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The troubling rise of hallucination presents perhaps the most significant impediment to the advancement of responsible AI.
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 · 2021
Earlier work this paper cites.
Let there be a clock on the beach: Reducing object hallucination in image captioning
Ali Furkan Biten, Lluís Gómez, and Dimosthenis Karatzas. 2022 · 2022
Earlier work this paper cites.
Eu code of conduct against online hate speech: latest evaluation shows slowdown in progress
European Commission. 2022 · 2022
Earlier work this paper cites.
Plausible may not be faithful: Probing object hallucination in vision-language pre-training
Wenliang Dai, Zihan Liu, Ziwei Ji, Dan Su, and Pascale Fung. 2022 · 2022
Earlier work this paper cites.
Instructblip: Towards general-purpose vision-language models with instruction tuning. arxiv 2023
W Dai, J Li, D Li, AMH Tiong, J Zhao, W Wang, B Li, P Fung, and S Hoi. 2023 · 2023
Earlier work this paper cites.
Multimodal-gpt: A vision and language model for dialogue with humans
Tao Gong, Chengqi Lyu, Shilong Zhang, Yudong Wang, Miao Zheng, Qian Zhao, Kuikun Liu, Wenwei Zhang, Ping Luo, and Kai Chen. 2023 · 2023
Earlier work this paper cites.
Hallusionbench: An advanced diagnostic suite for entangled language hallucination & visual illusion in large vision-language models
Tianrui Guan, Fuxiao Liu, Xiyang Wu Ruiqi Xian Zongxia Li, Xiaoyu Liu Xijun Wang, Lichang Chen Furong Huang Yaser Yacoob, and Dinesh Manocha Tianyi Zhou. 2023 · 2023
Earlier work this paper cites.
Detecting and preventing hallucinations in large vision language models
Anisha Gunjal, Jihan Yin, and Erhan Bas. 2023 · 2023
Earlier work this paper cites.
Volcano: Mitigating multimodal hallucination through self-feedback guided revision
Seongyun Lee, Sue Hyun Park, Yongrae Jo, and Minjoon Seo. 2023 · 2023
Earlier work this paper cites.
Mitigating object hallucinations in large vision-language models through visual contrastive decoding
Sicong Leng, Hang Zhang, Guanzheng Chen, Xin Li, Shijian Lu, Chunyan Miao, and Lidong Bing. 2023 · 2023
Cited alongside, same era.
Evaluating object hallucination in large vision-language models
Yifan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Wayne Xin Zhao, and Ji-Rong Wen. 2023 · 2023
Cited alongside, same era.
Ziyi Lin, Chris Liu, Renrui Zhang, Peng Gao, Longtian Qiu, Han Xiao, Han Qiu, Chen Lin, Wenqi Shao, Keqin Chen, Jiaming Han, Siyuan Huang, Yichi Zhang, Xuming He, Hongsheng Li, and Yu Qiao. 2023 · 2023
Cited alongside, same era.
Google shares drop $100 billion after its new ai chatbot makes a mistake
Emily Olson. 2023 · 2023
Cited alongside, same era.
mplug-owl: Modularization empowers large language models with multimodality
Qinghao Ye, Haiyang Xu, Guohai Xu, Jiabo Ye, Ming Yan, Yiyang Zhou, Junyang Wang, Anwen Hu, Pengcheng Shi, Yaya Shi, et al. 2023 · 2023
Later among the works it cites.
Woodpecker: Hallucination correction for multimodal large language models
Shukang Yin, Chaoyou Fu, Sirui Zhao, Tong Xu, Hao Wang, Dianbo Sui, Yunhang Shen, Ke Li, Xing Sun, and Enhong Chen. 2023 · 2023
Later among the works it cites.
Halle-switch: Controlling object hallucination in large vision language models
Bohan Zhai, Shijia Yang, Chenfeng Xu, Sheng Shen, Kurt Keutzer, and Manling Li. 2023 · 2023
Later among the works it cites.
Analyzing and mitigating object hallucination in large vision-language models
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, and Huaxiu Yao. 2023 · 2023
Later among the works it cites.
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Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al. 2023 · 2023
Cited alongside, same era.
Kosmos-2: Grounding multimodal large language models to the world
Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, and Furu Wei. 2023 · 2023
Cited alongside, same era.
The troubling emergence of hallucination in large language models - an extensive definition, quantification, and prescriptive remediations
Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S.M Towhidul Islam Tonmoy, Aman Chadha, Amit Sheth, and Amitava Das. 2023 · 2023
Cited alongside, same era.
Evaluation and analysis of hallucination in large vision-language models
Junyang Wang, Yiyang Zhou, Guohai Xu, Pengcheng Shi, Chenlin Zhao, Haiyang Xu, Qinghao Ye, Ming Yan, Ji Zhang, Jihua Zhu, et al. 2023 · 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. 2023a
Cited in the paper.
Mitigating hallucination in visual language models with visual supervision
Zhiyang Chen, Yousong Zhu, Yufei Zhan, Zhaowen Li, Chaoyang Zhao, Jinqiao Wang, and Ming Tang. 2023b
Cited in the paper.
The rapid rise of generative ai
Ardi Janjeva, Alexander Harris, Sarah Sarah, Alexander Kasprzyk, and Anna Gausen
Cited in the paper.
Aligning large multi-modal model with robust instruction tuning
Fuxiao Liu, Kevin Lin, Linjie Li, Jianfeng Wang, Yaser Yacoob, and Lijuan Wang. 2023a
Cited in the paper.
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny. 2023 · 2023
Later among the works it cites.
The new york times twitter
NewYorkTimes. 2024 · 2024
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Eyes wide shut? exploring the visual shortcomings of multimodal llms
Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, and Saining Xie. 2024 · 2024
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A comprehensive survey of hallucination mitigation techniques in large language models
S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, Anku Rani, Vipula Rawte, Aman Chadha, and Amitava Das. 2024 · 2024
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