Chuanqi Cheng · Yuhan Liu · Yankai Lin · Xun Zhang · Yufei zhang · Fei Jiang · Guojun Yin · Shuai Chen · Rui Yan
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Juntian Zhang · Song Jin · Chuanqi Cheng · Yuhan Liu · Yankai Lin · Xun Zhang · Yufei zhang · Fei Jiang · Guojun Yin · Shuai Chen · Rui Yan
Yubo Wang · Juntian Zhang · Yichen WU · Yankai Lin · Nils Lukas · Yuhan Liu
While Chain-of-Thought empowers Large Vision-Language Models with multi-step reasoning, explicit textual rationales suffer from an information bandwidth bottleneck, where continuous visual details are discarded during discrete tokenization. Recent latent reasoning methods attempt to address this...
Song Jin · Juntian Zhang · Xun Zhang · Zeying Tian · Fei Jiang · Guojun Yin · Shuai Chen · Yong Liu · Rui Yan
Recent advancements in Vision-Language Models (VLMs) have revolutionized general visual understanding. However, their application in the food domain remains constrained by benchmarks that rely on coarse-grained categories, single-view imagery, and inaccurate metadata. To bridge this gap, we intro...
Zixiao Wang · Duzhen Zhang · Juntian Zhang · Yuhan Liu · Guoming Li · Haolun Wu · Le Song · Xiuying Chen
When reading foreign-language literature, non-native users often face significant challenges. Existing traditional machine translation systems tend to obscure or mistranslate key terminology, while paraphrasing aimed at lay readers often oversimplifies it, thereby hindering their ability to maste...
Dylan Xinming Hou · Juntian Zhang · Xu Gu · Yichen WU · Nils Lukas · Gus Xia · Xiuying Chen · Yuhan Liu
The evolving realism of AI-generated Videos (AIGC-V) is rapidly rendering traditional artifact-centric detection insufficient, necessitating a paradigm shift from low-level inspection to high-level semantic verification. This paper presents a comprehensive survey of AIGC-V detection, reframing th...