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Recent progress in Machine Unlearning (MU) has introduced solutions for the selective removal of private or sensitive information encoded within deep neural networks.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Variational bayesian unlearning
Quoc Phong Nguyen, Bryan Kian Hsiang Low, and Patrick Jaillet. 2020 · 2020
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Machine unlearning
Lucas Bourtoule, Varun Chandrasekaran, Christopher A Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, and Nicolas Papernot. 2021 · 2021
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Multimodal neurons in artificial neural networks
Gabriel Goh, Nick Cammarata †, Chelsea Voss †, Shan Carter, Michael Petrov, Ludwig Schubert, Alec Radford, and Chris Olah. 2021 · 2021
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Align before fuse: Vision and language representation learning with momentum distillation
Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong, and Steven Chu Hong Hoi. 2021 · 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 · 2021
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Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2022 · 2022
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi. 2022 · 2022
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Continual learning and private unlearning
Bo Liu, Qiang Liu, and Peter Stone. 2022 · 2022
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A survey of machine unlearning
Thanh Tam Nguyen, Thanh Trung Huynh, Zhao Ren, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, and Quoc Viet Hung Nguyen. 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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Unrolling sgd: Understanding factors influencing machine unlearning
Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, and Nicolas Papernot. 2022 · 2022
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Who’s harry potter? approximate unlearning in llms
Ronen Eldan and Mark Russinovich. 2023 · 2023
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Erasing concepts from diffusion models
Rohit Gandikota, Joanna Materzynska, Jaden Fiotto-Kaufman, and David Bau. 2023 · 2023
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OpenAI. 2023 · 2023
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In-context unlearning: Language models as few shot unlearners
Martin Pawelczyk, Seth Neel, and Himabindu Lakkaraju. 2023 · 2023
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Knowledge unlearning for llms: Tasks, methods, and challenges
Nianwen Si, Hao Zhang, Heyu Chang, Wenlin Zhang, Dan Qu, and Weiqiang Zhang. 2023 · 2023
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Kga: A general machine unlearning framework based on knowledge gap alignment
Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, and Hongzhi Yin. 2023 · 2023
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Depn: Detecting and editing privacy neurons in pretrained language models
Xinwei Wu, Junzhuo Li, Minghui Xu, Weilong Dong, Shuangzhi Wu, Chao Bian, and Deyi Xiong. 2023 · 2023
Cited alongside, same era.
Understanding information storage and transfer in multi-modal large language models
Samyadeep Basu, Martin Grayson, Cecily Morrison, Besmira Nushi, Soheil Feizi, and Daniela Massiceti. 2024 · 2024
Cited alongside, same era.
Tofu: A task of fictitious unlearning for llms
Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary C Lipton, and J Zico Kolter. 2024 · 2024
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Mllm-protector: Ensuring mllm’s safety without hurting performance
Renjie Pi, Tianyang Han, Jianshu Zhang, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, and Tong Zhang. 2024 · 2024
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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 · 2024
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Learn while unlearn: An iterative unlearning framework for generative language models
Haoyu Tang, Ye Liu, Xukai Liu, Kai Zhang, Yanghai Zhang, Qi Liu, and Enhong Chen. 2024 · 2024
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Trishna Chakraborty, Erfan Shayegani, Zikui Cai, Nael B. Abu-Ghazaleh, M. Salman Asif, Yue Dong, Amit K. Roy-Chowdhury, and Chengyu Song. 2024 · 2024
Cited alongside, same era.
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, et al. 2024 · 2024
Cited alongside, same era.
Multidelete for multimodal machine unlearning
Jiali Cheng and Hadi Amiri. 2024 · 2024
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Performance gap in entity knowledge extraction across modalities in vision language models
Ido Cohen, Daniela Gottesman, Mor Geva, and Raja Giryes. 2024 · 2024
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Explainable and interpretable multimodal large language models: A comprehensive survey
Yunkai Dang, Kaichen Huang, Jiahao Huo, Yibo Yan, Sirui Huang, Dongrui Liu, Mengxi Gao, Jie Zhang, Chen Qian, Kun Wang, et al. 2024 · 2024
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Clear: Character unlearning in textual and visual modalities
Alexey Dontsov, Dmitrii Korzh, Alexey Zhavoronkin, Boris Mikheev, Denis Bobkov, Aibek Alanov, Oleg Y Rogov, Ivan Oseledets, and Elena Tutubalina. 2024 · 2024
Cited alongside, same era.
Chatglm: A family of large language models from glm-130b to glm-4 all tools
Team GLM, Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Dan Zhang, Diego Rojas, Guanyu Feng, Hanlin Zhao, et al. 2024 · 2024
Cited alongside, same era.
A survey on evaluation of multimodal large language models
Jiaxing Huang and Jingyi Zhang. 2024 · 2024
Cited alongside, same era.
Pratiksha Thaker, Yash Maurya, Shengyuan Hu, Zhiwei Steven Wu, and Virginia Smith. 2024 · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, et al. 2024 · 2024
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Shangyu Xing, Fei Zhao, Zhen Wu, Tuo An, Weihao Chen, Chunhui Li, Jianbing Zhang, and Xinyu Dai. 2024 · 2024
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Georeasoner: Reasoning on geospatially grounded context for natural language understanding
Yibo Yan and Joey Lee. 2024 · 2024
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Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web
Yibo Yan, Haomin Wen, Siru Zhong, Wei Chen, Haodong Chen, Qingsong Wen, Roger Zimmermann, and Yuxuan Liang. 2024c · 2024
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Cliperase: Efficient unlearning of visual-textual associations in clip
Tianyu Yang, Lisen Dai, Zheyuan Liu, Xiangqi Wang, Meng Jiang, Yapeng Tian, and Xiangliang Zhang. 2024 · 2024
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Zeping Yu and Sophia Ananiadou. 2024 · 2024
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Forget-me-not: Learning to forget in text-to-image diffusion models
Eric Zhang, Kai Wang, Xingqian Xu, Zhangyang Wang, and Humphrey Shi. 2023 · 2024
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Negative preference optimization: From catastrophic collapse to effective unlearning
Ruiqi Zhang, Licong Lin, Yu Bai, and Song Mei. 2024 · 2024
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Digital forgetting in large language models: A survey of unlearning methods
Alberto Blanco-Justicia, Najeeb Jebreel, Benet Manzanares-Salor, David Sánchez, Josep Domingo-Ferrer, Guillem Collell, and Kuan Eeik Tan. 2025 · 2025
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Position: Multimodal large language models can significantly advance scientific reasoning
Yibo Yan, Shen Wang, Jiahao Huo, Jingheng Ye, Zhendong Chu, Xuming Hu, Philip S Yu, Carla Gomes, Bart Selman, and Qingsong Wen. 2025 · 2025
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Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
Xingchen Zou, Yibo Yan, Xixuan Hao, Yuehong Hu, Haomin Wen, Erdong Liu, Junbo Zhang, Yong Li, Tianrui Li, Yu Zheng, et al. 2025 · 2025
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