Jin Peng Zhou

According to our database, Jin Peng Zhou authored at least 21 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Leveraging diffusion models for unsupervised out-of-distribution detection on image manifold.

Zhenzhen Liu, Jin Peng Zhou, Kilian Q. Weinberger

Frontiers Artif. Intell., 2024

Gemma 2: Improving Open Language Models at a Practical Size.

Morgane Rivière, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, Johan Ferret, Peter Liu, Pouya Tafti, Abe Friesen, Michelle Casbon, Sabela Ramos, Ravin Kumar, Charline Le Lan, Sammy Jerome, Anton Tsitsulin, Nino Vieillard, Piotr Stanczyk, Sertan Girgin, Nikola Momchev, Matt Hoffman, Shantanu Thakoor, Jean-Bastien Grill, Behnam Neyshabur, Olivier Bachem, Alanna Walton, Aliaksei Severyn, Alicia Parrish, Aliya Ahmad, Allen Hutchison, Alvin Abdagic, Amanda Carl, Amy Shen, Andy Brock, Andy Coenen, Anthony Laforge, Antonia Paterson, Ben Bastian, Bilal Piot, Bo Wu, Brandon Royal, Charlie Chen, Chintu Kumar, Chris Perry, Chris Welty, Christopher A. Choquette-Choo, Danila Sinopalnikov, David Weinberger, Dimple Vijaykumar, Dominika Rogozinska, Dustin Herbison, Elisa Bandy, Emma Wang, Eric Noland, Erica Moreira, Evan Senter, Evgenii Eltyshev, Francesco Visin, Gabriel Rasskin, Gary Wei, Glenn Cameron, Gus Martins, Hadi Hashemi, Hanna Klimczak-Plucinska, Harleen Batra, Harsh Dhand, Ivan Nardini, Jacinda Mein, Jack Zhou, James Svensson, Jeff Stanway, Jetha Chan, Jin Peng Zhou, Joana Carrasqueira, Joana Iljazi, Jocelyn Becker, Joe Fernandez, Joost van Amersfoort, Josh Gordon, Josh Lipschultz, Josh Newlan, Ju-yeong Ji, Kareem Mohamed, Kartikeya Badola, Kat Black, Katie Millican, Keelin McDonell, Kelvin Nguyen, Kiranbir Sodhia, Kish Greene, Lars Lowe Sjösund, Lauren Usui, Laurent Sifre, Lena Heuermann, Leticia Lago, Lilly McNealus

CoRR, 2024

On Speeding Up Language Model Evaluation.

Jin Peng Zhou, Christian K. Belardi, Ruihan Wu, Travis Zhang, Carla P. Gomes, Wen Sun, Kilian Q. Weinberger

CoRR, 2024

Orchestrating LLMs with Different Personalizations.

Jin Peng Zhou, Katie Z. Luo, Jingwen Gu, Jason Yuan, Kilian Q. Weinberger, Wen Sun

CoRR, 2024

Code Repair with LLMs gives an Exploration-Exploitation Tradeoff.

Hao Tang, Keya Hu, Jin Peng Zhou, Sicheng Zhong, Wei-Long Zheng, Xujie Si, Kevin Ellis

CoRR, 2024

Zero-shot Object-Level OOD Detection with Context-Aware Inpainting.

Quang-Huy Nguyen, Jin Peng Zhou, Zhenzhen Liu, Khanh-Huyen Bui, Kilian Q. Weinberger, Dung D. Le

CoRR, 2024

REFACTOR: Learning to Extract Theorems from Proofs.

Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger Baker Grosse

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization.

Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Magnushammer: A Transformer-Based Approach to Premise Selection.

Maciej Mikula, Szymon Tworkowski, Szymon Antoniak, Bartosz Piotrowski, Albert Q. Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Correction with Backtracking Reduces Hallucination in Summarization.

Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Peng Zhou, Minmin Chen, Kilian Q. Weinberger

CoRR, 2023

Magnushammer: A Transformer-based Approach to Premise Selection.

Maciej Mikula, Szymon Antoniak, Szymon Tworkowski, Albert Qiaochu Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu

CoRR, 2023

Unsupervised Out-of-Distribution Detection with Diffusion Inpainting.

Zhenzhen Liu, Jin Peng Zhou, Yufan Wang, Kilian Q. Weinberger

Proceedings of the International Conference on Machine Learning, 2023

Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs.

Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothée Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Does Label Differential Privacy Prevent Label Inference Attacks?

Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Learned Systems Security.

Roei Schuster, Jin Peng Zhou, Thorsten Eisenhofer, Paul Grubbs, Nicolas Papernot

CoRR, 2022

2021

Bayesian Preference Elicitation with Keyphrase-Item Coembeddings for Interactive Recommendation.

Hojin Yang, Scott Sanner, Ga Wu, Jin Peng Zhou

Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, 2021

2020

Not My Deepfake: Towards Plausible Deniability for Machine-Generated Media.

Baiwu Zhang, Jin Peng Zhou, Ilia Shumailov, Nicolas Papernot

CoRR, 2020

Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering.

Jin Peng Zhou, Ga Wu, Zheda Mai, Scott Sanner

CoRR, 2020

TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations.

Jin Peng Zhou, Zhaoyue Cheng, Felipe Pérez, Maksims Volkovs

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Predicting Twitter Engagement With Deep Language Models.

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

Proceedings of the RecSys Challenge '20: Proceedings of the Recommender Systems Challenge 2020, 2020

2019

Incremental Association Rule Mining Based on Matrix Compression for Edge Computing.

Dongdai Zhou, Meng Ouyang, Zhejun Kuang, Zhen Li, Jin Peng Zhou, Xiaochun Cheng

IEEE Access, 2019