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Multimodal large language models (MLLMs) have gained significant attention due to their strong multimodal understanding capability.
Indoor segmentation and support inference from rgbd images
Pushmeet Kohli Nathan Silberman, Derek Hoiem and Rob Fergus · 2012
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Referitgame: Referring to objects in photographs of natural scenes
Sahar Kazemzadeh, Vicente Ordonez, Mark Matten, and Tamara Berg · 2014
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick · 2015
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Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
Bryan A Plummer, Liwei Wang, Chris M Cervantes, Juan C Caicedo, Julia Hockenmaier, and Svetlana Lazebnik · 2015
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Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 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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Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh · 2017
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, et al · 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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Vizwiz grand challenge: Answering visual questions from blind people
Danna Gurari, Qing Li, Abigale J Stangl, Anhong Guo, Chi Lin, Kristen Grauman, Jiebo Luo, and Jeffrey P Bigham · 2018
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From film to video: Multi-turn question answering with multi-modal context
Dat Tien Nguyen, Shikhar Sharma, Hannes Schulz, and Layla El Asri · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut · 2018
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nocaps: novel object captioning at scale
Harsh Agrawal, Karan Desai, Yufei Wang, Xinlei Chen, Rishabh Jain, Mark Johnson, Dhruv Batra, Devi Parikh, Stefan Lee, and Peter Anderson · 2019
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Audio-visual scene-aware dialog
Huda Alamri, Vincent Cartillier, Abhishek Das, Jue Wang, Anoop Cherian, Irfan Essa, Dhruv Batra, Tim K. Marks, Chiori Hori, Peter Anderson, Stefan Lee, and Devi Parikh · 2019
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Gqa: A new dataset for real-world visual reasoning and compositional question answering
Drew A Hudson and Christopher D Manning · 2019
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Audiocaps: Generating captions for audios in the wild
Chris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, and Gunhee Kim · 2019
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Multimodal transformer networks for end-to-end video-grounded dialogue systems
Hung Le, Doyen Sahoo, Nancy F Chen, and Steven CH Hoi · 2019
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Ok-vqa: A visual question answering benchmark requiring external knowledge
Kenneth Marino, Mohammad Rastegari, Ali Farhadi, and Roozbeh Mottaghi · 2019
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Ocr-vqa: Visual question answering by reading text in images
Anand Mishra, Shashank Shekhar, Ajeet Kumar Singh, and Anirban Chakraborty · 2019
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Towards vqa models that can read
Amanpreet Singh, Vivek Natarajan, Meet Shah, Yu Jiang, Xinlei Chen, Dhruv Batra, Devi Parikh, and Marcus Rohrbach · 2019
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Three scenarios for continual learning
Gido M Van de Ven and Andreas S Tolias · 2019
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Vatex: A large-scale, high-quality multilingual dataset for video-and-language research
Xin Wang, Jiawei Wu, Junkun Chen, Lei Li, Yuan-Fang Wang, and William Yang Wang · 2019
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Clotho: An audio captioning dataset
Konstantinos Drossos, Samuel Lipping, and Tuomas Virtanen · 2020
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Hero: Hierarchical encoder for video+ language omni-representation pre-training
Linjie Li, Yen-Chun Chen, Yu Cheng, Zhe Gan, Licheng Yu, and Jingjing Liu · 2020
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Textcaps: a dataset for image captioning with reading comprehension
Oleksii Sidorov, Ronghang Hu, Marcus Rohrbach, and Amanpreet Singh · 2020
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Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
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Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans
Ainaz Eftekhar, Alexander Sax, Jitendra Malik, and Amir Zamir · 2021
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AST: Audio Spectrogram Transformer
Yuan Gong, Yu-An Chung, and James Glass · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Perceiver: General perception with iterative attention
Andrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, and Joao Carreira · 2021
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Pretrained transformers as universal computation engines
Kevin Lu, Aditya Grover, Pieter Abbeel, and Igor Mordatch · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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https://sharegpt.com/ , 2023
Sharegpt · 2023
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Objaverse: A universe of annotated 3d objects
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Pengi: An audio language model for audio tasks
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Mme: A comprehensive evaluation benchmark for multimodal large language models
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Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 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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Videoclip: Contrastive pre-training for zero-shot video-text understanding
Hu Xu, Gargi Ghosh, Po-Yao Huang, Dmytro Okhonko, Armen Aghajanyan, Florian Metze, Luke Zettlemoyer, and Christoph Feichtenhofer · 2021
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Just ask: Learning to answer questions from millions of narrated videos
Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, and Cordelia Schmid · 2021
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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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A massive 7t fmri dataset to bridge cognitive neuroscience and artificial intelligence
Emily J Allen, Ghislain St-Yves, Yihan Wu, Jesse L Breedlove, Jacob S Prince, Logan T Dowdle, Matthias Nau, Brad Caron, Franco Pestilli, Ian Charest, et al · 2022
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Omnivore: A single model for many visual modalities
Rohit Girdhar, Mannat Singh, Nikhila Ravi, Laurens van der Maaten, Armand Joulin, and Ishan Misra · 2022
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Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Zhenyu Qiu, Wei Lin, Jinrui Yang, Xiawu Zheng, et al · 2023
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Llama-adapter v2: Parameter-efficient visual instruction model
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Imagebind: One embedding space to bind them all
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Imagebind-llm: Multi-modality instruction tuning
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Obelisc: An open web-scale filtered dataset of interleaved image-text documents
Hugo Laurençon, Lucile Saulnier, Léo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M Rush, Douwe Kiela, et al · 2023
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Scalable 3d captioning with pretrained models
Tiange Luo, Chris Rockwell, Honglak Lee, and Justin Johnson · 2023
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Large language models as general pattern machines
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Anymal: An efficient and scalable any-modality augmented language model
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OpenAI · 2023
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Dinov2: Learning robust visual features without supervision
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From sparse to soft mixtures of experts
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Reconstructing the mind’s eye: fmri-to-image with contrastive learning and diffusion priors
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mplug-owl: Modularization empowers large language models with multimodality
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