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Multimodal large language models (MLLMs) equip pre-trained large-language models (LLMs) with visual capabilities.
Fast r-cnn
Ross Girshick. 2015 · 2015
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Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo. 2021 · 2021
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Visual prompting via image inpainting
Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, and Alexei Efros. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022
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Self-instruct: Aligning language models with self-generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2022 · 2022
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Omni3d: A large benchmark and model for 3d object detection in the wild
Garrick Brazil, Abhinav Kumar, Julian Straub, Nikhila Ravi, Justin Johnson, and Georgia Gkioxari. 2023 · 2023
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Instructdet: Diversifying referring object detection with generalized instructions
Ronghao Dang, Jiangyan Feng, Haodong Zhang, Chongjian Ge, Lin Song, Lijun Gong, Chengju Liu, Qijun Chen, Feng Zhu, Rui Zhao, et al. 2023 · 2023
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A challenger to gpt-4v? early explorations of gemini in visual expertise
Chaoyou Fu, Renrui Zhang, Haojia Lin, Zihan Wang, Timin Gao, Yongdong Luo, Yubo Huang, Zhengye Zhang, Longtian Qiu, Gaoxiang Ye, et al. 2023 · 2023
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Figstep: Jailbreaking large vision-language models via typographic visual prompts
Yichen Gong, Delong Ran, Jinyuan Liu, Conglei Wang, Tianshuo Cong, Anyu Wang, Sisi Duan, and Xiaoyun Wang. 2023 · 2023
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A systematic survey of prompt engineering on vision-language foundation models
Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, and Philip Torr. 2023 · 2023
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Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al. 2023 · 2023
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A practical survey on zero-shot prompt design for in-context learning
Yinheng Li. 2023 · 2023
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Mm-vid: Advancing video understanding with gpt-4v (ision)
Kevin Lin, Faisal Ahmed, Linjie Li, Chung-Ching Lin, Ehsan Azarnasab, Zhengyuan Yang, Jianfeng Wang, Lin Liang, Zicheng Liu, Yumao Lu, et al. 2023 · 2023
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Blackvip: Black-box visual prompting for robust transfer learning
Changdae Oh, Hyeji Hwang, Hee-young Lee, YongTaek Lim, Geunyoung Jung, Jiyoung Jung, Hosik Choi, and Kyungwoo Song. 2023 · 2023
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What does clip know about a red circle? visual prompt engineering for vlms
Aleksandar Shtedritski, Christian Rupprecht, and Andrea Vedaldi. 2023 · 2023
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In-context learning unlocked for diffusion models
Zhendong Wang, Yifan Jiang, Yadong Lu, Pengcheng He, Weizhu Chen, Zhangyang Wang, Mingyuan Zhou, et al. 2023 · 2023
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Few-shot composition learning for image retrieval with prompt tuning
Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li, and Ricardo Henao. 2023 · 2023
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Set-of-mark prompting unleashes extraordinary visual grounding in gpt-4v
Jianwei Yang, Hao Zhang, Feng Li, Xueyan Zou, Chunyuan Li, and Jianfeng Gao. 2023 · 2023
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Multimodal prompt perceiver: Empower adaptiveness generalizability and fidelity for all-in-one image restoration
Yuang Ai, Huaibo Huang, Xiaoqiang Zhou, Jiexiang Wang, and Ran He. 2024 · 2024
Cited alongside, same era.
Hallucination of multimodal large language models: A survey
Zechen Bai, Pichao Wang, Tianjun Xiao, Tong He, Zongbo Han, Zheng Zhang, and Mike Zheng Shou. 2024 · 2024
Cited alongside, same era.
Vip-llava: Making large multimodal models understand arbitrary visual prompts
Mu Cai, Haotian Liu, Siva Karthik Mustikovela, Gregory P Meyer, Yuning Chai, Dennis Park, and Yong Jae Lee. 2024 · 2024
Cited alongside, same era.
Controllable generation with text-to-image diffusion models: A survey
Pu Cao, Feng Zhou, Qing Song, and Lu Yang. 2024 · 2024
Cited alongside, same era.
T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models
Chong Mou, Xintao Wang, Liangbin Xie, Yanze Wu, Jian Zhang, Zhongang Qi, and Ying Shan. 2024 · 2024
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Pivot: Iterative visual prompting elicits actionable knowledge for vlms
Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, et al. 2024 · 2024
Closest in time.
Minheng Ni, Yeli Shen, Lei Zhang, and Wangmeng Zuo. 2024 · 2024
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Auto-encoding morph-tokens for multimodal llm
Kaihang Pan, Siliang Tang, Juncheng Li, Zhaoyu Fan, Wei Chow, Shuicheng Yan, Tat-Seng Chua, Yueting Zhuang, and Hanwang Zhang. 2024 · 2024
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Jang Hyun Cho, Boris Ivanovic, Yulong Cao, Edward Schmerling, Yue Wang, Xinshuo Weng, Boyi Li, Yurong You, Philipp Krähenbühl, Yan Wang, et al. 2024 · 2024
Cited alongside, same era.
Cityllava: Efficient fine-tuning for vlms in city scenario
Zhizhao Duan, Hao Cheng, Duo Xu, Xi Wu, Xiangxie Zhang, Xi Ye, and Zhen Xie. 2024 · 2024
Cited alongside, same era.
Multi-modal hallucination control by visual information grounding
Alessandro Favero, Luca Zancato, Matthew Trager, Siddharth Choudhary, Pramuditha Perera, Alessandro Achille, Ashwin Swaminathan, and Stefano Soatto. 2024 · 2024
Cited alongside, same era.
Aim: Let any multi-modal large language models embrace efficient in-context learning
Jun Gao, Qian Qiao, Ziqiang Cao, Zili Wang, and Wenjie Li. 2024 · 2024
Cited alongside, same era.
Agent smith: A single image can jailbreak one million multimodal llm agents exponentially fast
Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, and Min Lin. 2024 · 2024
Cited alongside, same era.
Xixuan Hao, Wei Chen, Yibo Yan, Siru Zhong, Kun Wang, Qingsong Wen, and Yuxuan Liang. 2024 · 2024
Cited alongside, same era.
Multi-modal instruction tuned llms with fine-grained visual perception
Junwen He, Yifan Wang, Lijun Wang, Huchuan Lu, Jun-Yan He, Jin-Peng Lan, Bin Luo, and Xuansong Xie. 2024 · 2024
Cited alongside, same era.
Visual prompting for generalized few-shot segmentation: A multi-scale approach
Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal, and James J Little. 2024 · 2024
Cited alongside, same era.
Leigang Qu, Haochuan Li, Tan Wang, Wenjie Wang, Yongqi Li, Liqiang Nie, and Tat-Seng Chua. 2024 · 2024
Closest in time.
Are you copying my prompt? protecting the copyright of vision prompt for vpaas via watermark
Huali Ren, Anli Yan, Chong-zhi Gao, Hongyang Yan, Zhenxin Zhang, and Jin Li. 2024 · 2024
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Learning visual prompts for guiding the attention of vision transformers
Razieh Rezaei, Masoud Jalili Sabet, Jindong Gu, Daniel Rueckert, Philip Torr, and Ashkan Khakzar. 2024 · 2024
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The prompt report: A systematic survey of prompting techniques
Sander Schulhoff, Michael Ilie, Nishant Balepur, Konstantine Kahadze, Amanda Liu, Chenglei Si, Yinheng Li, Aayush Gupta, HyoJung Han, Sevien Schulhoff, et al. 2024 · 2024
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Towards more unified in-context visual understanding
Dianmo Sheng, Dongdong Chen, Zhentao Tan, Qiankun Liu, Qi Chu, Jianmin Bao, Tao Gong, Bin Liu, Shengwei Xu, and Nenghai Yu. 2024 · 2024
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Generative multimodal models are in-context learners
Quan Sun, Yufeng Cui, Xiaosong Zhang, Fan Zhang, Qiying Yu, Yueze Wang, Yongming Rao, Jingjing Liu, Tiejun Huang, and Xinlong Wang. 2024 · 2024
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Towards open-world grasping with large vision-language models
Georgios Tziafas and Hamidreza Kasaei. 2024 · 2024
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Contrastive region guidance: Improving grounding in vision-language models without training
David Wan, Jaemin Cho, Elias Stengel-Eskin, and Mohit Bansal. 2024 · 2024
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Autoad-zero: A training-free framework for zero-shot audio description
Junyu Xie, Tengda Han, Max Bain, Arsha Nagrani, Gül Varol, Weidi Xie, and Andrew Zisserman. 2024 · 2024
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List items one by one: A new data source and learning paradigm for multimodal llms
An Yan, Zhengyuan Yang, Junda Wu, Wanrong Zhu, Jianwei Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Julian McAuley, Jianfeng Gao, et al. 2024 · 2024
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Mm-spubench: Towards better understanding of spurious biases in multimodal llms
Wenqian Ye, Guangtao Zheng, Yunsheng Ma, Xu Cao, Bolin Lai, James M Rehg, and Aidong Zhang. 2024 · 2024
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Jailbreak vision language models via bi-modal adversarial prompt
Zonghao Ying, Aishan Liu, Tianyuan Zhang, Zhengmin Yu, Siyuan Liang, Xianglong Liu, and Dacheng Tao. 2024 · 2024
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Raccoon: Remove, add, and change video content with auto-generated narratives
Jaehong Yoon, Shoubin Yu, and Mohit Bansal. 2024 · 2024
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Wenliang Zhong, Wenyi Wu, Qi Li, Rob Barton, Boxin Du, Shioulin Sam, Karim Bouyarmane, Ismail Tutar, and Junzhou Huang. 2024 · 2024
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