Kevin Gimpel
Toyota Technological Institute at Chicago
171 Papers
1.9K Citations
Kevin Gimpel is an academic researcher from Toyota Technological Institute at Chicago. The author has contributed to research in topics: Computer science & Sentence. The author has an hindex of 43, co-authored 170 publications. Previous affiliations of Kevin Gimpel include Toyota Technological Institute & New York University.
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Papers
•Posted Content
Gaussian Error Linear Units (GELUs)
Dan Hendrycks,Kevin Gimpel +1 more
TL;DR: An empirical evaluation of the GELU nonlinearity against the ReLU and ELU activations is performed and performance improvements are found across all considered computer vision, natural language processing, and speech tasks.
5.1K
•Proceedings Article
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan,Mingda Chen,Sebastian Goodman,Kevin Gimpel,Piyush Sharma,Radu Soricut +5 more
- 30 Apr 2020
TL;DR: This work presents two parameter-reduction techniques to lower memory consumption and increase the training speed of BERT, and uses a self-supervised loss that focuses on modeling inter-sentence coherence.
•Posted Content
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
TL;DR: The authors proposed a self-supervised loss that focuses on modeling inter-sentence coherence, and showed it consistently helps downstream tasks with multientence inputs, achieving state-of-the-art results on the GLUE, RACE, and \squad benchmarks.
4.1K
•Posted Content
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks,Kevin Gimpel +1 more
TL;DR: In this paper, the authors present a simple baseline that utilizes probabilities from softmax distributions for detecting misclassified or out-of-distribution examples, and assess performance by defining several tasks in computer vision, natural language processing, and automatic speech recognition.
2.1K
•Proceedings Article
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks,Kevin Gimpel +1 more
- 04 Nov 2016
TL;DR: A simple baseline that utilizes probabilities from softmax distributions is presented, showing the effectiveness of this baseline across all computer vision, natural language processing, and automatic speech recognition, and it is shown the baseline can sometimes be surpassed.
1.7K