Fetching the paper…
Reading the bibliography…
Multimodal Large Language Models (MLLMs) still struggle with hallucinations despite their impressive capabilities.
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
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.
Object hallucination in image captioning
Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, Trevor Darrell, and Kate Saenko · 2018
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
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, Gretchen Krueger, and Ilya Sutskever · 2021
Earlier work this paper cites.
Grounded language-image pre-training
Liunian Harold Li, Pengchuan Zhang, Haotian Zhang, Jianwei Yang, Chunyuan Li, Yiwu Zhong, Lijuan Wang, Lu Yuan, Lei Zhang, Jenq-Neng Hwang, et al · 2022
Earlier work this paper cites.
Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan · 2022
Earlier work this paper cites.
Qwen-vl: A frontier large vision-language model with versatile abilities
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
Earlier work this paper cites.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al · 2023
Earlier work this paper cites.
Instructblip: Towards general-purpose vision-language models with instruction tuning
Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven C. H. Hoi · 2023
Earlier work this paper cites.
BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models
Junnan Li, Dongxu Li, Silvio Savarese, and Steven C. H. Hoi · 2023
Earlier work this paper cites.
OpenAI · 2023
Earlier work this paper cites.
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
Cited alongside, same era.
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
Cited alongside, same era.
Image as a foreign language: BEIT pretraining for vision and vision-language tasks
Wenhui Wang, Hangbo Bao, Li Dong, Johan Bjorck, Zhiliang Peng, Qiang Liu, Kriti Aggarwal, Owais Khan Mohammed, Saksham Singhal, Subhojit Som, and Furu Wei · 2023
Cited alongside, same era.
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.
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
Later among the works it cites.
Hallucination augmented contrastive learning for multimodal large language model
Chaoya Jiang, Haiyang Xu, Mengfan Dong, Jiaxing Chen, Wei Ye, Ming Yan, Qinghao Ye, Ji Zhang, Fei Huang, and Shikun Zhang · 2024
Later among the works it cites.
Preventing reward hacking with occupancy measure regularization
Cassidy Laidlaw, Shivam Singhal, and Anca Dragan · 2024
Later among the works it cites.
Llava-next: Improved reasoning, ocr, and world knowledge, January 2024b
Haotian Liu, Chunyuan Li, Yuheng Li, Bo Li, Yuanhan Zhang, Sheng Shen, and Yong Jae Lee · 2024
Later among the works it cites.
Strengthening multimodal large language model with bootstrapped preference optimization
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Reformulating vision-language foundation models and datasets towards universal multimodal assistants
Tianyu Yu, Jinyi Hu, Yuan Yao, Haoye Zhang, Yue Zhao, Chongyi Wang, Shan Wang, Yinxv Pan, Jiao Xue, Dahai Li, et al · 2023
Cited alongside, same era.
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 · 2023
Cited alongside, same era.
Llama 3 model card
AI@Meta · 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
Cited alongside, same era.
Enhancing large vision language models with self-training on image comprehension
Yihe Deng, Pan Lu, Fan Yin, Ziniu Hu, Sheng Shen, James Zou, Kai-Wei Chang, and Wei Wang · 2024
Cited alongside, same era.
Hallusionbench: an advanced diagnostic suite for entangled language hallucination and 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, et al · 2024
Cited alongside, same era.
Detecting and preventing hallucinations in large vision language models
Anisha Gunjal, Jihan Yin, and Erhan Bas · 2024
Cited alongside, same era.
Efficient multimodal learning from data-centric perspective
Muyang He, Yexin Liu, Boya Wu, Jianhao Yuan, Yueze Wang, Tiejun Huang, and Bo Zhao · 2024
Cited alongside, same era.
Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, and Tong Zhang · 2024
Later among the works it cites.
Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
Later among the works it cites.
mdpo: Conditional preference optimization for multimodal large language models
Fei Wang, Wenxuan Zhou, James Y Huang, Nan Xu, Sheng Zhang, Hoifung Poon, and Muhao Chen · 2024
Later among the works it cites.
Minicpm-v: A gpt-4v level mllm on your phone
Yuan Yao, Tianyu Yu, Ao Zhang, Chongyi Wang, Junbo Cui, Hongji Zhu, Tianchi Cai, Haoyu Li, Weilin Zhao, Zhihui He, Qianyu Chen, Huarong Zhou, Zhensheng Zou, Haoye Zhang, Shengding Hu, Zhi Zheng, Jie Zhou, Jie Cai, Xu Han, Guoyang Zeng, Dahai Li, Zhiyuan Liu, and Maosong Sun · 2024
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 · 2024
Later among the works it cites.
Token-level direct preference optimization
Yongcheng Zeng, Guoqing Liu, Weiyu Ma, Ning Yang, Haifeng Zhang, and Jun Wang · 2024
Later among the works it cites.
Reflective instruction tuning: Mitigating hallucinations in large vision-language models
Jinrui Zhang, Teng Wang, Haigang Zhang, Ping Lu, and Feng Zheng · 2024
Later among the works it cites.
Mmbench: Is your multi-modal model an all-around player?
Yuan Liu, Haodong Duan, Yuanhan Zhang, Bo Li, Songyang Zhang, Wangbo Zhao, Yike Yuan, Jiaqi Wang, Conghui He, Ziwei Liu, et al · 2025
Closest in time.