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Disha Shrivastava
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2020 – today
- 2024
- [c5]Avinash Bhat
, Disha Shrivastava
Do LLMs Meet the Needs of Software Tutorial Writers? Opportunities and Design Implications. Conference on Designing Interactive Systems 2024 - [c4]Mina Lee
A Design Space for Intelligent and Interactive Writing Assistants. CHI 2024: 1054:1-1054:35 - [i12]Mina Lee, Katy Ilonka Gero, John Joon Young Chung, Simon Buckingham Shum, Vipul Raheja, Hua Shen, Subhashini Venugopalan, Thiemo Wambsganss, David Zhou, Emad A. Alghamdi, Tal August, Avinash Bhat, Madiha Zahrah Choksi, Senjuti Dutta, Jin L. C. Guo, Md. Naimul Hoque, Yewon Kim, Simon Knight
A Design Space for Intelligent and Interactive Writing Assistants. CoRR abs/2403.14117 (2024) - [i11]Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust:
Training Language Models to Self-Correct via Reinforcement Learning. CoRR abs/2409.12917 (2024) - 2023
- [c3]Disha Shrivastava, Hugo Larochelle, Daniel Tarlow:
Repository-Level Prompt Generation for Large Language Models of Code. ICML 2023: 31693-31715 - [i10]Avinash Bhat, Disha Shrivastava, Jin L. C. Guo:
Approach Intelligent Writing Assistants Usability with Seven Stages of Action. CoRR abs/2304.02822 (2023) - [i9]Disha Shrivastava, Denis Kocetkov, Harm de Vries, Dzmitry Bahdanau, Torsten Scholak:
RepoFusion: Training Code Models to Understand Your Repository. CoRR abs/2306.10998 (2023) - 2022
- [i8]Disha Shrivastava, Hugo Larochelle, Daniel Tarlow:
Repository-Level Prompt Generation for Large Language Models of Code. CoRR abs/2206.12839 (2022) - 2021
- [c2]Edoardo Maria Ponti, Rahul Aralikatte, Disha Shrivastava, Siva Reddy, Anders Søgaard:
Minimax and Neyman-Pearson Meta-Learning for Outlier Languages. ACL/IJCNLP (Findings) 2021: 1245-1260 - [c1]Disha Shrivastava, Hugo Larochelle, Daniel Tarlow:
Learning to Combine Per-Example Solutions for Neural Program Synthesis. NeurIPS 2021: 6102-6114 - [i7]Edoardo Maria Ponti, Rahul Aralikatte, Disha Shrivastava, Siva Reddy, Anders Søgaard:
Minimax and Neyman-Pearson Meta-Learning for Outlier Languages. CoRR abs/2106.01051 (2021) - [i6]Disha Shrivastava, Hugo Larochelle, Daniel Tarlow:
Learning to Combine Per-Example Solutions for Neural Program Synthesis. CoRR abs/2106.07175 (2021)
2010 – 2019
- 2019
- [j1]S. Agrawal, Anush Sankaran
What is deemed computationally creative? IBM J. Res. Dev. 63(1): 3:1-3:12 (2019) - [i5]Disha Shrivastava, Eeshan Gunesh Dhekane, Riashat Islam:
Transfer Learning by Modeling a Distribution over Policies. CoRR abs/1906.03574 (2019) - 2018
- [i4]Disha Shrivastava, Abhijit Mishra, Karthik Sankaranarayanan:
Modeling Topical Coherence in Discourse without Supervision. CoRR abs/1809.00410 (2018) - [i3]Disha Shrivastava, Sreyash Kenkre, Santosh Penubothula:
Hypernyms Through Intra-Article Organization in Wikipedia. CoRR abs/1809.00414 (2018) - 2017
- [i2]Disha Shrivastava, C. G. Saneem Ahmed, Anirban Laha, Karthik Sankaranarayanan:
A Machine Learning Approach for Evaluating Creative Artifacts. CoRR abs/1707.05499 (2017) - [i1]Disha Shrivastava, Santanu Chaudhury, Jayadeva:
A Data and Model-Parallel, Distributed and Scalable Framework for Training of Deep Networks in Apache Spark. CoRR abs/1708.05840 (2017)
Coauthor Index
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