| PaLM: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... arXiv preprint arXiv:2204.02311, 2022 | 5124 | 2022 |
| Bloom: A 176b-parameter open-access multilingual language model T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... | 1623 | 2023 |
| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 1434 | 2023 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1175 | 2022 |
| Bottom-up abstractive summarization S Gehrmann, Y Deng, AM Rush EMNLP 2018, 2018 | 851 | 2018 |
| BloombergGPT: A large language model for finance S Wu, O Irsoy, S Lu, V Dabravolski, M Dredze, S Gehrmann, P Kambadur, ... arXiv preprint arXiv:2303.17564, 2023 | 783 | 2023 |
| Challenging big-bench tasks and whether chain-of-thought can solve them M Suzgun, N Scales, N Schärli, S Gehrmann, Y Tay, HW Chung, ... ACL Findings 2023, 2022 | 561 | 2022 |
| LSTMVis: A tool for visual analysis of hidden state dynamics in recurrent neural networks H Strobelt*, S Gehrmann*, H Pfister, AM Rush IEEE transactions on visualization and computer graphics 24 (1), 667-676, 2017 | 555 | 2017 |
| GLTR: Statistical detection and visualization of generated text S Gehrmann*, H Strobelt*, AM Rush ACL Demo 2019, 2019 | 526 | 2019 |
| Investigating gender bias in language models using causal mediation analysis J Vig*, S Gehrmann*, Y Belinkov*, S Qian, D Nevo, Y Singer, S Shieber NeurIPS 2021 33, 12388-12401, 2020 | 495* | 2020 |
| ToTTo: A controlled table-to-text generation dataset AP Parikh, X Wang, S Gehrmann, M Faruqui, B Dhingra, D Yang, D Das EMNLP 2020, 2020 | 362 | 2020 |
| Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations P Das, T Sercu, K Wadhawan, I Padhi, S Gehrmann, F Cipcigan, ... Nature Biomedical Engineering 5 (6), 613-623, 2021 | 303 | 2021 |
| Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives S Gehrmann, F Dernoncourt, Y Li, ET Carlson, JT Wu, J Welt, J Foote Jr, ... PloS one 13 (2), e0192360, 2018 | 295* | 2018 |
| Seq2Seq-Vis: A visual debugging tool for sequence-to-sequence models H Strobelt*, S Gehrmann*, M Behrisch, A Perer, H Pfister, AM Rush IEEE transactions on visualization and computer graphics 25 (1), 353-363, 2018 | 279 | 2018 |
| The language interpretability tool: Extensible, interactive visualizations and analysis for NLP models I Tenney, J Wexler, J Bastings, T Bolukbasi, A Coenen, S Gehrmann, ... ACL Demo 2020, 2020 | 212 | 2020 |
| exBERT: A visual analysis tool to explore learned representations in transformers models B Hoover, H Strobelt, S Gehrmann EMNLP Demo 2019, 2019 | 193 | 2019 |
| The GEM benchmark: Natural language generation, its evaluation and metrics S Gehrmann, T Adewumi, K Aggarwal, PS Ammanamanchi, ... GEM Workshop at ACL 2021, 2021 | 151 | 2021 |
| Repairing the cracked foundation: A survey of obstacles in evaluation practices for generated text S Gehrmann, E Clark, T Sellam JAIR, 2022 | 150 | 2022 |
| Palm: Scaling language modeling with pathways. arXiv 2022 A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... arXiv preprint arXiv:2204.02311 10, 2022 | 115 | 2022 |
| Causal analysis of syntactic agreement mechanisms in neural language models M Finlayson, A Mueller, S Gehrmann, S Shieber, T Linzen, Y Belinkov ACL 2021, 2021 | 91 | 2021 |
Hendrik StrobeltSenior Research Scientist IBM Research / MIT-IBM Watson AI Lab在 strobelt.com 的电子邮件经过验证
