• Super Apriel: One Checkpoint, Many Speeds.
  SLAM Labs: Oleksiy Ostapenko, Raymond Li, Torsten Scholak, Alireza Mousavi-Hosseini, Aman Tiwari, Denis Kocetkov, Joel Lamy Poirier, Kelechi Ogueji, Nanda H Krishna, Rafael Pardinas, Sathwik Tejaswi Madhusudhan, Shruthan Radhakrishna, Srinivas Sunkara, Valerie Becaert.
  arXiv 2026.

Publications

• Post-Training with Policy Gradients: Optimality and the Base Model Barrier.
  Alireza Mousavi-Hosseini, Murat A. Erdogdu.
  To appear in ICML 2026, International Conference on Machine Learning. (Spotlight)

• Flow Matching with Semidiscrete Couplings.
  Alireza Mousavi-Hosseini*, Stephen Y. Zhang*, Michal Klein, Marco Cuturi.
  ICLR 2026, International Conference on Learning Representations.

• On Fitting Flow Models with Large Sinkhorn Couplings.
  Stephen Y. Zhang*, Alireza Mousavi-Hosseini*, Michal Klein, Marco Cuturi.
  TMLR 2026, Transactions on Machine Learning Research.
  Journal to Conference Presentation at NeurIPS 2026.

• When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective.
  Alireza Mousavi-Hosseini, Clayton Sanford, Denny Wu, Murat A. Erdogdu.
  NeurIPS 2025, Advances in Neural Information Processing Systems.
  Oral Presentation, ICML workshop on High-Dimensional Learning Dynamics, 2025.

• From Information to Generative Exponent: Learning Rate Induces Phase Transitions in SGD
  KC Tsiolis, Alireza Mousavi-Hosseini, Murat A. Erdogdu.
  NeurIPS 2025, Advances in Neural Information Processing Systems.
  

• Robust Feature Learning for Multi-Index Models in High Dimensions.
  Alireza Mousavi-Hosseini, Adel Javanmard, Murat A. Erdogdu.
  ICLR 2025, International Conference on Learning Representations.

• Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics.
  Alireza Mousavi-Hosseini, Denny Wu, Murat A. Erdogdu.
  ICLR 2025, International Conference on Learning Representations.

• Mean-Field Langevin Dynamics for Signed Measures via a Bilevel Approach.
  Guillaume Wang*, Alireza Mousavi-Hosseini*, Lénaïc Chizat.
  NeurIPS 2024, Advances in Neural Information Processing Systems. (Spotlight)

• A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers.
  Ye He, Alireza Mousavi-Hosseini, Krishnakumar Balasubramanian, Murat A. Erdogdu.
  NeurIPS 2024, Advances in Neural Information Processing Systems.

• Gradient-Based Feature Learning under Structured Data.
  Alireza Mousavi-Hosseini, Denny Wu, Taiji Suzuki, Murat A. Erdogdu.
  NeurIPS 2023, Advances in Neural Information Processing Systems.

• Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality.
  Alireza Mousavi-Hosseini*, Tyler Farghly*, Ye He, Krishnakumar Balasubramanian, Murat A. Erdogdu.
  COLT 2023, Annual Conference on Learning Theory.

• Neural Networks Efficiently Learn Low-Dimensional Representations with SGD.
  Alireza Mousavi-Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A. Erdogdu.
  ICLR 2023, International Conference on Learning Representations. (Spotlight)

* Equal Contributions