| 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 | 1247 | 2022 |
| Sequence-to-sequence learning as beam-search optimization S Wiseman, AM Rush EMNLP 2016, 2016 | 677 | 2016 |
| Challenges in data-to-document generation S Wiseman, SM Shieber, AM Rush EMNLP 2017, 2017 | 676 | 2017 |
| Semi-amortized variational autoencoders Y Kim, S Wiseman, AC Miller, D Sontag, AM Rush ICML 2018, 2018 | 291 | 2018 |
| Learning global features for coreference resolution S Wiseman, AM Rush, SM Shieber NAACL 2016, 2016 | 275 | 2016 |
| Learning neural templates for text generation S Wiseman, SM Shieber, AM Rush EMNLP 2018, 2018 | 241 | 2018 |
| Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution S Wiseman, AM Rush, SM Shieber, J Weston Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 231 | 2015 |
| MM1: methods, analysis and insights from multimodal LLM pre-training B McKinzie, Z Gan, JP Fauconnier, S Dodge, B Zhang, P Dufter, D Shah, ... European Conference on Computer Vision, 304-323, 2025 | 173 | 2025 |
| Controllable Paraphrase Generation with a Syntactic Exemplar M Chen, Q Tang, S Wiseman, K Gimpel ACL 2019, 2019 | 138 | 2019 |
| Summscreen: A dataset for abstractive screenplay summarization M Chen, Z Chu, S Wiseman, K Gimpel arXiv preprint arXiv:2104.07091, 2021 | 123 | 2021 |
| A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations M Chen, Q Tang, S Wiseman, K Gimpel NAACL 2019, 2019 | 88 | 2019 |
| Label-Agnostic Sequence Labeling by Copying Nearest Neighbors S Wiseman, K Stratos ACL 2019, 2019 | 68 | 2019 |
| ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation L Tu, RY Pang, S Wiseman, K Gimpel ACL 2020, 2020 | 60 | 2020 |
| Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks S Toshniwal, S Wiseman, A Ettinger, K Livescu, K Gimpel EMNLP 2020, 2020 | 58 | 2020 |
| A tutorial on deep latent variable models of natural language Y Kim, S Wiseman, AM Rush arXiv preprint arXiv:1812.06834, 2018 | 49 | 2018 |
| Chess as a Testbed for Language Model State Tracking S Toshniwal, S Wiseman, K Livescu, K Gimpel AAAI 2022, 2022 | 48* | 2022 |
| On Generalization in Coreference Resolution S Toshniwal, P Xia, S Wiseman, K Livescu, K Gimpel CRAC@EMNLP 2021, 2021 | 43 | 2021 |
| WikiTableT: A large-scale data-to-text dataset for generating Wikipedia article sections M Chen, S Wiseman, K Gimpel Findings of ACL 2021, 2021 | 32 | 2021 |
| Apple intelligence foundation language models T Gunter, Z Wang, C Wang, R Pang, A Narayanan, A Zhang, B Zhang, ... arXiv preprint arXiv:2407.21075, 2024 | 22 | 2024 |
| Discrete Latent Variable Representations for Low-Resource Text Classification S Jin, S Wiseman, K Stratos, K Livescu ACL 2020, 2020 | 21 | 2020 |
Alexander M. RushAssociate Professor, Cornell UniversityVerified email at cornell.edu
