1 citations · 1 across the 5 of their papers we have counts for
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SnapBench: Benchmarking Snap-and-Ask Multimodal Retrieval for Mobile Interactions
Zirong Chen, Fuda Ye, Kuan Zhang +7
Mobile AI acts as a visual oracle, empowering users to snap a picture of something and ask for information. Snap-and-ask retrieval is now one of the most common entry points for mo…
EviRank: Structured Relevance Evidence for Multimodal Image Re-ranking
Enjun Du, Siyi Liu, Zirong Chen +8
Real-world image search queries are multimodal and compositional: ``find this shirt in pink'' specifies an entity to retain, an attribute to modify, and context to ignore. Yet exis…
Beyond Closed-Pool Video Retrieval: A Benchmark and Agent Framework for Real-World Video Search and Moment Localization
Tao Yu, Yujia Yang, Haopeng Jin +17
Traditional video retrieval benchmarks focus on matching precise descriptions to closed video pools, failing to reflect real-world searches characterized by fuzzy, multi-dimensiona…
VDE Bench: Evaluating The Capability of Image Editing Models to Modify Visual Documents
Hongzhu Yi, Yujia Yang, Yuanxiang Wang +18
In recent years, image editing models have made significant progress, enabling users to manipulate visual content in a flexible and interactive manner through natural language inst…
ARC-Hunyuan-Video-7B: Structured Video Comprehension of Real-World Shorts
Yuying Ge, Yixiao Ge, Chen Li +15
Real-world user-generated short videos, especially those distributed on platforms such as WeChat Channel and TikTok, dominate the mobile internet. However, current large multimodal…