Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models. - Kushal Tirumala; Aram H. Markosyan; Luke Zettlemoyer; Armen Aghajanyan (NeurIPS, 2022)

Tell Your Story: Task-Oriented Dialogs for Interactive Content Creation. - Satwik Kottur; Seungwhan Moon; Aram H. Markosyan; Hardik Shah; Babak Damavandi; Alborz Geramifard (CoRR, 2022)

Identifying and Disentangling Spurious Features in Pretrained Image Representations. - Rafayel Darbinyan; Hrayr Harutyunyan; Aram H. Markosyan; Hrant Khachatrian (CoRR, 2023)

Using Captum to Explain Generative Language Models. - Vivek Miglani; Oliver Aobo Yang; Aram H. Markosyan; Diego Garcia-Olano; Narine Kokhlikyan (CoRR, 2023)

Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. - Mikayel Samvelyan; Sharath Chandra Raparthy; Andrei Lupu; Eric Hambro; Aram H. Markosyan; Manish Bhatt; Yuning Mao; Minqi Jiang; Jack Parker-Holder; Jakob N. Foerster; Tim Rocktäschel; Roberta Raileanu (NeurIPS, 2024)

Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs. - Chris Cummins; Volker Seeker; Jordi Armengol-Estapé; Aram H. Markosyan; Gabriel Synnaeve; Hugh Leather (CoRR, 2024)

Detecting Prefix Bias in LLM-based Reward Models. - Ashwin Kumar; Yuzi He; Aram H. Markosyan; Bobbie Chern; Imanol Arrieta Ibarra (FAccT, 2025)

With Great Backbones Comes Great Adversarial Transferability. - Erik Arakelyan; Karen Hambardzumyan; Davit Papikyan; Pasquale Minervini; Albert Gordo; Isabelle Augenstein; Aram H. Markosyan (CoRR, 2025)

What I cannot execute, I do not understand: Training and Evaluating LLMs on Program Execution Traces. - Jordi Armengol-Estapé; Quentin Carbonneaux; Tianjun Zhang; Aram H. Markosyan; Volker Seeker; Chris Cummins; Melanie Kambadur; Michael F. P. O'Boyle; Sida I. Wang; Gabriel Synnaeve; Hugh James Leather (CoRR, 2025)