Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks. - Sadegh Mahdavi; Kevin Swersky; Thomas Kipf; Milad Hashemi; Christos Thrampoulidis; Renjie Liao (Trans. Mach. Learn. Res., 2023)

Revisiting the Equivalence of In-Context Learning and Gradient Descent: The Impact of Data Distribution. - Sadegh Mahdavi; Renjie Liao; Christos Thrampoulidis (ICASSP, 2024)

Memorization Capacity of Multi-Head Attention in Transformers. - Sadegh Mahdavi; Renjie Liao; Christos Thrampoulidis (ICLR, 2024)

Leveraging Environment Interaction for Automated PDDL Translation and Planning with Large Language Models. - Sadegh Mahdavi; Raquel Aoki; Keyi Tang; Yanshuai Cao (NeurIPS, 2024)

Leveraging Environment Interaction for Automated PDDL Generation and Planning with Large Language Models. - Sadegh Mahdavi; Raquel Aoki; Keyi Tang; Yanshuai Cao (CoRR, 2024)

From Graph Diffusion to Graph Classification. - Jia Jun Cheng Xian; Sadegh Mahdavi; Renjie Liao; Oliver Schulte (CoRR, 2024)

Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation. - Sadegh Mahdavi; Muchen Li; Kaiwen Liu; Christos Thrampoulidis; Leonid Sigal; Renjie Liao (CoRR, 2025)

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation. - Wei Du; Branislav Kisacanin; George Armstrong; Shubham Toshniwal; Ivan Moshkov; Alexan Ayrapetyan; Sadegh Mahdavi; Dan Zhao; Shizhe Diao; Dragan Masulovic; Marius Stanean; Advaith Avadhanam; et al. (CoRR, 2025)