Gimpel, Kevin

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4,308

Gaussian Error Linear Units (GELUs)

Hendrycks, D., & Gimpel, K. (2016) · arXiv

Neural Networks and ApplicationsAdvanced Neural Network Applications

Cited by 3,537

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Hendrycks, D., & Gimpel, K. (2016) · arXiv

Adversarial Robustness in Machine LearningMachine Learning and Data Classification

Cited by 1,968

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

Commonsense Knowledge Base Completion

Li, X., Taheri, A., Tu, L., & Gimpel, K. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingAdvanced Graph Neural Networks

Cited by 166

SummScreen: A Dataset for Abstractive Screenplay Summarization

Chen, M., Chu, Z., Wiseman, S., & Gimpel, K. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingAdvanced Text Analysis Techniques

Cited by 46

Paraphrastic Representations at Scale

Wieting, J., Gimpel, K., Neubig, G., & Berg-kirkpatrick, T. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Topic ModelingNatural Language Processing Techniques

Cited by 13