Eric Gan

According to our database, Eric Gan authored at least 11 papers between 2023 and 2026.

Collaborative distances:

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

2026

Auditing Sabotage Bench: A Benchmark for Detecting and Fixing Research Sabotage in ML Codebases.

Eric Gan, Aryan Bhatt, Buck Shlegeris, Julian Stastny, Vivek Hebbar

CoRR, April, 2026

Product-Stability: Provable Convergence for Gradient Descent on the Edge of Stability.

Eric Gan

CoRR, April, 2026

2025

DigiData: Training and Evaluating General-Purpose Mobile Control Agents.

Yuxuan Sun, Manchen Wang, Shengyi Qian, William R. Wong, Eric Gan, Pierluca D'Oro, Alejandro Castillejo Munoz, Sneha Silwal, Pedro Matias, Nitin Kamra, Satwik Kottur, Nick Raines, Xuanyi Zhao, Joy Chen, Joseph Greer, Andrea Madotto, Allen Bolourchi, James Valori, Kevin Carlberg, Karl Ridgeway, Joseph Tighe

CoRR, November, 2025

Occam's Razor for SSL: Memory-Efficient Parametric Instance Discrimination.

Eric Gan, Patrik Reizinger, Alice Bizeul, Attila Juhos, Mark Ibrahim, Randall Balestriero, David A. Klindt, Wieland Brendel, Baharan Mirzasoleiman

Trans. Mach. Learn. Res., 2025

2024

Seeing Is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability.

Ziming Liu, Eric Gan, Max Tegmark

Entropy, January, 2024

Make the Most of Your Data: Changing the Training Data Distribution to Improve In-distribution Generalization Performance.

Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman

CoRR, 2024

Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization.

Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Investigating the Benefits of Projection Head for Representation Learning.

Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, 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

Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent.

Lauren Watson, Eric Gan, Mohan Dantam, Baharan Mirzasoleiman, Rik Sarkar

CoRR, 2023

Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression.

Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023