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Generative AI technologies have been deployed in many places, such as (multimodal) large language models and vision generative models.
Harry Potter [book series]
JK Rowling. 1997 · 1997
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Continual learning with deep generative replay
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Attention is all you need
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Bert: Pre-training of deep bidirectional transformers for language understanding
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
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The california consumer privacy act: Towards a european-style privacy regime in the united states
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General data protection regulation (GDPR)
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Object hallucination in image captioning
Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, Trevor Darrell, and Kate Saenko. 2018 · 2018
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2018 · 2018
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Personalizing dialogue agents: I have a dog, do you have pets too?
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018 · 2018
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Mathqa: Towards interpretable math word problem solving with operation-based formalisms
Aida Amini, Saadia Gabriel, Peter Lin, Rik Koncel-Kedziorski, Yejin Choi, and Hannaneh Hajishirzi. 2019 · 2019
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Nudenet: Neural nets for nudity classification, detection and selective censoring
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Nuanced metrics for measuring unintended bias with real data for text classification. In WWW
Daniel Borkan, Lucas Dixon, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. 2019 · 2019
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Lifelong anomaly detection through unlearning. In CCS
Min Du, Zhi Chen, Chang Liu, Rajvardhan Oak, and Dawn Song. 2019 · 2019
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Making ai forget you: Data deletion in machine learning
Antonio Ginart, Melody Guan, Gregory Valiant, and James Y Zou. 2019 · 2019
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SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization. In Proceedings of the 2nd Workshop on New Frontiers in Summarization
Bogdan Gliwa, Iwona Mochol, Maciej Biesek, and Aleksander Wawer. 2019 · 2019
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Certified data removal from machine learning models
Chuan Guo, Tom Goldstein, Awni Hannun, and Laurens Van Der Maaten. 2019 · 2019
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The European Union general data protection regulation: what it is and what it means
Chris Jay Hoofnagle, Bart Van Der Sloot, and Frederik Zuiderveen Borgesius. 2019 · 2019
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Parameter-efficient transfer learning for NLP. In ICML
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
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California consumer privacy act
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Controllable text-to-image generation. In Neurips
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, and Philip Torr. 2019 · 2019
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The emergence of deepfake technology: A review
Mika Westerlund. 2019 · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Piqa: Reasoning about physical commonsense in natural language. In AAAI
Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
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Linear mode connectivity and the lottery ticket hypothesis. In ICML
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel Roy, and Michael Carbin. 2020 · 2020
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The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy. 2020 · 2020
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
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StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2020 · 2020
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CrowS-pairs: A challenge dataset for measuring social biases in masked language models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R Bowman. 2020 · 2020
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Variational bayesian unlearning
Quoc Phong Nguyen, Bryan Kian Hsiang Low, and Patrick Jaillet. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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LEDGAR: A large-scale multi-label corpus for text classification of legal provisions in contracts. In LREC
Don Tuggener, Pius Von Däniken, Thomas Peetz, and Mark Cieliebak. 2020 · 2020
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On the dangers of stochastic parrots: Can language models be too big?. In FAccT
Emily M Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
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Machine unlearning. In IEEE Symposium on Security and Privacy (SP)
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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Right to be forgotten in the age of machine learning. In Advances in Digital Science: ICADS 2021
Quang-Vinh Dang. 2021 · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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Deduplicating training data makes language models better
Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, and Nicholas Carlini. 2021 · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2021 · 2021
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Gender and representation bias in GPT-3 generated stories. In Proceedings of the third workshop on narrative understanding
Li Lucy and David Bamman. 2021 · 2021
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Merging models with fisher-weighted averaging, 2021
Michael Matena and Colin Raffel. [n. d.] · 2021
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Hatexplain: A benchmark dataset for explainable hate speech detection. In AAAI
Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann, Pawan Goyal, and Animesh Mukherjee. 2021 · 2021
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Learning transferable visual models from natural language supervision. In ICML
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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Machine unlearning of features and labels
Alexander Warnecke, Lukas Pirch, Christian Wressnegger, and Konrad Rieck. 2021 · 2021
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Do prompt-based models really understand the meaning of their prompts?
Albert Webson and Ellie Pavlick. 2021 · 2021
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Git re-basin: Merging models modulo permutation symmetries
Samuel K Ainsworth, Jonathan Hayase, and Siddhartha Srinivasa. 2022 · 2022
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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Efficient model updates for approximate unlearning of graph-structured data. In ICLR
Eli Chien, Chao Pan, and Olgica Milenkovic. 2022 · 2022
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Preserving patient privacy during computation over shared electronic health record data
Olivia G d’Aliberti and Mark A Clark. 2022 · 2022
Cited alongside, same era.
An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or. 2022 · 2022
Cited alongside, same era.
Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned
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. 2023b · 2023
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Jailbreaking gpt-4v via self-adversarial attacks with system prompts
Yuanwei Wu, Xiang Li, Yixin Liu, Pan Zhou, and Lichao Sun. 2023a · 2023
Later among the works it cites.
Machine Unlearning: A Survey
Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou, and Philip S. Yu. 2023 · 2023
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Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, et al · 2022
Cited alongside, same era.
Transformer feed-forward layers build predictions by promoting concepts in the vocabulary space
Mor Geva, Avi Caciularu, Kevin Ro Wang, and Yoav Goldberg. 2022 · 2022
Cited alongside, same era.
Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2022a · 2022
Cited alongside, same era.
Patching open-vocabulary models by interpolating weights
Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, and Ludwig Schmidt. 2022b · 2022
Cited alongside, same era.
Knowledge unlearning for mitigating privacy risks in language models
Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, and Minjoon Seo. 2022 · 2022
Cited alongside, same era.
Dataless knowledge fusion by merging weights of language models
Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, and Pengxiang Cheng. 2022 · 2022
Cited alongside, same era.
Privacy adhering machine un-learning in nlp
Vinayshekhar Bannihatti Kumar, Rashmi Gangadharaiah, and Dan Roth. 2022 · 2022
Cited alongside, same era.
Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin A Raffel. 2022c · 2022
Cited alongside, same era.
Yuanshun Yao, Xiaojun Xu, and Yang Liu. 2023 · 2023
Later among the works it cites.
Tianyu Yu, Yuan Yao, Haoye Zhang, Taiwen He, Yifeng Han, Ganqu Cui, Jinyi Hu, Zhiyuan Liu, Hai-Tao Zheng, Maosong Sun, et al · 2023
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Right to be forgotten in the era of large language models: Implications, challenges, and solutions
Dawen Zhang, Pamela Finckenberg-Broman, Thong Hoang, Shidong Pan, Zhenchang Xing, Mark Staples, and Xiwei Xu. 2023a · 2023
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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. 2023c · 2023
Later among the works it cites.
Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, and Sijia Liu. 2023b · 2023
Later among the works it cites.
Learning and forgetting unsafe examples in large language models
Jiachen Zhao, Zhun Deng, David Madras, James Zou, and Mengye Ren. 2023a · 2023
Later among the works it cites.
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
Later among the works it cites.
Making harmful behaviors unlearnable for large language models
Xin Zhou, Yi Lu, Ruotian Ma, Tao Gui, Qi Zhang, and Xuanjing Huang. 2023 · 2023
Later among the works it cites.
Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
Maksym Andriushchenko, Francesco Croce, and Nicolas Flammarion. 2024 · 2024
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Digital Forgetting in Large Language Models: A Survey of Unlearning Methods
Alberto Blanco-Justicia, Najeeb Jebreel, Benet Manzanares, David Sánchez, Josep Domingo-Ferrer, Guillem Collell, and Kuan Eeik Tan. 2024 · 2024
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Evaluating the ripple effects of knowledge editing in language models
Roi Cohen, Eden Biran, Ori Yoran, Amir Globerson, and Mor Geva. 2024 · 2024
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Larimar: Large Language Models with Episodic Memory Control
Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarath Swaminathan, Sihui Dai, Aurélie Lozano, Georgios Kollias, Vijil Chenthamarakshan, Soham Dan, et al · 2024
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Unmemorization in Large Language Models via Self-Distillation and Deliberate Imagination
Yijiang River Dong, Hongzhou Lin, Mikhail Belkin, Ramon Huerta, and Ivan Vulić. 2024 · 2024
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Avoiding Copyright Infringement via Machine Unlearning
Guangyao Dou, Zheyuan Liu, Qing Lyu, Kaize Ding, and Eric Wong. 2024 · 2024
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Unified concept editing in diffusion models. In WACV
Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzyńska, and David Bau. 2024 · 2024
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Model editing can hurt general abilities of large language models
Jia-Chen Gu, Hao-Xiang Xu, Jun-Yu Ma, Pan Lu, Zhen-Hua Ling, Kai-Wei Chang, and Nanyun Peng. 2024b · 2024
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Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models
Kang Gu, Md Rafi Ur Rashid, Najrin Sultana, and Shagufta Mehnaz. 2024a · 2024
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Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast
Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, and Min Lin. 2024c · 2024
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Selective amnesia: A continual learning approach to forgetting in deep generative models
Alvin Heng and Harold Soh. 2024 · 2024
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Separate the wheat from the chaff: Model deficiency unlearning via parameter-efficient module operation. In AAAI
Xinshuo Hu, Dongfang Li, Baotian Hu, Zihao Zheng, Zhenyu Liu, and Min Zhang. 2024 · 2024
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Offset Unlearning for Large Language Models
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Unlearning Reveals the Influential Training Data of Language Models
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Beavertails: Towards improved safety alignment of llm via a human-preference dataset
Jiaming Ji, Mickel Liu, Josef Dai, Xuehai Pan, Chi Zhang, Ce Bian, Boyuan Chen, Ruiyang Sun, Yizhou Wang, and Yaodong Yang. 2024 · 2024
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Machine Unlearning for Image-to-Image Generative Models
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Pre-trained language models for text generation: A survey
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The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning
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Siyuan Liang, Kuanrong Liu, Jiajun Gong, Jiawei Liang, Yuan Xun, Ee-Chien Chang, and Xiaochun Cao. 2024 · 2024
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2024b · 2024
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Rethinking Machine Unlearning for Large Language Models
Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R Varshney, et al · 2024
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Towards Safer Large Language Models through Machine Unlearning
Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, and Meng Jiang. 2024a · 2024
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Forgetting Private Textual Sequences in Language Models Via Leave-One-Out Ensemble. In ICASSP
Zhe Liu and Ozlem Kalinli. 2024 · 2024
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Threats, attacks, and defenses in machine unlearning: A survey
Ziyao Liu, Huanyi Ye, Chen Chen, and Kwok-Yan Lam. 2024d · 2024
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Eraser: Jailbreaking Defense in Large Language Models via Unlearning Harmful Knowledge
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Eight Methods to Evaluate Robust Unlearning in LLMs
Aengus Lynch, Phillip Guo, Aidan Ewart, Stephen Casper, and Dylan Hadfield-Menell. 2024 · 2024
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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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Feature unlearning for pre-trained gans and vaes. In AAAI
Saemi Moon, Seunghyuk Cho, and Dongwoo Kim. 2024 · 2024
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Jailbreaking attack against multimodal large language model
Zhenxing Niu, Haodong Ren, Xinbo Gao, Gang Hua, and Rong Jin. 2024 · 2024
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Dissecting Language Models: Machine Unlearning via Selective Pruning
Nicholas Pochinkov and Nandi Schoots. 2024 · 2024
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The Frontier of Data Erasure: Machine Unlearning for Large Language Models
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Copyright Protection in Generative AI: A Technical Perspective
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Addressing cognitive bias in medical language models
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Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning
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Guardrail Baselines for Unlearning in LLMs
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Lingzhi Wang, Xingshan Zeng, Jinsong Guo, Kam-Fai Wong, and Georg Gottlob. 2024c · 2024
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Editing Conceptual Knowledge for Large Language Models
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Yu Wang, Ruihan Wu, Zexue He, Xiusi Chen, and Julian McAuley. 2024b · 2024
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Machine Unlearning for Traditional Models and Large Language Models: A Short Survey
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Machine Unlearning of Pre-trained Large Language Models
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Composing Parameter-Efficient Modules with Arithmetic Operation
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Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning
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UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models
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Judging llm-as-a-judge with mt-bench and chatbot arena
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