Fetching the paper…
Reading the bibliography…
We introduce MuirBench, a comprehensive benchmark that focuses on robust multi-image understanding capabilities of multimodal LLMs.
Why is a picture worth a thousand words?
George L Gropper · 1963
Earlier work this paper cites.
The geometry of multiple images: the laws that govern the formation of multiple images of a scene and some of their applications
Olivier Faugeras, Quang-Tuan Luong, and Theo Papadopoulo · 2001
Earlier work this paper cites.
A picture is worth a thousand words: Using visual images to improve comprehension for middle school struggling readers
Anne Nielsen Hibbing and Joan L Rankin-Erickson · 2003
Earlier work this paper cites.
The effect of powerpoint presentations on student learning and attitudes
Hossein Nouri and Abdus Shahid · 2005
Earlier work this paper cites.
Im2gps: estimating geographic information from a single image
James Hays and Alexei A Efros · 2008
Earlier work this paper cites.
Action-conditional video prediction using deep networks in atari games
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L Lewis, and Satinder Singh · 2015
Earlier work this paper cites.
Unsupervised learning for physical interaction through video prediction
Chelsea Finn, Ian Goodfellow, and Sergey Levine · 2016
Earlier work this paper cites.
A picture is worth more words over time: Multimodality and narrative structure across eight decades of american superhero comics
Neil Cohn, Ryan Taylor, and Kaitlin Pederson · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Know what you don’t know: Unanswerable questions for squad
Pranav Rajpurkar, Robin Jia, and Percy Liang · 2018
Earlier work this paper cites.
Deep learning for multiple-image super-resolution
Michal Kawulok, Pawel Benecki, Szymon Piechaczek, Krzysztof Hrynczenko, Daniel Kostrzewa, and Jakub Nalepa · 2019
Earlier work this paper cites.
A corpus for reasoning about natural language grounded in photographs
Alane Suhr, Stephanie Zhou, Ally Zhang, Iris Zhang, Huajun Bai, and Yoav Artzi · 2019
Earlier work this paper cites.
Visual question answering on image sets
Ankan Bansal, Yuting Zhang, and Rama Chellappa · 2020
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
University-1652: A multi-view multi-source benchmark for drone-based geo-localization
Zhedong Zheng, Yunchao Wei, and Yi Yang · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
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
Earlier work this paper cites.
D2s: Document-to-slide generation via query-based text summarization
Edward Sun, Yufang Hou, Dakuo Wang, Yunfeng Zhang, and Nancy XR Wang · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
There’s a time and place for reasoning beyond the image
Xingyu Fu, Ben Zhou, Ishaan Chandratreya, Carl Vondrick, and Dan Roth · 2022
Earlier work this paper cites.
Ego4d: Around the world in 3,000 hours of egocentric video
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, et al · 2022
Earlier work this paper cites.
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
Earlier work this paper cites.
ChartQA: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Do Long, Jia Qing Tan, Shafiq Joty, and Enamul Hoque · 2022
Earlier work this paper cites.
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, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, and Ludwig Schmidt · 2023
Earlier work this paper cites.
Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond, 2023
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
Cited alongside, same era.
Minigpt-v2: large language model as a unified interface for vision-language multi-task learning, 2023
Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, and Mohamed Elhoseiny · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks
Zhe Chen, Jiannan Wu, Wenhai Wang, Weijie Su, Guo Chen, Sen Xing, Zhong Muyan, Qinglong Zhang, Xizhou Zhu, Lewei Lu, et al · 2023
Cited alongside, same era.
Introducing mpt-7b: A new standard for open-source, commercially usable llms, 2023
MosaicML NLP Team · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Later among the works it cites.
Genecis: A benchmark for general conditional image similarity
Sagar Vaze, Nicolas Carion, and Ishan Misra · 2023
Later among the works it cites.
Cogvlm: Visual expert for pretrained language models, 2023
Weihan Wang, Qingsong Lv, Wenmeng Yu, Wenyi Hong, Ji Qi, Yan Wang, Junhui Ji, Zhuoyi Yang, Lei Zhao, Xixuan Song, Jiazheng Xu, Bin Xu, Juanzi Li, Yuxiao Dong, Ming Ding, and Jie Tang · 2023
Later among the works it cites.
Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Opencompass: A universal evaluation platform for foundation models
OpenCompass Contributors · 2023
Cited alongside, same era.
Xtuner: A toolkit for efficiently fine-tuning llm
XTuner Contributors · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Eva: Exploring the limits of masked visual representation learning at scale
Yuxin Fang, Wen Wang, Binhui Xie, Quan Sun, Ledell Wu, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2023
Cited alongside, same era.
Tianrui Guan, Fuxiao Liu, Xiyang Wu, Ruiqi Xian, Zongxia Li, Xiaoyu Liu, Xijun Wang, Lichang Chen, Furong Huang, Yaser Yacoob, et al · 2023
Cited alongside, same era.
Seed-bench-2: Benchmarking multimodal large language models
Bohao Li, Yuying Ge, Yixiao Ge, Guangzhi Wang, Rui Wang, Ruimao Zhang, and Ying Shan · 2023
Cited alongside, same era.
Vila: On pre-training for visual language models, 2023
Ji Lin, Hongxu Yin, Wei Ping, Yao Lu, Pavlo Molchanov, Andrew Tao, Huizi Mao, Jan Kautz, Mohammad Shoeybi, and Song Han · 2023
Cited alongside, same era.
Visual spatial reasoning
Fangyu Liu, Guy Emerson, and Nigel Collier · 2023
Cited alongside, same era.
Later among the works it cites.
Uavm’23: 2023 workshop on uavs in multimedia: Capturing the world from a new perspective
Zhedong Zheng, Yujiao Shi, Tingyu Wang, Jun Liu, Jianwu Fang, Yunchao Wei, and Tat-seng Chua · 2023
Later among the works it cites.
Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu, Naoto Usuyama, Sheng Zhang, Fei Wang, Yujia Xie, Mahmoud Khademi, Ziyi Yang, et al · 2024
Closest in time.
Blink: Multimodal large language models can see but not perceive
Xingyu Fu, Yushi Hu, Bangzheng Li, Yu Feng, Haoyu Wang, Xudong Lin, Dan Roth, Noah A Smith, Wei-Chiu Ma, and Ranjay Krishna · 2024
Closest in time.
Mantis: Interleaved multi-image instruction tuning
Dongfu Jiang, Xuan He, Huaye Zeng, Cong Wei, Max Ku, Qian Liu, and Wenhu Chen · 2024
Closest in time.
Many-shot in-context learning in multimodal foundation models
Yixing Jiang, Jeremy Irvin, Ji Hun Wang, Muhammad Ahmed Chaudhry, Jonathan H Chen, and Andrew Y Ng · 2024
Closest in time.
Obelics: 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 Rush, Douwe Kiela, et al · 2024
Closest in time.
What matters when building vision-language models?, 2024
Hugo Laurençon, Léo Tronchon, Matthieu Cord, and Victor Sanh · 2024
Closest in time.
Fine-tuning multimodal llms to follow zero-shot demonstrative instructions
Juncheng Li, Kaihang Pan, Zhiqi Ge, Minghe Gao, Wei Ji, Wenqiao Zhang, Tat-Seng Chua, Siliang Tang, Hanwang Zhang, and Yueting Zhuang · 2024
Closest in time.
Llava-next: Improved reasoning, ocr, and world knowledge, January 2024
Haotian Liu, Chunyuan Li, Yuheng Li, Bo Li, Yuanhan Zhang, Sheng Shen, and Yong Jae Lee · 2024
Closest in time.
Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
Closest in time.
Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, and Jianfeng Gao · 2024
Closest in time.
Unsolvable problem detection: Evaluating trustworthiness of vision language models
Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming, Qing Yu, Go Irie, Yixuan Li, Hai Li, Ziwei Liu, and Kiyoharu Aizawa · 2024
Closest in time.
Chameleon: Mixed-modal early-fusion foundation models
Chameleon Team · 2024
Closest in time.
Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Gedas Bertasius, Mohit Bansal, et al · 2024
Closest in time.
Kaining Ying, Fanqing Meng, Jin Wang, Zhiqian Li, Han Lin, Yue Yang, Hao Zhang, Wenbo Zhang, Yuqi Lin, Shuo Liu, et al · 2024
Closest in time.
Llama-adapter: Efficient fine-tuning of language models with zero-init attention
Renrui Zhang, Jiaming Han, Aojun Zhou, Xiangfei Hu, Shilin Yan, Pan Lu, Hongsheng Li, Peng Gao, and Yu Qiao · 2024
Closest in time.
Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems?
Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Peng Gao, and Hongsheng Li · 2024
Closest in time.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2024
Closest in time.
Multimodal c4: An open, billion-scale corpus of images interleaved with text
Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, and Yejin Choi · 2024
Closest in time.