Robust Generation of Dynamical Patterns in Human Motion by a Deep Belief Nets. - Sainbayar Sukhbaatar; Takaki Makino; Kazuyuki Aihara; Takashi Chikayama (ACML, 2011)

Auto-pooling: Learning to Improve Invariance of Image Features from Image Sequences - Sainbayar Sukhbaatar; Takaki Makino; Kazuyuki Aihara (ICLR (Workshop Poster), 2013)

End-To-End Memory Networks. - Sainbayar Sukhbaatar; Arthur Szlam; Jason Weston; Rob Fergus (NIPS, 2015)

Learning from Noisy Labels with Deep Neural Networks. - Sainbayar Sukhbaatar; Rob Fergus (ICLR (Workshop), 2015)

MazeBase: A Sandbox for Learning from Games. - Sainbayar Sukhbaatar; Arthur Szlam; Gabriel Synnaeve; Soumith Chintala; Rob Fergus (CoRR, 2015)

Weakly Supervised Memory Networks. - Sainbayar Sukhbaatar; Arthur Szlam; Jason Weston; Rob Fergus (CoRR, 2015)

Simple Baseline for Visual Question Answering. - Bolei Zhou; Yuandong Tian; Sainbayar Sukhbaatar; Arthur Szlam; Rob Fergus (CoRR, 2015)

Learning Multiagent Communication with Backpropagation. - Sainbayar Sukhbaatar; Arthur Szlam; Rob Fergus (NIPS, 2016)

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. - Sainbayar Sukhbaatar; Ilya Kostrikov; Arthur Szlam; Rob Fergus (CoRR, 2017)

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. - Sainbayar Sukhbaatar; Zeming Lin; Ilya Kostrikov; Gabriel Synnaeve; Arthur Szlam; Rob Fergus (ICLR (Poster), 2018)

Composable Planning with Attributes. - Amy Zhang 001; Sainbayar Sukhbaatar; Adam Lerer; Arthur Szlam; Rob Fergus (ICML, 2018)

Planning with Arithmetic and Geometric Attributes. - David Folqué; Sainbayar Sukhbaatar; Arthur Szlam; Joan Bruna (CoRR, 2018)

Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning. - Sainbayar Sukhbaatar; Emily Denton; Arthur Szlam; Rob Fergus (CoRR, 2018)

Elements of Intelligence: Memory, Communication and Intrinsic Motivation. - Sainbayar Sukhbaatar (2018)

Training Hybrid Language Models by Marginalizing over Segmentations. - Edouard Grave; Sainbayar Sukhbaatar; Piotr Bojanowski; Armand Joulin (ACL (1), 2019)

Adaptive Attention Span in Transformers. - Sainbayar Sukhbaatar; Edouard Grave; Piotr Bojanowski; Armand Joulin (ACL (1), 2019)

Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks. - Amanpreet Singh; Tushar Jain; Sainbayar Sukhbaatar (ICLR (Poster), 2019)

Augmenting Self-attention with Persistent Memory. - Sainbayar Sukhbaatar; Edouard Grave; Guillaume Lample; Hervé Jégou; Armand Joulin (CoRR, 2019)

Accessing Higher-level Representations in Sequential Transformers with Feedback Memory. - Angela Fan; Thibaut Lavril; Edouard Grave; Armand Joulin; Sainbayar Sukhbaatar (CoRR, 2020)

Learning to Visually Navigate in Photorealistic Environments Without any Supervision. - Lina Mezghani; Sainbayar Sukhbaatar; Arthur Szlam; Armand Joulin; Piotr Bojanowski (CoRR, 2020)

Not All Memories are Created Equal: Learning to Forget by Expiring. - Sainbayar Sukhbaatar; Da Ju; Spencer Poff; Stephen Roller; Arthur Szlam; Jason Weston; Angela Fan (ICML, 2021)

Hash Layers For Large Sparse Models. - Stephen Roller; Sainbayar Sukhbaatar; Arthur Szlam; Jason Weston (NeurIPS, 2021)

Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping. - Lina Mezghani; Sainbayar Sukhbaatar; Piotr Bojanowski; Alessandro Lazaric; Karteek Alahari (CoRL, 2022)

Director: Generator-Classifiers For Supervised Language Modeling. - Kushal Arora; Kurt Shuster 001; Sainbayar Sukhbaatar; Jason Weston (AACL/IJCNLP (1), 2022)

Memory-Augmented Reinforcement Learning for Image-Goal Navigation. - Lina Mezghani; Sainbayar Sukhbaatar; Thibaut Lavril; Oleksandr Maksymets; Dhruv Batra; Piotr Bojanowski; Karteek Alahari (IROS, 2022)

Staircase Attention for Recurrent Processing of Sequences. - Da Ju; Stephen Roller; Sainbayar Sukhbaatar; Jason Weston (NeurIPS, 2022)

Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. - Akram Erraqabi; Marlos C. Machado; Mingde Zhao 001; Sainbayar Sukhbaatar; Alessandro Lazaric; Ludovic Denoyer; Yoshua Bengio (UAI, 2022)

Walk the Random Walk: Learning to Discover and Reach Goals Without Supervision. - Lina Mezghani; Sainbayar Sukhbaatar; Piotr Bojanowski; Karteek Alahari (CoRR, 2022)

A Data Source for Reasoning Embodied Agents. - Jack Lanchantin; Sainbayar Sukhbaatar; Gabriel Synnaeve; Yuxuan Sun 004; Kavya Srinet; Arthur Szlam (AAAI, 2023)

The CRINGE Loss: Learning what language not to model. - Leonard Adolphs; Tianyu Gao; Jing Xu; Kurt Shuster 001; Sainbayar Sukhbaatar; Jason Weston (ACL (1), 2023)

Learning to Reason and Memorize with Self-Notes. - Jack Lanchantin; Shubham Toshniwal; Jason Weston; Arthur Szlam; Sainbayar Sukhbaatar (NeurIPS, 2023)

MINOTAUR: Multi-task Video Grounding From Multimodal Queries. - Raghav Goyal; Effrosyni Mavroudi; Xitong Yang; Sainbayar Sukhbaatar; Leonid Sigal; Matt Feiszli; Lorenzo Torresani; Du Tran (CoRR, 2023)

Think Before You Act: Unified Policy for Interleaving Language Reasoning with Actions. - Lina Mezghani; Piotr Bojanowski; Karteek Alahari; Sainbayar Sukhbaatar (CoRR, 2023)

Large Language Model Programs. - Imanol Schlag; Sainbayar Sukhbaatar; Asli Celikyilmaz; Wen-tau Yih; Jason Weston; Jürgen Schmidhuber; Xian Li 003 (CoRR, 2023)

Improving Open Language Models by Learning from Organic Interactions. - Jing Xu; Da Ju; Joshua Lane; Mojtaba Komeili; Eric Michael Smith; Megan Ung; Morteza Behrooz; William Ngan; Rashel Moritz; Sainbayar Sukhbaatar; Y-Lan Boureau; Jason Weston; et al. (CoRR, 2023)

System 2 Attention (is something you might need too). - Jason Weston; Sainbayar Sukhbaatar (CoRR, 2023)

Some things are more CRINGE than others: Preference Optimization with the Pairwise Cringe Loss. - Jing Xu; Andrew Lee 001; Sainbayar Sukhbaatar; Jason Weston (CoRR, 2023)

Compositional Interfaces for Compositional Generalization. - Jelena Luketina; Jack Lanchantin; Sainbayar Sukhbaatar; Arthur Szlam (CoLLAs, 2024)

Self-Rewarding Language Models. - Weizhe Yuan; Richard Yuanzhe Pang; Kyunghyun Cho; Xian Li 003; Sainbayar Sukhbaatar; Jing Xu; Jason Weston (ICML, 2024)

Iterative Reasoning Preference Optimization. - Richard Yuanzhe Pang; Weizhe Yuan; He He 001; Kyunghyun Cho; Sainbayar Sukhbaatar; Jason Weston (NeurIPS, 2024)

Self-Rewarding Language Models. - Weizhe Yuan; Richard Yuanzhe Pang; Kyunghyun Cho; Sainbayar Sukhbaatar; Jing Xu; Jason Weston (CoRR, 2024)

Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping. - Lucas Lehnert; Sainbayar Sukhbaatar; Paul McVay; Michael Rabbat; Yuandong Tian (CoRR, 2024)

Teaching Large Language Models to Reason with Reinforcement Learning. - Alex Havrilla; Yuqing Du; Sharath Chandra Raparthy; Christoforos Nalmpantis; Jane Dwivedi-Yu; Maksym Zhuravinskyi; Eric Hambro; Sainbayar Sukhbaatar; Roberta Raileanu (CoRR, 2024)

Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM. - Sainbayar Sukhbaatar; Olga Golovneva; Vasu Sharma; Hu Xu 001; Xi Victoria Lin; Baptiste Rozière; Jacob Kahn; Daniel Li 006; Wen-tau Yih; Jason Weston; Xian Li 003 (CoRR, 2024)

Reverse Training to Nurse the Reversal Curse. - Olga Golovneva; Zeyuan Allen-Zhu; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

Contextual Position Encoding: Learning to Count What's Important. - Olga Golovneva; Tianlu Wang; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

Following Length Constraints in Instructions. - Weizhe Yuan; Ilia Kulikov; Ping Yu; Kyunghyun Cho; Sainbayar Sukhbaatar; Jason Weston; Jing Xu (CoRR, 2024)

Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge. - Tianhao Wu 002; Weizhe Yuan; Olga Golovneva; Jing Xu; Yuandong Tian; Jiantao Jiao; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

Thinking LLMs: General Instruction Following with Thought Generation. - Tianhao Wu 002; Janice Lan; Weizhe Yuan; Jiantao Jiao; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

Self-Consistency Preference Optimization. - Archiki Prasad; Weizhe Yuan; Richard Yuanzhe Pang; Jing Xu; Maryam Fazel-Zarandi; Mohit Bansal; Sainbayar Sukhbaatar; Jason Weston; Jane A. Yu (CoRR, 2024)

Adaptive Decoding via Latent Preference Optimization. - Shehzaad Dhuliawala; Ilia Kulikov; Ping Yu; Asli Celikyilmaz; Jason Weston; Sainbayar Sukhbaatar; Jack Lanchantin (CoRR, 2024)

Training Large Language Models to Reason in a Continuous Latent Space. - Shibo Hao; Sainbayar Sukhbaatar; DiJia Su; Xian Li 003; Zhiting Hu; Jason Weston; Yuandong Tian (CoRR, 2024)

Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces. - DiJia Su; Sainbayar Sukhbaatar; Michael Rabbat; Yuandong Tian; Qinqing Zheng (ICLR, 2025)

Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback. - Yen-Ting Lin; Di Jin; Tengyu Xu; Tianhao Wu 002; Sainbayar Sukhbaatar; Chen Zhu; Yun He; Yun-Nung Chen; Jason Weston; Yuandong Tian; Arash Rahnama; Sinong Wang; et al. (CoRR, 2025)

Diverse Preference Optimization. - Jack Lanchantin; Angelica Chen; Shehzaad Dhuliawala; Ping Yu; Jason Weston; Sainbayar Sukhbaatar; Ilia Kulikov (CoRR, 2025)

R.I.P.: Better Models by Survival of the Fittest Prompts. - Ping Yu; Weizhe Yuan; Olga Golovneva; Tianhao Wu 002; Sainbayar Sukhbaatar; Jason Weston; Jing Xu (CoRR, 2025)

SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks. - Yifei Zhou; Song Jiang; Yuandong Tian; Jason Weston; Sergey Levine; Sainbayar Sukhbaatar; Xian Li 003 (CoRR, 2025)

Multi-Token Attention. - Olga Golovneva; Tianlu Wang; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2025)

Self-Challenging Language Model Agents. - Yifei Zhou; Sergey Levine; Jason Weston; Xian Li 003; Sainbayar Sukhbaatar (CoRR, 2025)

Bridging Offline and Online Reinforcement Learning for LLMs. - Jack Lanchantin; Angelica Chen; Janice Lan; Xian Li 003; Swarnadeep Saha; Tianlu Wang; Jing Xu; Ping Yu; Weizhe Yuan; Jason E. Weston; Sainbayar Sukhbaatar; Ilia Kulikov (CoRR, 2025)

CoT-Self-Instruct: Building high-quality synthetic prompts for reasoning and non-reasoning tasks. - Ping Yu; Jack Lanchantin; Tianlu Wang; Weizhe Yuan; Olga Golovneva; Ilia Kulikov; Sainbayar Sukhbaatar; Jason Weston; Jing Xu (CoRR, 2025)