Yu Yang

According to our database, Yu Yang authored at least 31 papers between 2018 and 2025.

Collaborative distances:

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

2025

RedCodeAgent: Automatic Red-teaming Agent against Diverse Code Agents.

Chengquan Guo, Chulin Xie, Yu Yang, Zhaorun Chen, Zinan Lin, Xander Davies, Yarin Gal, Dawn Song, Bo Li

CoRR, October, 2025

AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration.

Andy Zhou, Kevin Wu, Francesco Pinto, Zhaorun Chen, Yi Zeng, Yu Yang, Shuang Yang, Sanmi Koyejo, James Y. Zou, Bo Li

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures.

Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

AIR-BENCH 2024: A Safety Benchmark based on Regulation and Policies Specified Risk Categories.

Yi Zeng, Yu Yang, Andy Zhou, Jeffrey Ziwei Tan, Yuheng Tu, Yifan Mai, Kevin Klyman, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, Bo Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

SecCodePLT: A Unified Platform for Evaluating the Security of Code GenAI.

Yu Yang, Yuzhou Nie, Zhun Wang, Yuheng Tang, Wenbo Guo, Bo Li, Dawn Song

CoRR, 2024

Memory-efficient Training of LLMs with Larger Mini-batches.

Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman

CoRR, 2024

AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies.

Yi Zeng, Yu Yang, Andy Zhou, Jeffrey Ziwei Tan, Yuheng Tu, Yifan Mai, Kevin Klyman, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, Bo Li

CoRR, 2024

AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies.

Yi Zeng, Kevin Klyman, Andy Zhou, Yu Yang, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, Bo Li

CoRR, 2024

SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models.

Yu Yang, Siddhartha Mishra, Jeffrey N. Chiang, Baharan Mirzasoleiman

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings.

Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality.

Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias.

Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Towards Mitigating Spurious Correlations in the Wild: A Benchmark & a more Realistic Dataset.

Siddharth Joshi, Yu Yang, Yihao Xue, Wenhan Yang, Baharan Mirzasoleiman

CoRR, 2023

Eliminating Spurious Correlations from Pre-trained Models via Data Mixing.

Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman

CoRR, 2023

Network Transplanting for the Functionally Modular Architecture.

Quanshi Zhang, Xu Cheng, Xin Wang, Yu Yang, Yingnian Wu

Proceedings of the Pattern Recognition and Computer Vision - 6th Chinese Conference, 2023

Robust Learning with Progressive Data Expansion Against Spurious Correlation.

Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning.

Yu Yang, Besmira Nushi, Hamid Palangi, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023

Towards Sustainable Learning: Coresets for Data-efficient Deep Learning.

Yu Yang, Hao Kang, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023

NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training.

Neha Prakriya, Yu Yang, Baharan Mirzasoleiman, Cho-Jui Hsieh, Jason Cong

Proceedings of the 15th ACM/USENIX Workshop on Hot Topics in Storage and File Systems, 2023

2022

Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks.

Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman

CoRR, 2022

Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack.

Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Not All Poisons are Created Equal: Robust Training against Data Poisoning.

Yu Yang, Tian Yu Liu, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2022

2019

Visual graph mining for graph matching.

Quanshi Zhang, Xuan Song, Yu Yang, Haotian Ma, Ryosuke Shibasaki

Comput. Vis. Image Underst., 2019

A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks.

Lior Deutsch, Erik Nijkamp, Yu Yang

CoRR, 2019

Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract).

Quanshi Zhang, Yu Yang, Ying Nian Wu

CoRR, 2019

Network Transplanting (extended abstract).

Quanshi Zhang, Yu Yang, Qian Yu, Ying Nian Wu

CoRR, 2019

Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks.

Zenan Ling, Haotian Ma, Yu Yang, Robert C. Qiu, Song-Chun Zhu, Quanshi Zhang

CoRR, 2019

Interpreting CNNs via Decision Trees.

Quanshi Zhang, Yu Yang, Haotian Ma, Ying Nian Wu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Unsupervised Learning of Neural Networks to Explain Neural Networks.

Quanshi Zhang, Yu Yang, Yuchen Liu, Ying Nian Wu, Song-Chun Zhu

CoRR, 2018

Network Transplanting.

Quanshi Zhang, Yu Yang, Ying Nian Wu, Song-Chun Zhu

CoRR, 2018

Interpreting CNNs via Decision Trees.

Quanshi Zhang, Yu Yang, Ying Nian Wu, Song-Chun Zhu

CoRR, 2018