| Energy and policy considerations for modern deep learning research E Strubell, A Ganesh, A McCallum Proceedings of the AAAI conference on artificial intelligence 34 (09), 13693 …, 2020 | 4130 | 2020 |
| Fast and accurate entity recognition with iterated dilated convolutions E Strubell, P Verga, D Belanger, A McCallum Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 625 | 2017 |
| Linguistically-Informed Self-Attention for Semantic Role Labeling E Strubell, P Verga, D Andor, D Weiss, A McCallum Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 490 | 2018 |
| Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction P Verga, E Strubell, A McCallum Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 339 | 2018 |
| Aligning artificial intelligence with climate change mitigation LH Kaack, PL Donti, E Strubell, G Kamiya, F Creutzig, D Rolnick Nature Climate Change 12 (6), 518-527, 2022 | 292 | 2022 |
| Machine-learned and codified synthesis parameters of oxide materials E Kim, K Huang, A Tomala, S Matthews, E Strubell, A Saunders, ... Scientific data 4 (1), 1-9, 2017 | 180 | 2017 |
| Measuring the carbon intensity of ai in cloud instances J Dodge, T Prewitt, R Tachet des Combes, E Odmark, R Schwartz, ... Proceedings of the 2022 ACM conference on fairness, accountability, and …, 2022 | 178 | 2022 |
| Inorganic materials synthesis planning with literature-trained neural networks E Kim, Z Jensen, A van Grootel, K Huang, M Staib, S Mysore, HS Chang, ... Journal of chemical information and modeling 60 (3), 1194-1201, 2020 | 134 | 2020 |
| The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures S Mysore, Z Jensen, E Kim, K Huang, HS Chang, E Strubell, J Flanigan, ... arXiv preprint arXiv:1905.06939, 2019 | 125 | 2019 |
| Power Hungry Processing: Watts Driving the Cost of AI Deployment? A Sasha Luccioni, Y Jernite, E Strubell arXiv e-prints, arXiv: 2311.16863, 2023 | 124* | 2023 |
| An empirical investigation of the role of pre-training in lifelong learning SV Mehta, D Patil, S Chandar, E Strubell Journal of Machine Learning Research 24 (214), 1-50, 2023 | 118 | 2023 |
| Multilingual relation extraction using compositional universal schema P Verga, D Belanger, E Strubell, B Roth, A McCallum Proceedings of the 2016 Conference of the North American Chapter of the …, 2015 | 116 | 2015 |
| Efficient methods for natural language processing: A survey M Treviso, JU Lee, T Ji, B Aken, Q Cao, MR Ciosici, M Hassid, K Heafield, ... Transactions of the Association for Computational Linguistics 11, 826-860, 2023 | 103 | 2023 |
| A survey of active learning for natural language processing Z Zhang, E Strubell, E Hovy arXiv preprint arXiv:2210.10109, 2022 | 98 | 2022 |
| Olmo: Accelerating the science of language models D Groeneveld, I Beltagy, P Walsh, A Bhagia, R Kinney, O Tafjord, AH Jha, ... arXiv preprint arXiv:2402.00838, 2024 | 87 | 2024 |
| Dolma: An open corpus of three trillion tokens for language model pretraining research L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson, R Authur, ... arXiv preprint arXiv:2402.00159, 2024 | 84 | 2024 |
| An introduction to quantum algorithms E Strubell | 58 | 2011 |
| DSI++: Updating transformer memory with new documents SV Mehta, J Gupta, Y Tay, M Dehghani, VQ Tran, J Rao, M Najork, ... arXiv preprint arXiv:2212.09744, 2022 | 46 | 2022 |
| Automatically extracting action graphs from materials science synthesis procedures S Mysore, E Kim, E Strubell, A Liu, HS Chang, S Kompella, K Huang, ... arXiv preprint arXiv:1711.06872, 2017 | 46 | 2017 |
| Queer people are people first: Deconstructing sexual identity stereotypes in large language models H Dhingra, P Jayashanker, S Moghe, E Strubell arXiv preprint arXiv:2307.00101, 2023 | 34 | 2023 |
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerifisert e-postadresse på cs.umass.edu
