Iman Mirzadeh

According to our database, Iman Mirzadeh authored at least 11 papers between 2023 and 2025.

Collaborative distances:

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

2025

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity.

Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, Maxwell Horton, Samy Bengio, Mehrdad Farajtabar

CoRR, June, 2025

GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, Oncel Tuzel, Samy Bengio, Mehrdad Farajtabar

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining.

Jeffrey Li, Mohammadreza Armandpour, Iman Mirzadeh, Sachin Mehta, Vaishaal Shankar, Raviteja Vemulapalli, Samy Bengio, Oncel Tuzel, Mehrdad Farajtabar, Hadi Pouransari, Fartash Faghri

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

SALSA: Soup-based Alignment Learning for Stronger Adaptation in RLHF.

Atoosa Malemir Chegini, Hamid Kazemi, Iman Mirzadeh, Dong Yin, Maxwell Horton, Moin Nabi, Mehrdad Farajtabar, Keivan Alizadeh

CoRR, 2024

Computational Bottlenecks of Training Small-scale Large Language Models.

Saleh Ashkboos, Iman Mirzadeh, Keivan Alizadeh, Mohammad Hossein Sekhavat, Moin Nabi, Mehrdad Farajtabar, Fartash Faghri

CoRR, 2024

Duo-LLM: A Framework for Studying Adaptive Computation in Large Language Models.

Keivan Alizadeh, Iman Mirzadeh, Hooman Shahrokhi, Dmitry Belenko, Frank Sun, Minsik Cho, Mohammad Hossein Sekhavat, Moin Nabi, Mehrdad Farajtabar

CoRR, 2024

Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization.

Mohammad Samragh, Iman Mirzadeh, Keivan Alizadeh-Vahid, Fartash Faghri, Minsik Cho, Moin Nabi, Devang Naik, Mehrdad Farajtabar

CoRR, 2024

OpenELM: An Efficient Language Model Family with Open Training and Inference Framework.

Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, Mohammad Rastegari

CoRR, 2024

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models.

Iman Mirzadeh, Keivan Alizadeh-Vahid, Sachin Mehta, Carlo C. del Mundo, Oncel Tuzel, Golnoosh Samei, Mohammad Rastegari, Mehrdad Farajtabar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

LLM in a flash: Efficient Large Language Model Inference with Limited Memory.

Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko, S. Khatamifard, Minsik Cho, Carlo C. del Mundo, Mohammad Rastegari, Mehrdad Farajtabar

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

LLM in a flash: Efficient Large Language Model Inference with Limited Memory.

Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko, Karen Khatamifard, Minsik Cho, Carlo C. del Mundo, Mohammad Rastegari, Mehrdad Farajtabar

CoRR, 2023