9 papers
MINERVA-Cultural: A Benchmark for Cultural and Multilingual Long Video Reasoning
Darshan Singh, Arsha Nagrani, Kawshik Manikantan +6
Recent advancements in video models have shown tremendous progress, particularly in long video understanding. However, current benchmarks predominantly feature western-centric data…
CRIT: Graph-Based Automatic Data Synthesis to Enhance Cross-Modal Multi-Hop Reasoning
Junyoung Sung, Seungwoo Lyu, Minjun Kim +3
Real-world reasoning often requires combining information across modalities, connecting textual context with visual cues in a multi-hop process. Yet, most multimodal benchmarks fai…
CAViAR: Critic-Augmented Video Agentic Reasoning
Sachit Menon, Ahmet Iscen, Arsha Nagrani +3
Video understanding has seen significant progress in recent years, with models' performance on perception from short clips continuing to rise. Yet, multiple recent benchmarks, such…
VoCap: Video Object Captioning and Segmentation from Any Prompt
Jasper Uijlings, Xingyi Zhou, Xiuye Gu +5
Understanding objects in videos in terms of fine-grained localization masks and detailed semantic properties is a fundamental task in video understanding. In this paper, we propose…
MINERVA: Evaluating Complex Video Reasoning
Arsha Nagrani, Sachit Menon, Ahmet Iscen +9
Multimodal LLMs are turning their focus to video benchmarks, however most video benchmarks only provide outcome supervision, with no intermediate or interpretable reasoning steps.…
MoReVQA: Exploring Modular Reasoning Models for Video Question Answering
Juhong Min, Shyamal Buch, Arsha Nagrani +2
This paper addresses the task of video question answering (videoQA) via a decomposed multi-stage, modular reasoning framework. Previous modular methods have shown promise with a si…