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We present MM1.5, a new family of multimodal large language models (MLLMs) designed to enhance capabilities in text-rich image understanding, visual referring and grounding, and multi-image reasoning.
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: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions
Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier · 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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Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang · 2015
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Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
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A diagram is worth a dozen images
Aniruddha Kembhavi, Mike Salvato, Eric Kolve, Minjoon Seo, Hannaneh Hajishirzi, and Ali Farhadi · 2016
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A diagram is worth a dozen images
Aniruddha Kembhavi, Mike Salvato, Eric Kolve, Minjoon Seo, Hannaneh Hajishirzi, and Ali Farhadi · 2016
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Modeling context between objects for referring expression understanding
Varun K Nagaraja, Vlad I Morariu, and Larry S Davis · 2016
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Modeling context in referring expressions
Licheng Yu, Patrick Poirson, Shan Yang, Alexander C Berg, and Tamara L Berg · 2016
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens Van Der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick · 2017
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
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Seq2sql: Generating structured queries from natural language using reinforcement learning
Victor Zhong, Caiming Xiong, and Richard Socher · 2017
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Learning to describe differences between pairs of similar images
Harsh Jhamtani and Taylor Berg-Kirkpatrick · 2018
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Dvqa: Understanding data visualizations via question answering
Kushal Kafle, Brian Price, Scott Cohen, and Christopher Kanan · 2018
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A corpus for reasoning about natural language grounded in photographs
Alane Suhr, Stephanie Zhou, Ally Zhang, Iris Zhang, Huajun Bai, and Yoav Artzi · 2018
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Scene text visual question answering
Ali Furkan Biten, Ruben Tito, Andres Mafla, Lluis Gomez, Marçal Rusinol, Ernest Valveny, CV Jawahar, and Dimosthenis Karatzas · 2019
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Tabfact: A large-scale dataset for table-based fact verification
Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, and William Yang Wang · 2019
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Neural naturalist: Generating fine-grained image comparisons
Maxwell Forbes, Christine Kaeser-Chen, Piyush Sharma, and Serge Belongie · 2019
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LVIS: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollár, and Ross B. Girshick · 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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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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Objects365: A large-scale, high-quality dataset for object detection
Shuai Shao, Zeming Li, Tianyuan Zhang, Chao Peng, Gang Yu, Xiangyu Zhang, Jing Li, and Jian Sun · 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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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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Raven: A dataset for relational and analogical visual reasoning
Chi Zhang, Feng Gao, Baoxiong Jia, Yixin Zhu, and Song-Chun Zhu · 2019
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Widget captioning: Generating natural language description for mobile user interface elements
Yang Li, Gang Li, Luheng He, Jingjie Zheng, Hong Li, and Zhiwei Guan · 2020
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Chart-to-text: Generating natural language descriptions for charts by adapting the transformer model
Jason Obeid and Enamul Hoque · 2020
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Textcaps: a dataset for image captioningwith reading comprehension
Oleksii Sidorov, Ronghang Hu, Marcus Rohrbach, and Amanpreet Singh · 2020
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Deepform: Understand structured documents at scale, 2020
Stacey Svetlichnaya · 2020
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Finqa: A dataset of numerical reasoning over financial data
Zhiyu Chen, Wenhu Chen, Charese Smiley, Sameena Shah, Iana Borova, Dylan Langdon, Reema Moussa, Matt Beane, Ting-Hao Huang, Bryan Routledge, et al · 2021
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Hitab: A hierarchical table dataset for question answering and natural language generation
Zhoujun Cheng, Haoyu Dong, Zhiruo Wang, Ran Jia, Jiaqi Guo, Yan Gao, Shi Han, Jian-Guang Lou, and Dongmei Zhang · 2021
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{GS}hard: Scaling giant models with conditional computation and automatic sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, and Zhifeng Chen · 2021
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Inter-gps: Interpretable geometry problem solving with formal language and symbolic reasoning
Pan Lu, Ran Gong, Shibiao Jiang, Liang Qiu, Siyuan Huang, Xiaodan Liang, and Song-Chun Zhu · 2021
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Iconqa: A new benchmark for abstract diagram understanding and visual language reasoning
Pan Lu, Liang Qiu, Jiaqi Chen, Tony Xia, Yizhou Zhao, Wei Zhang, Zhou Yu, Xiaodan Liang, and Song-Chun Zhu · 2021
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Docvqa: A dataset for vqa on document images
Minesh Mathew, Dimosthenis Karatzas, and CV Jawahar · 2021
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Kleister: key information extraction datasets involving long documents with complex layouts
Tomasz Stanisławek, Filip Graliński, Anna Wróblewska, Dawid Lipiński, Agnieszka Kaliska, Paulina Rosalska, Bartosz Topolski, and Przemysław Biecek · 2021
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Visualmrc: Machine reading comprehension on document images
Ryota Tanaka, Kyosuke Nishida, and Sen Yoshida · 2021
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Multimodal few-shot learning with frozen language models
Maria Tsimpoukelli, Jacob L Menick, Serkan Cabi, SM Eslami, Oriol Vinyals, and Felix Hill · 2021
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Screen2words: Automatic mobile ui summarization with multimodal learning
Bryan Wang, Gang Li, Xin Zhou, Zhourong Chen, Tovi Grossman, and Yang Li · 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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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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TAT-QA: A question answering benchmark on a hybrid of tabular and textual content in finance
Fengbin Zhu, Wenqiang Lei, Youcheng Huang, Chao Wang, Shuo Zhang, Jiancheng Lv, Fuli Feng, and Tat-Seng Chua · 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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Screenqa: Large-scale question-answer pairs over mobile app screenshots
Yu-Chung Hsiao, Fedir Zubach, Maria Wang, and Jindong Chen · 2022
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Ocr-free document understanding transformer
Geewook Kim, Teakgyu Hong, Moonbin Yim, JeongYeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, and Seunghyun Park · 2022
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Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan · 2022
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Chartqa: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Do Xuan Long, Jia Qing Tan, Shafiq Joty, and Enamul Hoque · 2022
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Infographicvqa
Minesh Mathew, Viraj Bagal, Rubèn Tito, Dimosthenis Karatzas, Ernest Valveny, and CV Jawahar · 2022
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Predicting and explaining mobile ui tappability with vision modeling and saliency analysis
Eldon Schoop, Xin Zhou, Gang Li, Zhourong Chen, Bjoern Hartmann, and Yang Li · 2022
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A-okvqa: A benchmark for visual question answering using world knowledge
Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, Kenneth Marino, and Roozbeh Mottaghi · 2022
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St-moe: Designing stable and transferable sparse expert models
Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, and William Fedus · 2022
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Openflamingo: An open-source framework for training large autoregressive vision-language models
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Gadre, Shiori Sagawa, et al · 2023
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Qwen-vl: A frontier large vision-language model with versatile abilities
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
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Automatikz: Text-guided synthesis of scientific vector graphics with tikz
Jonas Belouadi, Anne Lauscher, and Steffen Eger · 2023
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Minigpt-v2: large language model as a unified interface for vision-language multi-task learning
Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, and Mohamed Elhoseiny · 2023
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Shikra: Unleashing multimodal llm’s referential dialogue magic
Keqin Chen, Zhao Zhang, Weili Zeng, Richong Zhang, Feng Zhu, and Rui Zhao · 2023
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Sharegpt4v: Improving large multi-modal models with better captions
Lin Chen, Jisong Li, Xiaoyi Dong, Pan Zhang, Conghui He, Jiaqi Wang, Feng Zhao, and Dahua Lin · 2023
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Dreamsim: Learning new dimensions of human visual similarity using synthetic data
Stephanie Fu*, Netanel Tamir*, Shobhita Sundaram*, Lucy Chai, Richard Zhang, Tali Dekel, and Phillip Isola · 2023
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A framework for few-shot language model evaluation, 12 2023
Leo Gao, Jonathan Tow, Baber Abbasi, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Alain Le Noac’h, Haonan Li, Kyle McDonell, Niklas Muennighoff, Chris Ociepa, Jason Phang, Laria Reynolds, Hailey Schoelkopf, Aviya Skowron, Lintang Sutawika, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou · 2023
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Language is not all you need: Aligning perception with language models
Shaohan Huang, Li Dong, Wenhui Wang, Yaru Hao, Saksham Singhal, Shuming Ma, Tengchao Lv, Lei Cui, Owais Khan Mohammed, Barun Patra, et al · 2023
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Geomverse: A systematic evaluation of large models for geometric reasoning
Mehran Kazemi, Hamidreza Alvari, Ankit Anand, Jialin Wu, Xi Chen, and Radu Soricut · 2023
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Mimic-it: Multi-modal in-context instruction tuning
Bo Li, Yuanhan Zhang, Liangyu Chen, Jinghao Wang, Fanyi Pu, Jingkang Yang, Chunyuan Li, and Ziwei Liu · 2023
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Seed-bench: Benchmarking multimodal llms with generative comprehension
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Spotlight: Mobile UI understanding using vision-language models with a focus
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IntentQA: Context-aware video intent reasoning
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Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
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Lisa: Reasoning segmentation via large language model
Xin Lai, Zhuotao Tian, Yukang Chen, Yanwei Li, Yuhui Yuan, Shu Liu, and Jiaya Jia · 2024
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