Nikolaos Tsilivis

According to our database, Nikolaos Tsilivis authored at least 14 papers between 2022 and 2026.

Collaborative distances:

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

2026

Learning to Think from Multiple Thinkers.

Nirmit Joshi, Roey Magen, Nathan Srebro, Nikolaos Tsilivis, Gal Vardi

CoRR, April, 2026

On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds.

Matteo Vilucchio, Nikolaos Tsilivis, Bruno Loureiro, Julia Kempe

Trans. Mach. Learn. Res., 2026

2025

OpenApps: Simulating Environment Variations to Measure UI-Agent Reliability.

Karen Ullrich, Jingtong Su, Claudia Shi, Arjun Subramonian, Amir Bar, Ivan Evtimov, Nikolaos Tsilivis, Randall Balestriero, Julia Kempe, Mark Ibrahim

CoRR, November, 2025

How Reinforcement Learning After Next-Token Prediction Facilitates Learning.

Nikolaos Tsilivis, Eran Malach, Karen Ullrich, Julia Kempe

CoRR, October, 2025

Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks.

Nikolaos Tsilivis, Gal Vardi, Julia Kempe

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

On the Robustness of Neural Collapse and the Neural Collapse of Robustness.

Jingtong Su, Ya Shi Zhang, Nikolaos Tsilivis, Julia Kempe

Trans. Mach. Learn. Res., 2024

Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks.

Yunzhen Feng, Tim G. J. Rudner, Nikolaos Tsilivis, Julia Kempe

Trans. Mach. Learn. Res., 2024

The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains.

Ezra Edelman, Nikolaos Tsilivis, Benjamin L. Edelman, Eran Malach, Surbhi Goel

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

The Price of Implicit Bias in Adversarially Robust Generalization.

Nikolaos Tsilivis, Natalie Frank, Nati Srebro, Julia Kempe

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

2023

Kernels, Data & Physics.

Francesco Cagnetta, Deborah Oliveira, Mahalakshmi Sabanayagam, Nikolaos Tsilivis, Julia Kempe

CoRR, 2023

A Tale of Two Circuits: Grokking as Competition of Sparse and Dense Subnetworks.

William Merrill, Nikolaos Tsilivis, Aman Shukla

CoRR, 2023

2022

Can we achieve robustness from data alone?

Nikolaos Tsilivis, Jingtong Su, Julia Kempe

CoRR, 2022

Extracting Finite Automata from RNNs Using State Merging.

William Merrill, Nikolaos Tsilivis

CoRR, 2022

What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness?

Nikolaos Tsilivis, Julia Kempe

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