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ORCIDYangsibo Huang
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2020 – today
- 2024
[c14]Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
LabelDP-Pro: Learning with Label Differential Privacy via Projections. ICLR 2024- [c13]Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen:
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation. ICLR 2024 - [c12]Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer:
Detecting Pretraining Data from Large Language Models. ICLR 2024 - [c11]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
Position: A Safe Harbor for AI Evaluation and Red Teaming. ICML 2024 - [c10]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. ICML 2024 - [i31]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang
, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. CoRR abs/2402.05162 (2024) - [i30]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
A Safe Harbor for AI Evaluation and Red Teaming. CoRR abs/2403.04893 (2024) - [i29]Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal:
AI Risk Management Should Incorporate Both Safety and Security. CoRR abs/2405.19524 (2024) - [i28]Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. CoRR abs/2406.14322 (2024) - [i27]Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson:
Fantastic Copyrighted Beasts and How (Not) to Generate Them. CoRR abs/2406.14526 (2024) - [i26]Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal:
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors. CoRR abs/2406.14598 (2024) - [i25]Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang:
Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. CoRR abs/2406.16135 (2024) - [i24]Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson:
Evaluating Copyright Takedown Methods for Language Models. CoRR abs/2406.18664 (2024) - [i23]Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang:
MUSE: Machine Unlearning Six-Way Evaluation for Language Models. CoRR abs/2407.06460 (2024) - [i22]Xindi Wu, Dingli Yu, Yangsibo Huang, Olga Russakovsky, Sanjeev Arora:
ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty. CoRR abs/2408.14339 (2024) - [i21]Shachar Don-Yehiya, Ben Burtenshaw, Ramón Fernandez Astudillo, Cailean Osborne, Mimansa Jaiswal, Tzu-Sheng Kuo, Wenting Zhao, Idan Shenfeld, Andi Peng, Mikhail Yurochkin, Atoosa Kasirzadeh, Yangsibo Huang, Tatsunori Hashimoto, Yacine Jernite, Daniel Vila-Suero, Omri Abend, Jennifer Ding, Sara Hooker, Hannah Rose Kirk, Leshem Choshen:
The Future of Open Human Feedback. CoRR abs/2408.16961 (2024) - [i20]Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang:
Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. CoRR abs/2410.09591 (2024) - [i19]Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar:
On Memorization of Large Language Models in Logical Reasoning. CoRR abs/2410.23123 (2024) - 2023
- [j2]Yangsibo Huang, Chun-Yin Huang, Xiaoxiao Li, Kai Li:
A Dataset Auditing Method for Collaboratively Trained Machine Learning Models. IEEE Trans. Medical Imaging 42(7): 2081-2090 (2023) - [c9]Yangsibo Huang, Samyak Gupta, Zexuan Zhong, Kai Li, Danqi Chen:
Privacy Implications of Retrieval-Based Language Models. EMNLP 2023: 14887-14902 - [c8]Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Sparsity-Preserving Differentially Private Training of Large Embedding Models. NeurIPS 2023 - [i18]Yangsibo Huang, Daogao Liu, Zexuan Zhong, Weijia Shi, Yin Tat Lee:
kNN-Adapter: Efficient Domain Adaptation for Black-Box Language Models. CoRR abs/2302.10879 (2023) - [i17]Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang:
Challenges towards the Next Frontier in Privacy. CoRR abs/2304.06929 (2023) - [i16]Jiaxi Yang, Wenglong Deng, Benlin Liu, Yangsibo Huang, Xiaoxiao Li:
Matching-based Data Valuation for Generative Model. CoRR abs/2304.10701 (2023) - [i15]Yangsibo Huang, Samyak Gupta, Zexuan Zhong, Kai Li, Danqi Chen:
Privacy Implications of Retrieval-Based Language Models. CoRR abs/2305.14888 (2023) - [i14]Yangsibo Huang, Haotian Jiang, Daogao Liu, Mohammad Mahdian, Jieming Mao, Vahab Mirrokni:
Learning across Data Owners with Joint Differential Privacy. CoRR abs/2305.15723 (2023) - [i13]Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen:
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation. CoRR abs/2310.06987 (2023) - [i12]Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer:
Detecting Pretraining Data from Large Language Models. CoRR abs/2310.16789 (2023) - [i11]Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR abs/2311.08357 (2023) - 2022
- [c7]Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao, Kai Li, Danqi Chen:
Recovering Private Text in Federated Learning of Language Models. NeurIPS 2022 - [i10]Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao, Kai Li, Danqi Chen:
Recovering Private Text in Federated Learning of Language Models. CoRR abs/2205.08514 (2022) - 2021
- [c6]Yangsibo Huang, Xiaoxiao Li, Kai Li:
EMA: Auditing Data Removal from Trained Models. MICCAI (5) 2021: 793-803 - [c5]Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora:
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning. NeurIPS 2021: 7232-7241 - [i9]Yangsibo Huang, Xiaoxiao Li, Kai Li:
EMA: Auditing Data Removal from Trained Models. CoRR abs/2109.03675 (2021) - [i8]Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora:
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning. CoRR abs/2112.00059 (2021) - 2020
- [c4]Wei Qiu, Yangsibo Huang, Quanzheng Li:
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks. IEEE BigData 2020: 4715-4723 - [c3]Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, Sanjeev Arora:
TextHide: Tackling Data Privacy for Language Understanding Tasks. EMNLP (Findings) 2020: 1368-1382 - [c2]Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora:
InstaHide: Instance-hiding Schemes for Private Distributed Learning. ICML 2020: 4507-4518 - [i7]Yangsibo Huang, Yushan Su, Sachin Ravi, Zhao Song, Sanjeev Arora, Kai Li:
Privacy-preserving Learning via Deep Net Pruning. CoRR abs/2003.01876 (2020) - [i6]Ziheng Duan, Daniel Montes, Yangsibo Huang, Dufan Wu, Javier M. Romero, Ramon Gilberto Gonzalez, Quanzheng Li:
Deep Learning Based Detection and Localization of Cerebal Aneurysms in Computed Tomography Angiography. CoRR abs/2005.11098 (2020) - [i5]Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora:
InstaHide: Instance-hiding Schemes for Private Distributed Learning. CoRR abs/2010.02772 (2020) - [i4]Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, Sanjeev Arora:
TextHide: Tackling Data Privacy in Language Understanding Tasks. CoRR abs/2010.06053 (2020) - [i3]Xiaoxiao Li, Yangsibo Huang, Binghui Peng, Zhao Song, Kai Li:
MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery. CoRR abs/2010.11463 (2020) - [i2]Wei Qiu, Yangsibo Huang, Quanzheng Li:
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks. CoRR abs/2012.12581 (2020)
2010 – 2019
- 2019
- [j1]Yunze Man, Yangsibo Huang, Junyi Feng, Xi Li, Fei Wu:
Deep Q Learning Driven CT Pancreas Segmentation With Geometry-Aware U-Net. IEEE Trans. Medical Imaging 38(8): 1971-1980 (2019) - [c1]Ryan Neph, Yangsibo Huang, Youming Yang, Ke Sheng:
DeepMCDose: A Deep Learning Method for Efficient Monte Carlo Beamlet Dose Calculation by Predictive Denoising in MR-Guided Radiotherapy. AIRT@MICCAI 2019: 137-145 - [i1]Yunze Man, Yangsibo Huang, Junyi Feng, Xi Li, Fei Wu:
Deep Q Learning Driven CT Pancreas Segmentation with Geometry-Aware U-Net. CoRR abs/1904.09120 (2019)
Coauthor Index
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last updated on 2024-12-01 01:16 CET by the dblp team
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