VideoAutoArena: An Automated Arena for Evaluating Large Multimodal Models in Video Analysis through User Simulation

Rank analysis of incomplete block designs: I. the method of paired comparisons

Ralph Allan Bradley and Milton E. Terry · 1952

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The USCF Rating System: Its Development, Theory, and Applications

A.E. Elo · 1966

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Visualizing data using t-sne

Laurens van der Maaten and Geoffrey Hinton · 2008

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The ”something something” video database for learning and evaluating visual common sense

Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fründ, Peter Yianilos, Moritz Mueller-Freitag, Florian Hoppe, Christian Thurau, Ingo Bax, and Roland Memisevic · 2017

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Video question answering via gradually refined attention over appearance and motion

Dejing Xu, Zhou Zhao, Jun Xiao, Fei Wu, Hanwang Zhang, Xiangnan He, and Yueting Zhuang · 2017

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Activitynet-qa: A dataset for understanding complex web videos via question answering

Zhou Yu, Dejing Xu, Jun Yu, Ting Yu, Zhou Zhao, Yueting Zhuang, and Dacheng Tao · 2019

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Language models are few-shot learners

Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020

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Training verifiers to solve math word problems

Original

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman · 2021

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AGQA: A benchmark for compositional spatio-temporal reasoning

Madeleine Grunde-McLaughlin, Ranjay Krishna, and Maneesh Agrawala · 2021

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Measuring massive multitask language understanding

Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2021

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Next-qa: Next phase of question-answering to explaining temporal actions

Junbin Xiao, Xindi Shang, Angela Yao, and Tat-Seng Chua · 2021

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Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond

Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023

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Instructblip: Towards general-purpose vision-language models with instruction tuning

Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven C. H. Hoi · 2023

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BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models

Junnan Li, Dongxu Li, Silvio Savarese, and Steven C. H. Hoi · 2023

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Video-llava: Learning united visual representation by alignment before projection

Original

Bin Lin, Yang Ye, Bin Zhu, Jiaxi Cui, 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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Valley: Video assistant with large language model enhanced ability

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Ruipu Luo, Ziwang Zhao, Min Yang, Junwei Dong, Minghui Qiu, Pengcheng Lu, Tao Wang, and Zhongyu Wei · 2023

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Macaw-llm: Multi-modal language modeling with image, audio, video, and text integration

Original

Chenyang Lyu, Minghao Wu, Longyue Wang, Xinting Huang, Bingshuai Liu, Zefeng Du, Shuming Shi, and Zhaopeng Tu · 2023

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Egoschema: A diagnostic benchmark for very long-form video language understanding

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Perception test: A diagnostic benchmark for multimodal video models

Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adrià Recasens, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre Fréchette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, and João Carreira · 2023

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ST-LLM: large language models are effective temporal learners

Ruyang Liu, Chen Li, Haoran Tang, Yixiao Ge, Ying Shan, and Ge Li · 2024

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Tempcompass: Do video llms really understand videos?

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Wildvision: Evaluating vision-language models in the wild with human preferences

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Yujie Lu, Dongfu Jiang, Wenhu Chen, William Yang Wang, Yejin Choi, and Bill Yuchen Lin · 2024

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Wizardcoder: Empowering code large language models with evol-instruct

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xgen-mm-vid (blip-3-video): You only need 32 tokens to represent a video even in vlms

Michael S. Ryoo, Honglu Zhou, Shrikant B. Kendre, Can Qin, Le Xue, Manli Shu, Silvio Savarese, Ran Xu, Caiming Xiong, and Juan Carlos Niebles · 2024

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