Subspace Learning for Feature Selection via Rank Revealing QR Factorization: Unsupervised and Hybrid Approaches with Non-negative Matrix Factorization and Evolutionary Algorithm. - Amir Moslemi; Arash Ahmadian (CoRR, 2022)

Pseudo-Inverted Bottleneck Convolution for Darts Search Space. - Arash Ahmadian; Louis S. P. Liu; Yue Fei; Konstantinos N. Plataniotis; Mahdi S. Hosseini (ICASSP, 2023)

Intriguing Properties of Quantization at Scale. - Arash Ahmadian; Saurabh Dash; Hongyu Chen 008; Bharat Venkitesh; Stephen Zhen Gou; Phil Blunsom; Ahmet Üstün; Sara Hooker (NeurIPS, 2023)

Intriguing Properties of Quantization at Scale. - Arash Ahmadian; Saurabh Dash; Hongyu Chen 008; Bharat Venkitesh; Stephen Gou; Phil Blunsom; Ahmet Üstün; Sara Hooker (CoRR, 2023)

λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces. - Claas Voelcker; Arash Ahmadian; Romina Abachi; Igor Gilitschenski; Amir-massoud Farahmand (CoRR, 2023)

Subspace learning using structure learning and non-convex regularization: Hybrid technique with mushroom reproduction optimization in gene selection. - Amir Moslemi; Mahdi Bidar; Arash Ahmadian (Comput. Biol. Medicine, 2023)

Dual regularized subspace learning using adaptive graph learning and rank constraint: Unsupervised feature selection on gene expression microarray datasets. - Amir Moslemi; Arash Ahmadian (Comput. Biol. Medicine, 2023)

Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs. - Arash Ahmadian; Chris Cremer; Matthias Gallé; Marzieh Fadaee; Julia Kreutzer; Olivier Pietquin; Ahmet Üstün; Sara Hooker (ACL (1), 2024)

The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm. - Aakanksha; Arash Ahmadian; Beyza Ermis; Seraphina Goldfarb-Tarrant; Julia Kreutzer; Marzieh Fadaee; Sara Hooker (EMNLP, 2024)

RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs. - John Dang; Arash Ahmadian; Kelly Marchisio; Julia Kreutzer; Ahmet Üstün; Sara Hooker (EMNLP, 2024)

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. - Yannis Flet-Berliac; Nathan Grinsztajn; Florian Strub; Eugene Choi; Bill Wu; Chris Cremer; Arash Ahmadian; Yash Chandak; Mohammad Gheshlaghi Azar; Olivier Pietquin; Matthieu Geist (EMNLP, 2024)

Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning. - Ted Zadouri; Ahmet Üstün; Arash Ahmadian; Beyza Ermis; Acyr Locatelli; Sara Hooker (ICLR, 2024)

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. - Yannis Flet-Berliac; Nathan Grinsztajn; Florian Strub; Eugene Choi; Chris Cremer; Arash Ahmadian; Yash Chandak; Mohammad Gheshlaghi Azar; Olivier Pietquin; Matthieu Geist (CoRR, 2024)

Averaging log-likelihoods in direct alignment. - Nathan Grinsztajn; Yannis Flet-Berliac; Mohammad Gheshlaghi Azar; Florian Strub; Bill Wu; Eugene Choi; Chris Cremer; Arash Ahmadian; Yash Chandak; Olivier Pietquin; Matthieu Geist (CoRR, 2024)

Mix Data or Merge Models? Optimizing for Diverse Multi-Task Learning. - Aakanksha; Arash Ahmadian; Seraphina Goldfarb-Tarrant; Beyza Ermis; Marzieh Fadaee; Sara Hooker (CoRR, 2024)

If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs. - Muhammad Khalifa; Yi Chern Tan; Arash Ahmadian; Tom Hosking; Honglak Lee; Lu Wang 008; Ahmet Üstün; Tom Sherborne; Matthias Gallé (CoRR, 2024)

Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier. - John Dang; Shivalika Singh; Daniel D'souza; Arash Ahmadian; Alejandro Salamanca; Madeline Smith; Aidan Peppin; Sungjin Hong; Manoj Govindassamy; Terrence Zhao; Sandra Kublik; Meor Amer; et al. (CoRR, 2024)

Subspace learning for feature selection via rank revealing QR factorization: Fast feature selection. - Amir Moslemi; Arash Ahmadian (Expert Syst. Appl., 2024)

Self-Improving Robust Preference Optimization. - Eugene Choi; Arash Ahmadian; Matthieu Geist; Olivier Pietquin; Mohammad Gheshlaghi Azar (ICLR, 2025)

Command A: An Enterprise-Ready Large Language Model. - Aakanksha; Arash Ahmadian; Marwan Ahmed; Jay Alammar; Milad Alizadeh; Yazeed Alnumay; Sophia Althammer; Arkady Arkhangorodsky; Viraat Aryabumi; Dennis Aumiller; Raphaël Avalos; Zahara Aviv; et al. (CoRR, 2025)

Aya Vision: Advancing the Frontier of Multilingual Multimodality. - Saurabh Dash; Yiyang Nan; John Dang; Arash Ahmadian; Shivalika Singh; Madeline Smith; Bharat Venkitesh; Vlad Shmyhlo; Viraat Aryabumi; Walter Beller-Morales; Jeremy Pekmez; Jason Ozuzu; et al. (CoRR, 2025)

Calibrated Value-Aware Model Learning with Stochastic Environment Models. - Claas Voelcker; Anastasiia Pedan; Arash Ahmadian; Romina Abachi; Igor Gilitschenski; Amir-massoud Farahmand (CoRR, 2025)

Programming by Backprop: LLMs Acquire Reusable Algorithmic Abstractions During Code Training. - Jonathan Cook 004; Silvia Sapora; Arash Ahmadian; Akbir Khan; Tim Rocktäschel; Jakob N. Foerster; Laura Ruis (CoRR, 2025)