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Jin Peng Zhou
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2020 – today
- 2024
- [i11]Quang-Huy Nguyen, Jin Peng Zhou, Zhenzhen Liu, Khanh-Huyen Bui, Kilian Q. Weinberger, Dung D. Le:
Zero-shot Object-Level OOD Detection with Context-Aware Inpainting. CoRR abs/2402.03292 (2024) - [i10]Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger B. Grosse:
REFACTOR: Learning to Extract Theorems from Proofs. CoRR abs/2402.17032 (2024) - [i9]Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu:
Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization. CoRR abs/2403.18120 (2024) - 2023
- [c6]Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo:
Does Label Differential Privacy Prevent Label Inference Attacks? AISTATS 2023: 4336-4347 - [c5]Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothée Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu:
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. ICLR 2023 - [c4]Zhenzhen Liu, Jin Peng Zhou, Yufan Wang, Kilian Q. Weinberger:
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting. ICML 2023: 22528-22538 - [i8]Zhenzhen Liu, Jin Peng Zhou, Yufan Wang, Kilian Q. Weinberger:
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting. CoRR abs/2302.10326 (2023) - [i7]Maciej Mikula, Szymon Antoniak, Szymon Tworkowski, Albert Qiaochu Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu:
Magnushammer: A Transformer-based Approach to Premise Selection. CoRR abs/2303.04488 (2023) - [i6]Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Peng Zhou, Minmin Chen, Kilian Q. Weinberger:
Correction with Backtracking Reduces Hallucination in Summarization. CoRR abs/2310.16176 (2023) - 2022
- [i5]Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo:
Does Label Differential Privacy Prevent Label Inference Attacks? CoRR abs/2202.12968 (2022) - [i4]Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, Wenda Li, Jiacheng Liu, Mateja Jamnik, Timothée Lacroix, Yuhuai Wu, Guillaume Lample:
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. CoRR abs/2210.12283 (2022) - [i3]Roei Schuster, Jin Peng Zhou, Thorsten Eisenhofer, Paul Grubbs, Nicolas Papernot:
Learned Systems Security. CoRR abs/2212.10318 (2022) - 2021
- [c3]Hojin Yang, Scott Sanner, Ga Wu, Jin Peng Zhou:
Bayesian Preference Elicitation with Keyphrase-Item Coembeddings for Interactive Recommendation. UMAP 2021: 55-64 - 2020
- [c2]Maksims Volkovs, Zhaoyue Cheng, Mathieu Ravaut, Hojin Yang, Kevin Shen, Jin Peng Zhou, Anson Wong, Saba Zuberi, Ivan Zhang, Nick Frosst, Helen Ngo, Carol Chen, Bharat Venkitesh, Stephen Gou, Aidan N. Gomez:
Predicting Twitter Engagement With Deep Language Models. RecSys Challenge 2020: 38-43 - [c1]Jin Peng Zhou, Zhaoyue Cheng, Felipe Pérez, Maksims Volkovs:
TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations. RecSys 2020: 338-347 - [i2]Jin Peng Zhou, Ga Wu, Zheda Mai, Scott Sanner:
Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering. CoRR abs/2008.01246 (2020) - [i1]Baiwu Zhang, Jin Peng Zhou, Ilia Shumailov, Nicolas Papernot:
Not My Deepfake: Towards Plausible Deniability for Machine-Generated Media. CoRR abs/2008.09194 (2020)
2010 – 2019
- 2019
- [j1]Dongdai Zhou, Meng Ouyang, Zhejun Kuang, Zhen Li, Jin Peng Zhou, Xiaochun Cheng:
Incremental Association Rule Mining Based on Matrix Compression for Edge Computing. IEEE Access 7: 173044-173053 (2019)
Coauthor Index
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