Yotam Alexander

According to our database, Yotam Alexander authored at least 7 papers between 2023 and 2026.

Collaborative distances:

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

2026

Why Does Agentic Safety Fail to Generalize Across Tasks?

Yonatan Slutzky, Yotam Alexander, Tomer Slor, Yoav Nagel, Nadav Cohen

CoRR, May, 2026

Outcome-Based RL Provably Leads Transformers to Reason, but Only With the Right Data.

Yuval Ran-Milo, Yotam Alexander, Shahar Mendel, Nadav Cohen

CoRR, January, 2026

2025

Revisiting Glorot Initialization for Long-Range Linear Recurrences.

Noga Bar, Mariia Seleznova, Yotam Alexander, Gitta Kutyniok, Raja Giryes

CoRR, May, 2025

Do Neural Networks Need Gradient Descent to Generalize? A Theoretical Study.

Yotam Alexander, Yonatan Slutzky, Yuval Ran-Milo, Nadav Cohen

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

2024

The Implicit Bias of Structured State Space Models Can Be Poisoned With Clean Labels.

Yonatan Slutzky, Yotam Alexander, Noam Razin, Nadav Cohen

CoRR, 2024

Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States.

Noam Razin, Yotam Alexander, Edo Cohen-Karlik, Raja Giryes, Amir Globerson, Nadav Cohen

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

2023

What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement.

Yotam Alexander, Nimrod De La Vega, Noam Razin, Nadav Cohen

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