Commonsense mining as knowledge base completion? A study on the impact of novelty. - Stanislaw Jastrzebski; Dzmitry Bahdanau; Seyedarian Hosseini; Michael Noukhovitch; Yoshua Bengio; Jackie Chi Kit Cheung (CoRR, 2018)

Fashion-Gen: The Generative Fashion Dataset and Challenge. - Negar Rostamzadeh; Seyedarian Hosseini; Thomas Boquet; Wojciech Stokowiec; Ying Zhang 033; Christian Jauvin; Chris Pal (CoRR, 2018)

Learning to Understand Goal Specifications by Modelling Reward. - Dzmitry Bahdanau; Felix Hill; Jan Leike; Edward Hughes 001; Seyed Arian Hosseini; Pushmeet Kohli; Edward Grefenstette (ICLR (Poster), 2019)

Ordered Memory. - Yikang Shen; Shawn Tan; Seyed Arian Hosseini; Zhouhan Lin; Alessandro Sordoni; Aaron C. Courville (NeurIPS, 2019)

Understanding by Understanding Not: Modeling Negation in Language Models. - Arian Hosseini; Siva Reddy; Dzmitry Bahdanau; R. Devon Hjelm; Alessandro Sordoni; Aaron C. Courville (NAACL-HLT, 2021)

On the Compositional Generalization Gap of In-Context Learning. - Arian Hosseini; Ankit Vani; Dzmitry Bahdanau; Alessandro Sordoni; Aaron C. Courville (BlackboxNLP@EMNLP, 2022)

Joint Prompt Optimization of Stacked LLMs using Variational Inference. - Alessandro Sordoni; Eric Yuan; Marc-Alexandre Côté; Matheus Pereira; Adam Trischler; Ziang Xiao; Arian Hosseini; Friederike Niedtner; Nicolas Le Roux (NeurIPS, 2023)

Deep Language Networks: Joint Prompt Training of Stacked LLMs using Variational Inference. - Alessandro Sordoni; Xingdi Yuan; Marc-Alexandre Côté; Matheus Pereira; Adam Trischler; Ziang Xiao; Arian Hosseini; Friederike Niedtner; Nicolas Le Roux (CoRR, 2023)

V-STaR: Training Verifiers for Self-Taught Reasoners. - Arian Hosseini; Xingdi Yuan; Nikolay Malkin; Aaron C. Courville; Alessandro Sordoni; Rishabh Agarwal (CoRR, 2024)

The N+ Implementation Details of RLHF with PPO: A Case Study on TL;DR Summarization. - Shengyi Huang; Michael Noukhovitch; Arian Hosseini; Kashif Rasul; Weixun Wang; Lewis Tunstall (CoRR, 2024)

Not All LLM Reasoners Are Created Equal. - Arian Hosseini; Alessandro Sordoni; Daniel Toyama; Aaron C. Courville; Rishabh Agarwal (CoRR, 2024)

Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. - Hritik Bansal; Arian Hosseini; Rishabh Agarwal; Vinh Q. Tran 002; Mehran Kazemi (ICLR, 2025)

Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models. - Michael Noukhovitch; Shengyi Huang; Sophie Xhonneux; Arian Hosseini; Rishabh Agarwal; Aaron C. Courville (ICLR, 2025)

Generative Verifiers: Reward Modeling as Next-Token Prediction. - Lunjun Zhang; Arian Hosseini; Hritik Bansal; Mehran Kazemi; Aviral Kumar; Rishabh Agarwal (ICLR, 2025)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning. - Nishad Singhi; Hritik Bansal; Arian Hosseini; Aditya Grover; Kai-Wei Chang; Marcus Rohrbach; Anna Rohrbach (CoRR, 2025)

Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers. - Kusha Sareen; Morgane M. Moss; Alessandro Sordoni; Rishabh Agarwal; Arian Hosseini (CoRR, 2025)

Multi-Turn Puzzles: Evaluating Interactive Reasoning and Strategic Dialogue in LLMs. - Kartikeya Badola; Jonathan Simon; Arian Hosseini; Sara Marie Mc Carthy; Tsendsuren Munkhdalai; Abhimanyu Goyal; Tomás Kociský; Shyam Upadhyay; Bahare Fatemi; Mehran Kazemi (CoRR, 2025)