Divyansh Kaushik

According to our database, Divyansh Kaushik authored at least 10 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Resolving the Human-subjects Status of Machine Learning's Crowdworkers: What ethical framework should govern the interaction of ML researchers and crowdworkers?

Divyansh Kaushik, Zachary C. Lipton, Alex John London

ACM Queue, 2024

2022

Resolving the Human Subjects Status of Machine Learning's Crowdworkers.

Divyansh Kaushik, Zachary C. Lipton, Alex John London

CoRR, 2022

Practical Benefits of Feature Feedback Under Distribution Shift.

Anurag Katakkar, Clay H. Yoo, Weiqin Wang, Zachary C. Lipton, Divyansh Kaushik

Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022

2021

Dynabench: Rethinking Benchmarking in NLP.

Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, Adina Williams

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Explaining the Efficacy of Counterfactually Augmented Data.

Divyansh Kaushik, Amrith Setlur, Eduard H. Hovy, Zachary Chase Lipton

Proceedings of the 9th International Conference on Learning Representations, 2021

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

Divyansh Kaushik, Douwe Kiela, Zachary C. Lipton, Wen-tau Yih

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Learning The Difference That Makes A Difference With Counterfactually-Augmented Data.

Divyansh Kaushik, Eduard H. Hovy, Zachary Chase Lipton

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment.

Yifan Wu, Ezra Winston, Divyansh Kaushik, Zachary C. Lipton

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks.

Divyansh Kaushik, Zachary C. Lipton

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

Making Travel Smarter: Extracting Travel Information From Email Itineraries Using Named Entity Recognition.

Divyansh Kaushik, Shashank Gupta, Chakradhar Raju, Reuben Dias, Sanjib Ghosh

Proceedings of the International Conference Recent Advances in Natural Language Processing, 2017