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Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities in multimodal task reasoning.
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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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh · 2015
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A comprehensive survey on cross-modal retrieval
Kaiye Wang, Qiyue Yin, Wei Wang, Shu Wu, and Liang Wang · 2016
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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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Dexperts: Decoding-time controlled text generation with experts and anti-experts, 2021
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, and Yejin Choi · 2021
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Learning transferable visual models from natural language supervision, 2021
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Eva: Exploring the limits of masked visual representation learning at scale, 2022
Yuxin Fang, Wen Wang, Binhui Xie, Quan Sun, Ledell Wu, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2022
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Contrastive decoding: Open-ended text generation as optimization
Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, and Mike Lewis · 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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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
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Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
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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
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A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions, 2023
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, and Ting Liu · 2023
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Contrastive decoding improves reasoning in large language models
Sean O’Brien and Mike Lewis · 2023
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A survey of hallucination in large foundation models
Vipula Rawte, Amit Sheth, and Amitava Das · 2023
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Aligning large multimodal models with factually augmented rlhf
Zhiqing Sun, Sheng Shen, Shengcao Cao, Haotian Liu, Chunyuan Li, Yikang Shen, Chuang Gan, Liang-Yan Gui, Yu-Xiong Wang, Yiming Yang, et al · 2023
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An llm-free multi-dimensional benchmark for mllms hallucination evaluation
Junyang Wang, Yuhang Wang, Guohai Xu, Jing Zhang, Yukai Gu, Haitao Jia, Ming Yan, Ji Zhang, and Jitao Sang · 2023
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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
Cited alongside, same era.
Enhancing multimodal large language models with vision detection models: An empirical study
Qirui Jiao, Daoyuan Chen, Yilun Huang, Yaliang Li, and Ying Shen · 2024
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Vacode: Visual augmented contrastive decoding
Sihyeon Kim, Boryeong Cho, Sangmin Bae, Sumyeong Ahn, and Se-Young Yun · 2024
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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 · 2024
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Evaluation and enhancement of semantic grounding in large vision-language models
Jiaying Lu, Jinmeng Rao, Kezhen Chen, Xiaoyuan Guo, Yawen Zhang, Baochen Sun, Carl Yang, and Jie Yang · 2024
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Entropy-based decoding for retrieval-augmented large language models
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Halle-switch: Controlling object hallucination in large vision language models
Bohan Zhai, Shijia Yang, Chenfeng Xu, Sheng Shen, Kurt Keutzer, and Manling Li · 2023
Cited alongside, same era.
Enhancing uncertainty-based hallucination detection with stronger focus
Tianhang Zhang, Lin Qiu, Qipeng Guo, Cheng Deng, Yue Zhang, Zheng Zhang, Chenghu Zhou, Xinbing Wang, and Luoyi Fu · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Dola: Decoding by contrasting layers improves factuality in large language models, 2024
Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James Glass, and Pengcheng He · 2024
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Seeing is believing: Mitigating hallucination in large vision-language models via clip-guided decoding, 2024
Ailin Deng, Zhirui Chen, and Bryan Hooi · 2024
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Mme: A comprehensive evaluation benchmark for multimodal large language models, 2024
Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Jinrui Yang, Xiawu Zheng, Ke Li, Xing Sun, Yunsheng Wu, and Rongrong Ji · 2024
Cited alongside, same era.
Incorporating visual experts to resolve the information loss in multimodal large language models
Xin He, Longhui Wei, Lingxi Xie, and Qi Tian · 2024
Cited alongside, same era.
Opera: Alleviating hallucination in multi-modal large language models via over-trust penalty and retrospection-allocation
Qidong Huang, Xiaoyi Dong, Pan Zhang, Bin Wang, Conghui He, Jiaqi Wang, Dahua Lin, Weiming Zhang, and Nenghai Yu · 2024
Cited alongside, same era.
Zexuan Qiu, Zijing Ou, Bin Wu, Jingjing Li, Aiwei Liu, and Irwin King · 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
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Ritual: Random image transformations as a universal anti-hallucination lever in lvlms
Sangmin Woo, Jaehyuk Jang, Donguk Kim, Yubin Choi, and Changick Kim · 2024
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Logical closed loop: Uncovering object hallucinations in large vision-language models
Junfei Wu, Qiang Liu, Ding Wang, Jinghao Zhang, Shu Wu, Liang Wang, and Tieniu Tan · 2024
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V?: Guided visual search as a core mechanism in multimodal llms
Penghao Wu and Saining Xie · 2024
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Debiasing large visual language models
Yi-Fan Zhang, Weichen Yu, Qingsong Wen, Xue Wang, Zhang Zhang, Liang Wang, Rong Jin, and Tieniu Tan · 2024
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Enhancing contextual understanding in large language models through contrastive decoding
Zheng Zhao, Emilio Monti, Jens Lehmann, and Haytham Assem · 2024
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Ibd: Alleviating hallucinations in large vision-language models via image-biased decoding, 2024
Lanyun Zhu, Deyi Ji, Tianrun Chen, Peng Xu, Jieping Ye, and Jun Liu · 2024
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Jiaming Li, Jiacheng Zhang, Zequn Jie, Lin Ma, and Guanbin Li · 2025
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