Divyansh Kaushik

Divyansh Kaushik

Carnegie Mellon University

H-index: 8

North America-United States

Contact Divyansh Kaushik

About Divyansh Kaushik

Divyansh Kaushik, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Carnegie Mellon University, specializes in the field of Machine Learning, Natural Language Processing, Technology & Society, Science & Technology Policy.

His recent articles reflect a diverse array of research interests and contributions to the field:

Practical Benefits of Feature Feedback Under Distribution Shift

Robustifying NLP with Humans in the Loop

The Impact of International Scientists, Engineers, and Students on U.S. Research Outputs and Global Competitiveness

On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study

Dynabench: Rethinking Benchmarking in NLP

Explaining The Efficacy of Counterfactually Augmented Data

Learning the Difference that Makes a Difference with Counterfactually-Augmented Data

Divyansh Kaushik Information

University	Carnegie Mellon University
Position	PhD Student at Language Technologies Institute
Citations(all)	1285
Citations(since 2020)	1276
Cited By	280
hIndex(all)	8
hIndex(since 2020)	8
i10Index(all)	7
i10Index(since 2020)	7
Email	Access Email
University Profile Page	Carnegie Mellon University
Google Scholar	View Google Scholar Profile

Divyansh Kaushik Skills & Research Interests

Machine Learning

Natural Language Processing

Technology & Society

Science & Technology Policy

Top articles of Divyansh Kaushik

Practical Benefits of Feature Feedback Under Distribution Shift

BlackboxNLP Workshop

2022

Divyansh Kaushik

H-Index: 4

Robustifying NLP with Humans in the Loop

2022/2/24

Divyansh Kaushik

H-Index: 4

The Impact of International Scientists, Engineers, and Students on U.S. Research Outputs and Global Competitiveness

MIT Science Policy Review

2021/5/20

Divyansh Kaushik

H-Index: 4

On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study

Association for Computational Linguistics and International Joint Conference on Natural Language Processing (ACL-IJCNLP)

2021

Divyansh Kaushik

H-Index: 4

Dynabench: Rethinking Benchmarking in NLP

arXiv preprint arXiv:2104.14337

2021/4/7

Max Bartolo

H-Index: 3

Yixin Nie

H-Index: 7

Divyansh Kaushik

H-Index: 4

Atticus Geiger

H-Index: 5

Zhengxuan Wu

H-Index: 5

Grusha Prasad

H-Index: 3

Amanpreet Singh

H-Index: 1

Sebastian Riedel

H-Index: 39

Robin Jia

H-Index: 10

Mohit Bansal

H-Index: 39

Christopher Potts

H-Index: 1

Explaining The Efficacy of Counterfactually Augmented Data

International Conference on Learning Representations (ICLR)

2021

Divyansh Kaushik

H-Index: 4

Amrith Setlur

H-Index: 3

Eduard Hovy

H-Index: 61

Learning the Difference that Makes a Difference with Counterfactually-Augmented Data

International Conference on Learning Representations (ICLR)

2020

Divyansh Kaushik

H-Index: 4

Eduard Hovy

H-Index: 61

See List of Professors in Divyansh Kaushik University(Carnegie Mellon University)

Co-Authors

H-index: 68

Mohit Bansal — Mohit Bansal
University of North Carolina at Chapel Hill

Visit Mohit Bansal Page

H-index: 65

Sebastian Riedel — Sebastian Riedel
University College London

Visit Sebastian Riedel Page

H-index: 53

Zachary C. Lipton — Zachary C. Lipton
Carnegie Mellon University

Visit Zachary C. Lipton Page

H-index: 38

Alex John London — Alex John London
Carnegie Mellon University

Visit Alex John London Page

H-index: 22

Robin Jia — Robin Jia
University of Southern California

Visit Robin Jia Page

H-index: 15

Yixin Nie — Yixin Nie
University of North Carolina at Chapel Hill

Visit Yixin Nie Page

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