Soroush Tabesh

According to our database, Soroush Tabesh authored at least 9 papers between 2023 and 2025.

Collaborative distances:

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

2025

Quartet: Native FP4 Training Can Be Optimal for Large Language Models.

Roberto L. Castro, Andrei Panferov, Soroush Tabesh, Oliver Sieberling, Jiale Chen, Mahdi Nikdan, Saleh Ashkboos, Dan Alistarh

CoRR, May, 2025

ASIDE: Architectural Separation of Instructions and Data in Language Models.

Egor Zverev, Evgenii Kortukov, Alexander Panfilov, Soroush Tabesh, Alexandra Volkova, Sebastian Lapuschkin, Wojciech Samek, Christoph H. Lampert

CoRR, March, 2025

QuEST: Stable Training of LLMs with 1-Bit Weights and Activations.

Andrei Panferov, Jiale Chen, Soroush Tabesh, Roberto L. Castro, Mahdi Nikdan, Dan Alistarh

CoRR, February, 2025

HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs.

Saleh Ashkboos, Mahdi Nikdan, Soroush Tabesh, Roberto L. Castro, Torsten Hoefler, Dan Alistarh

CoRR, January, 2025

TACO Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression.

Denis Kuznedelev, Soroush Tabesh, Kimia Noorbakhsh, Elias Frantar, Sara Beery, Eldar Kurtic, Dan Alistarh

Trans. Mach. Learn. Res., 2025

Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?

Egor Zverev, Sahar Abdelnabi, Soroush Tabesh, Mario Fritz, Christoph H. Lampert

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation.

Mahdi Nikdan, Soroush Tabesh, Dan Alistarh

CoRR, 2024

RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation.

Mahdi Nikdan, Soroush Tabesh, Elvir Crncevic, Dan Alistarh

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

2023

Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression.

Denis Kuznedelev, Soroush Tabesh, Kimia Noorbakhsh, Elias Frantar, Sara Beery, Eldar Kurtic, Dan Alistarh

CoRR, 2023