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Vision-language large models have achieved remarkable success in various multi-modal tasks, yet applying them to video understanding remains challenging due to the inherent complexity and computational demands of video data.
Collecting highly parallel data for paraphrase evaluation
David Chen and William B Dolan · 2011
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Activitynet: A large-scale video benchmark for human activity understanding
Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem, and Juan Carlos Niebles · 2015
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Msr-vtt: A large video description dataset for bridging video and language
Jun Xu, Tao Mei, Ting Yao, and Yong Rui · 2016
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Tgif-qa: Toward spatio-temporal reasoning in visual question answering
Yunseok Jang, Yale Song, Youngjae Yu, Youngjin Kim, and Gunhee Kim · 2017
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Language models are few-shot learners
Tom B Brown · 2020
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
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Zero-shot video question answering via frozen bidirectional language models, 2022
Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, and Cordelia Schmid · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Instructblip: Towards general-purpose vision-language models with instruction tuning, 2023
Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi · 2023
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Video-llava: Learning united visual representation by alignment before projection
Bin Lin, Bin Zhu, Yang Ye, Munan Ning, Peng Jin, and Li Yuan · 2023
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Vista-llama: Reliable video narrator via equal distance to visual tokens
Fan Ma, Xiaojie Jin, Heng Wang, Yuchen Xian, Jiashi Feng, and Yi Yang · 2023
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Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, and Jianfeng Gao · 2023
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Audio-visual llm for video understanding
Fangxun Shu, Lei Zhang, Hao Jiang, and Cihang Xie · 2023
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Video understanding with large language models: A survey
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Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks
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Videollama 2: Advancing spatial-temporal modeling and audio understanding in video-llms
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An image grid can be worth a video: Zero-shot video question answering using a vlm
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Llama: Open and efficient foundation language models
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Vid2seq: Large-scale pretraining of a visual language model for dense video captioning
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Video-llama: An instruction-tuned audio-visual language model for video understanding
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Minigpt-5: Interleaved vision-and-language generation via generative vokens
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Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
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Wonkyun Kim, Changin Choi, Wonseok Lee, and Wonjong Rhee · 2024
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Mvbench: A comprehensive multi-modal video understanding benchmark
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Llava-next: A strong zero-shot video understanding model
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