Speaker-follower models for vision-and-language navigation D Fried, R Hu, V Cirik, A Rohrbach, J Andreas, LP Morency, ... Advances in neural information processing systems 31, 2018 | 488 | 2018 |
Incoder: A generative model for code infilling and synthesis D Fried, A Aghajanyan, J Lin, S Wang, E Wallace, F Shi, R Zhong, W Yih, ... arXiv preprint arXiv:2204.05999, 2022 | 435 | 2022 |
Starcoder: may the source be with you! R Li, LB Allal, Y Zi, N Muennighoff, D Kocetkov, C Mou, M Marone, C Akiki, ... arXiv preprint arXiv:2305.06161, 2023 | 432 | 2023 |
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 | 180 | 2022 |
Bayesian geometric modeling of indoor scenes L Del Pero, J Bowdish, D Fried, B Kermgard, E Hartley, K Barnard Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on …, 2012 | 165 | 2012 |
Neural theory-of-mind? on the limits of social intelligence in large lms M Sap, R LeBras, D Fried, Y Choi arXiv preprint arXiv:2210.13312, 2022 | 155 | 2022 |
SantaCoder: don't reach for the stars! LB Allal, R Li, D Kocetkov, C Mou, C Akiki, CM Ferrandis, N Muennighoff, ... arXiv preprint arXiv:2301.03988, 2023 | 151 | 2023 |
Contrastive decoding: Open-ended text generation as optimization XL Li, A Holtzman, D Fried, P Liang, J Eisner, T Hashimoto, L Zettlemoyer, ... arXiv preprint arXiv:2210.15097, 2022 | 144 | 2022 |
Generating images with multimodal language models JY Koh, D Fried, RR Salakhutdinov Advances in Neural Information Processing Systems 36, 2024 | 129 | 2024 |
Grounding language models to images for multimodal inputs and outputs JY Koh, R Salakhutdinov, D Fried International Conference on Machine Learning, 17283-17300, 2023 | 124 | 2023 |
Webarena: A realistic web environment for building autonomous agents S Zhou, FF Xu, H Zhu, X Zhou, R Lo, A Sridhar, X Cheng, Y Bisk, D Fried, ... arXiv preprint arXiv:2307.13854, 2023 | 122 | 2023 |
DS-1000: A natural and reliable benchmark for data science code generation Y Lai, C Li, Y Wang, T Zhang, R Zhong, L Zettlemoyer, W Yih, D Fried, ... International Conference on Machine Learning, 18319-18345, 2023 | 118 | 2023 |
Unified pragmatic models for generating and following instructions D Fried, J Andreas, D Klein arXiv preprint arXiv:1711.04987, 2017 | 115 | 2017 |
Analyzing the language of food on social media D Fried, M Surdeanu, S Kobourov, M Hingle, D Bell 2014 IEEE International Conference on Big Data (Big Data), 778-783, 2014 | 111 | 2014 |
Are you looking? grounding to multiple modalities in vision-and-language navigation R Hu, D Fried, A Rohrbach, D Klein, T Darrell, K Saenko arXiv preprint arXiv:1906.00347, 2019 | 89 | 2019 |
Pragmatically informative text generation S Shen, D Fried, J Andreas, D Klein arXiv preprint arXiv:1904.01301, 2019 | 70 | 2019 |
Natural language to code translation with execution F Shi, D Fried, M Ghazvininejad, L Zettlemoyer, SI Wang arXiv preprint arXiv:2204.11454, 2022 | 68 | 2022 |
Maps of computer science D Fried, SG Kobourov 2014 IEEE Pacific Visualization Symposium, 113-120, 2014 | 61 | 2014 |
Effective inference for generative neural parsing M Stern, D Fried, D Klein arXiv preprint arXiv:1707.08976, 2017 | 60 | 2017 |
Higher-order lexical semantic models for non-factoid answer reranking D Fried, P Jansen, G Hahn-Powell, M Surdeanu, P Clark Transactions of the Association for Computational Linguistics 3, 197-210, 2015 | 59 | 2015 |