1 citations · 1 across the 8 of their papers we have counts for
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Video-Arena: A Scalable Agentic Video Benchmark for Spatiotemporal Capability
Kuan Zhang, Yukun Chen, Zhihao Yang +7
Understanding and tracking a dynamic world are fundamental to visual intelligence. Existing video benchmarks provide limited insight into whether models can maintain a coherent und…
Learning Multimodal Embeddings with Evidence-Aligned Readout
Zirong Chen, Fuda Ye, Enjun Du +8
Multimodal large language models can expose task-relevant evidence through generation, but producing useful evidence does not by itself determine how it enters a retrieval embeddin…
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…
EVQAScore: A Fine-grained Metric for Video Question Answering Data Quality Evaluation
Hao Liang, Zirong Chen, Hejun Dong +1
Video question-answering (QA) is a core task in video understanding. Evaluating the quality of video QA and video caption data quality for training video large language models (Vid…
MathScape: Benchmarking Multimodal Large Language Models in Real-World Mathematical Contexts
Hao Liang, Linzhuang Sun, Minxuan Zhou +7
With the rapid progress of Multimodal LLMs, evaluating their mathematical reasoning capabilities has become an increasingly important research direction. In particular, visual-text…