| Opt: Open pre-trained transformer language models S Zhang, S Roller, N Goyal, M Artetxe, M Chen, S Chen, C Dewan, ... arXiv preprint arXiv:2205.01068, 2022 | 3713* | 2022 |
| Recipes for building an open-domain chatbot S Roller arXiv preprint arXiv:2004.13637, 2020 | 1132 | 2020 |
| Wizard of wikipedia: Knowledge-powered conversational agents E Dinan, S Roller, K Shuster, A Fan, M Auli, J Weston arXiv preprint arXiv:1811.01241, 2018 | 1034 | 2018 |
| Neural text generation with unlikelihood training S Welleck, I Kulikov, S Roller, E Dinan, K Cho, J Weston arXiv preprint arXiv:1908.04319, 2019 | 588 | 2019 |
| Supervised Text-based Geolocation Using Language Models on an Adaptive Grid S Roller, M Speriosu, S Rallapalli, B Wing, J Baldridge | 305 | 2012 |
| Blenderbot 3: a deployed conversational agent that continually learns to responsibly engage K Shuster, J Xu, M Komeili, D Ju, EM Smith, S Roller, M Ung, M Chen, ... arXiv preprint arXiv:2208.03188, 2022 | 282 | 2022 |
| What makes a good conversation? how controllable attributes affect human judgments A See, S Roller, D Kiela, J Weston arXiv preprint arXiv:1902.08654, 2019 | 263 | 2019 |
| Human-level play in the game of Diplomacy by combining language models with strategic reasoning Meta Fundamental AI Research Diplomacy Team (FAIR)†, A Bakhtin, ... Science 378 (6624), 1067-1074, 2022 | 251 | 2022 |
| Inclusive yet selective: Supervised distributional hypernymy detection S Roller, K Erk, G Boleda Proceedings of COLING 2014, the 25th international conference on …, 2014 | 225 | 2014 |
| Don't say that! making inconsistent dialogue unlikely with unlikelihood training M Li, S Roller, I Kulikov, S Welleck, YL Boureau, K Cho, J Weston arXiv preprint arXiv:1911.03860, 2019 | 209 | 2019 |
| Hash layers for large sparse models S Roller, S Sukhbaatar, J Weston Advances in Neural Information Processing Systems 34, 17555-17566, 2021 | 196 | 2021 |
| Acute-eval: Improved dialogue evaluation with optimized questions and multi-turn comparisons M Li, J Weston, S Roller arXiv preprint arXiv:1909.03087, 2019 | 178 | 2019 |
| Hearst patterns revisited: Automatic hypernym detection from large text corpora S Roller, D Kiela, M Nickel arXiv preprint arXiv:1806.03191, 2018 | 170 | 2018 |
| MGNC-CNN: A simple approach to exploiting multiple word embeddings for sentence classification Y Zhang, S Roller, B Wallace arXiv preprint arXiv:1603.00968, 2016 | 150 | 2016 |
| Language models that seek for knowledge: Modular search & generation for dialogue and prompt completion K Shuster, M Komeili, L Adolphs, S Roller, A Szlam, J Weston arXiv preprint arXiv:2203.13224, 2022 | 124 | 2022 |
| A multimodal LDA model integrating textual, cognitive and visual modalities S Roller, SS Im Walde Proceedings of the 2013 Conference on Empirical Methods in Natural Language …, 2013 | 121 | 2013 |
| Relations such as hypernymy: Identifying and exploiting hearst patterns in distributional vectors for lexical entailment S Roller, K Erk arXiv preprint arXiv:1605.05433, 2016 | 94 | 2016 |
| Scaling laws for generative mixed-modal language models A Aghajanyan, L Yu, A Conneau, WN Hsu, K Hambardzumyan, S Zhang, ... International Conference on Machine Learning, 265-279, 2023 | 89 | 2023 |
| Inferring concept hierarchies from text corpora via hyperbolic embeddings M Le, S Roller, L Papaxanthos, D Kiela, M Nickel arXiv preprint arXiv:1902.00913, 2019 | 88 | 2019 |
| Representing meaning with a combination of logical and distributional models I Beltagy, S Roller, P Cheng, K Erk, RJ Mooney Computational Linguistics 42 (4), 763-808, 2016 | 84 | 2016 |
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