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Vision language models (VLMs) have shown strong zero-shot generalization across various tasks, especially when integrated with large language models (LLMs).
Decoding advertisements
Judith Williamson · 1978
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Visual rhetoric in advertising: Text-interpretive, experimental, and reader-response analyses
Edward F McQuarrie and David Glen Mick · 1999
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Modeling the determinants and effects of creativity in advertising
Robert E Smith, Scott B MacKenzie, Xiaojing Yang, Laura M Buchholz, and William K Darley · 2007
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Creativity in advertising: When it works and when it doesn’t
Werner Reinartz and Peter Saffert · 2013
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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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Learning common sense through visual abstraction
Ramakrishna Vedantam, Xiao Lin, Tanmay Batra, C Lawrence Zitnick, and Devi Parikh · 2015
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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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Automatic understanding of image and video advertisements
Zaeem Hussain, Mingda Zhang, Xiaozhong Zhang, Keren Ye, Christopher Thomas, Zuha Agha, Nathan Ong, and Adriana Kovashka · 2017
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Advise: Symbolism and external knowledge for decoding advertisements
Keren Ye and Adriana Kovashka · 2018
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Interpreting the rhetoric of visual advertisements
Keren Ye, Narges Honarvar Nazari, James Hahn, Zaeem Hussain, Mingda Zhang, and Adriana Kovashka · 2019
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From recognition to cognition: Visual commonsense reasoning
Rowan Zellers, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
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Understanding advertisements with bert
Kanika Kalra, Bhargav Kurma, Silpa Vadakkeeveetil Sreelatha, Manasi Patwardhan, and Shirish Karande · 2020
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Mpnet: Masked and permuted pre-training for language understanding
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu · 2020
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Beyond visual semantics: Exploring the role of scene text in image understanding
Arka Ujjal Dey, Suman K Ghosh, Ernest Valveny, and Gaurav Harit · 2021
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Detecting persuasive atypicality by modeling contextual compatibility
Meiqi Guo, Rebecca Hwa, and Adriana Kovashka · 2021
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Affect2mm: Affective analysis of multimedia content using emotion causality
Trisha Mittal, Puneet Mathur, Aniket Bera, and Dinesh Manocha · 2021
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Clipcap: Clip prefix for image captioning
Ron Mokady, Amir Hertz, and Amit H Bermano · 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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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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Breaking shortcuts by masking for robust visual reasoning
Keren Ye, Mingda Zhang, and Adriana Kovashka · 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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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
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Winoground: Probing vision and language models for visio-linguistic compositionality
Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, and Candace Ross · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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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 Hoi · 2023
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Desco: Learning object recognition with rich language descriptions
Liunian Li, Zi-Yi Dou, Nanyun Peng, and Kai-Wei Chang · 2023
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Idealgpt: Iteratively decomposing vision and language reasoning via large language models
Haoxuan You, Rui Sun, Zhecan Wang, Long Chen, Gengyu Wang, Hammad Ayyubi, Kai-Wei Chang, and Shih-Fu Chang · 2023
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When and why vision-language models behave like bags-of-words, and what to do about it?
Mert Yuksekgonul, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, and James Zou · 2023
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Kaiyang Zhou, Jingkang Yang, Chen Change Loy, and Ziwei Liu · 2022
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Learning to prompt for vision-language models
Kaiyang Zhou, Jingkang Yang, Chen Change Loy, and Ziwei Liu · 2022
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Metaclue: Towards comprehensive visual metaphors research
Arjun R Akula, Brendan Driscoll, Pradyumna Narayana, Soravit Changpinyo, Zhiwei Jia, Suyash Damle, Garima Pruthi, Sugato Basu, Leonidas Guibas, William T Freeman, et al · 2023
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A video is worth 4096 tokens: Verbalize story videos to understand them in zero shot
Aanisha Bhattacharya, Yaman K Singla, Balaji Krishnamurthy, Rajiv Ratn Shah, and Changyou Chen · 2023
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Vasr: Visual analogies of situation recognition
Yonatan Bitton, Ron Yosef, Eliyahu Strugo, Dafna Shahaf, Roy Schwartz, and Gabriel Stanovsky · 2023
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Breaking common sense: Whoops! a vision-and-language benchmark of synthetic and compositional images
Nitzan Bitton-Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, and Roy Schwartz · 2023
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Understanding and improving visual prompting: A label-mapping perspective
Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, and Sijia Liu · 2023
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Ge Zheng, Bin Yang, Jiajin Tang, Hong-Yu Zhou, and Sibei Yang · 2023
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Rome: Evaluating pre-trained vision-language models on reasoning beyond visual common sense
Kankan Zhou, Eason Lai, Wei Bin Au Yeong, Kyriakos Mouratidis, and Jing Jiang · 2023
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Don’t buy it! Reassessing the ad understanding abilities of contrastive multimodal models
Anna Bavaresco, Alberto Testoni, and Raquel Fernández · 2024
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Zheng Cai, Maosong Cao, Haojiong Chen, Kai Chen, Keyu Chen, Xin Chen, Xun Chen, Zehui Chen, Zhi Chen, Pei Chu, et al · 2024
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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, Muyan Zhong, Qinglong Zhang, Xizhou Zhu, Lewei Lu, Bin Li, Ping Luo, Tong Lu, Yu Qiao, and Jifeng Dai · 2024
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Faith and fate: Limits of transformers on compositionality
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Enhancing advanced visual reasoning ability of large language models
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Improved baselines with visual instruction tuning
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Chameleon: Plug-and-play compositional reasoning with large language models
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Compositional chain-of-thought prompting for large multimodal models
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Active learning for vision-language models
Bardia Safaei and Vishal M Patel · 2024
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T-sciq: Teaching multimodal chain-of-thought reasoning via large language model signals for science question answering
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MiniGPT-4: Enhancing vision-language understanding with advanced large language models
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