Rush, Alexander M.

Transformers: State-of-the-Art Natural Language Processing

Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., et al. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Topic ModelingNatural Language Processing Techniques

Cited by 8,741

HuggingFace's Transformers: State-of-the-art Natural Language Processing

Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., et al. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3,347

Character-Aware Neural Language Models

Kim, Y., Jernite, Y., Sontag, D., & Rush, A. M. (2015) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1,530

Sequence-Level Knowledge Distillation

Kim, Y., & Rush, A. M. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesAdvanced Neural Network Applications

Cited by 836

Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

Weston, J., Bordes, A., Chopra, S., Rush, A. M., van Merriënboer, B., Joulin, A., & Mikolov, T. (2015) · arXiv

Spatial Cognition and NavigationTopic Modeling

Cited by 670

Multitask Prompted Training Enables Zero-Shot Task Generalization

Sanh, V., Webson, A., Raffel, C., Bach, S. H., Sutawika, L., Alyafeai, Z., Chaffin, A., Stiegler, A., Scao, T. L., Raja, A., et al. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 612

Challenges in Data-to-Document Generation

Wiseman, S., Shieber, S., & Rush, A. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Topic ModelingMultimodal Machine Learning Applications

Cited by 524

GLTR: Statistical Detection and Visualization of Generated Text

Gehrmann, S., Strobelt, H., & Rush, A. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

Authorship Attribution and ProfilingDigital Media Forensic Detection

Cited by 470

GLTR: Statistical Detection and Visualization of Generated Text

Gehrmann, S., Strobelt, H., & Rush, A. M. (2019) · arXiv

Authorship Attribution and ProfilingDigital Media Forensic Detection

Cited by 460

Structured Attention Networks

Kim, Y., Denton, C., Hoang, L., & Rush, A. M. (2017) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 381

Datasets: A Community Library for Natural Language Processing

Lhoest, Q., Villanova del Moral, A., Jernite, Y., Thakur, A., von Platen, P., Patil, S., Chaumond, J., Drame, M., Plu, J., Tunstall, L., et al. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Natural Language Processing TechniquesTopic Modeling

Cited by 343

Commonsense Knowledge Mining from Pretrained Models

Davison, J., Feldman, J., & Rush, A. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 264

Parameter-Efficient Transfer Learning with Diff Pruning

Guo, D., Rush, A., & Kim, Y. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 220

Movement pruning: Adaptive sparsity by fine-tuning

Sanh, V., Wolf, T., & Rush, A. M. (2020) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 218

Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models

Strobelt, H., Webson, A., Sanh, V., Hoover, B., Beyer, J., Pfister, H., & Rush, A. M. (2022) · arXiv

Topic ModelingData Visualization and Analytics

Cited by 204

Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation With Large Language Models

Strobelt, H., Webson, A., Sanh, V., Hoover, B., Beyer, J., Pfister, H., & Rush, A. M. (2022) · IEEE Transactions on Visualization and Computer Graphics

Topic ModelingData Visualization and Analytics

Cited by 204

How many data points is a prompt worth?

Le Scao, T., & Rush, A. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 179

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

Bach, S., Sanh, V., Yong, Z. X., Webson, A., Raffel, C., Nayak, N. V., Sharma, A., Kim, T., Bari, M. S., Fevry, T., et al. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

Natural Language Processing TechniquesTopic Modeling

Cited by 178

Don’t Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference

Belinkov, Y., Poliak, A., Shieber, S., Van Durme, B., & Rush, A. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 73

OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents

Laurençon, H., Saulnier, L., Tronchon, L., Bekman, S., Singh, A., Lozhkov, A., Wang, T., Karamcheti, S., Rush, A. M., Kiela, D., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsHandwritten Text Recognition Techniques

Cited by 72

End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

Petti, S., Bhattacharya, N., Rao, R., Dauparas, J., Thomas, N., Zhou, J., Rush, A. M., Koo, P., & Ovchinnikov, S. (2023) · Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 54

Scaling Data-Constrained Language Models

Muennighoff, N., Rush, A. M., Barak, B., Scao, T. L., Piktus, A., Tazi, N., Pyysalo, S., Wolf, T., & Raffel, C. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

Scaling Data-Constrained Language Models

Muennighoff, N., Rush, A., Barak, B., Scao, T. L., Tazi, N., Piktus, A., Pyysalo, S., Wolf, T., & Raffel, C. (2023) · Advances in Neural Information Processing Systems 36

Topic ModelingNatural Language Processing Techniques

Cited by 47

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

Bach, S. H., Sanh, V., Yong, Z.-X., Webson, A., Raffel, C., Nayak, N. V., Sharma, A., Kim, T., Bari, M. S., Fevry, T., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 21