1 citations · 1 across the 6 of their papers we have counts for
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CaST-Bench: Benchmarking Causal Chain-Grounded Spatio-Temporal Reasoning for Video Question Answering
Mingfang Zhang, Jingjing Pan, Ashutosh Kumar +7
Cause-and-effect reasoning in video is a significant challenge for Vision-Language Models (VLMs), as it requires going beyond surface-level perception to a deeper understanding of…
FindIt: A Format-Informed Visual Detection Benchmark for Generalist Multimodal LLMs
Eshika Khandelwal, Jingjing Pan, Mingfang Zhang +3
Multimodal large language models (MLLMs) are predominantly evaluated on free-form vision-language tasks such as visual question answering, captioning, and summarization. However, t…
ParallelVLM: Lossless Video-LLM Acceleration with Visual Alignment Aware Parallel Speculative Decoding
Quan Kong, Yuhao Shen, Yicheng Ji +2
Although current Video-LLMs achieve impressive performance in video understanding tasks, their autoregressive decoding efficiency remains constrained by the massive number of video…
Vision-TTT: Efficient and Expressive Visual Representation Learning with Test-Time Training
Quan Kong, Yanru Xiao, Yuhao Shen +1
Learning efficient and expressive visual representation has long been the pursuit of computer vision research. While Vision Transformers (ViTs) gradually replace traditional Convol…