Shrimai Prabhumoye

I am a PhD student at Language Technologies, School of Computer Science, Carnegie Mellon University. I am advised by Prof. Alan W. Black and Prof. Ruslan Salakhutdinov. I work on controllable text generation with focus on style, content and structure. I am also exploring the ethical considerations of controllable text generation. I co-designed the Computational Ethics for NLP course which was offered for the first time in Spring 2018 at CMU.

I graduated with a Masters in Language Technologies in Aug 2017. During that time, I was leading the CMU Magnus team in the Amazon Alexa Prize competition. I completed my undergraduate at National Institute of Technology, Karnataka, India.

Email: sprabhum at cs.cmu[dot]edu; sprabhum at andrew[dot]cmu.edu
Office: 5511 Gates and Hillman Center, Carnegie Mellon University

News

Apr 2021	I successfully defended my thesis!
Mar 2021	New paper titled *Focused Attention Improves Document-Grounded Generation* is accepted at NAACL 2021
Mar 2021	New paper titled *Case Study: Deontological Ethics in NLP* is accepted at NAACL 2021
Oct 2020	New paper titled *Exploring Controllable Text Generation Techniques* is accepted at COLING 2020
Sep 2020	Invited talk at Grace Hopper Conference 2020 on Text Generation: Should machines reflect the way humans interact in society.
Jul 2020	Invited talk at Allen Institute for AI, MILA, Salesforce, Deep Learning: Classics and Trends, and Apple on Controllable Text Generation: Should machines reflect the way humans interact in society.
Jul 2020	Our work on politeness transfer is featured in SCS CMU News, TechCrunch, CNET, Pittsburgh Post-Gazette, msn, Hindustan Times, and Axios.
May 2020	Excited to join Salesforce Research as an intern.
Apr 2020	I successfully proposed my thesis titled Controllable Text Generation: Should machines reflect the way humans interact in society?
Apr 2020	New paper titled *Politeness Transfer: A Tag and Generate Approach* is accepted at ACL 2020
Apr 2020	New paper titled *Topological Sort for Sentence Ordering* is accepted at ACL 2020
2019	Invited talk at University of Massachusets Amherst and Google AI, NYC on Controlling Style, Content and Structure in Text Generation

Publications

15. Focused Attention Improves Document-Grounded Generation

Shrimai Prabhumoye, Kazuma Hashimoto, Yingbo Zhou, Alan W Black, Ruslan Salakhutdinov.
In the proceedings of North America Chapter of Association of Computational Linguistics (NAACL) 2021.

14. Case Study: Deontological Ethics in NLP

Shrimai Prabhumoye*, Brendon Boldt*, Ruslan Salakhutdinov, Alan W Black.
In the proceedings of North America Chapter of Association of Computational Linguistics (NAACL) 2021.

13. Exploring Controllable Text Generation Techniques

Shrimai Prabhumoye, Alan W Black, Ruslan Salakhutdinov.
Proceedings of the 28th International Conference on Computational Linguistics (COLING) 2020.
Selected for oral presentation

12. Topological Sort for Sentence Ordering

Shrimai Prabhumoye, Ruslan Salakhutdinov, Alan W Black.
In the proceedings of Association for Computational Linguistics Conference (ACL) 2020.

11. Politeness Transfer: A Tag and Generate Approach

Aman Madaan*, Amrith Setlur*, Tanmay Parekh*, Barnabas Poczos, Graham Neubig,Yiming Yang,
Ruslan Salakhutdinov, Alan W Black, Shrimai Prabhumoye.
In the proceedings of Association for Computational Linguistics Conference (ACL) 2020.

10. I love your chain mail! Making knights smile in a fantasy game world:
Open-domain goal-oriented dialogue agents

Shrimai Prabhumoye*, Margaret Li*, Jack Urbanek, Emily Dinan, Douwe Kiela, Jason Weston, Arthur Szlam.
arXiv:2002.02878 [cs.AI]

9. Generating Interactive Worlds with Text

Angela Fan*, Jack Urbanek*, Pratik Ringshia, Emily Dinan, Emma Qian, Siddharth Karamcheti, Shrimai Prabhumoye,
Douwe Kiela, Tim Rocktaschel, Arthur Szlam, Jason Weston.
In the Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence.

8. Principled Frameworks for Evaluating Ethics in NLP Systems

Shrimai Prabhumoye, Elijah Mayfield, Alan W Black.
Widening NLP Workshop at ACL 2019.

7. "My Way of Telling a Story": Persona based Grounded Story Generation

Shrimai Prabhumoye*, Khyathi Chandu*, Ruslan Salakhutdinov, Alan W Black.
In the proceedings of Storytelling Workshop at ACL 2019.

6. Equity Beyond Bias in Language Technologies for Education

Elijah Mayfield, Michael Madaio, Shrimai Prabhumoye, David Gerritsen, Brittany McLaughlin,
Ezekiel Dixon-Román, Alan W Black.
In the Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications at ACL 2019.

5. Towards Content Transfer Through Grounded Text Generation

Shrimai Prabhumoye, Chris Quirk, Michel Galley
In the proceedings of North America Chapter of Association of Computational Linguistics (NAACL) 2019.
Selected for oral presentation

4. A Dataset for Document Grounded Conversations

Kangyan Zhou, Shrimai Prabhumoye, Alan W Black.
In the proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP) 2018.

3. Style Transfer Through Back-Translation

Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, Alan W Black.
In the proceedings of Association for Computational Linguistics Conference (ACL) 2018.
Selected for oral presentation

2. Linguistic Markers of Influence in Informal Interactions

Shrimai Prabhumoye*, Samridhi Choudhary*, Evangelia Spiliopoulou, Christopher Bogart, Carolyn Penstein Rose, Alan W Black.
In the proceedings of Workshop on NLP+CSS at ACL 2017.

1. Building CMU Magus from User Feedback

Shrimai Prabhumoye*, Fadi Botros*, Khyathi Chandu*, Samridhi Choudhary*, Esha Keni*, Chaitanya Malaviya*, Thomas Manzini*, Rama Pasumarthi*, Shivani Poddar*, Abhilasha Ravichander*, Zhou Yu, Alan Black
In the proceedings of Alexa Prize 2017.

Mentored Students

Politeness Transfer: A Tag and Generate Approach

This work introduces a new task of politeness transfer which involves converting non-polite sentences to polite sentences while preserving the meaning. We also provide a dataset of more than 1.39 million instances automatically labeled for politeness to encourage benchmark evaluations on this new task. We design a tag and generate pipeline that identifies stylistic attributes and subsequently generates a sentence in the target style while preserving most of the source content.

Associated Publication: Politeness Transfer: A Tag and Generate Approach at ACL 2020

Downstream tasks to evaluate style transfer

We know that downstream tasks are influenced by the demographic skew of training sets like the sentiment analysis task is affected by the gender confound and the part of speech (POS) tagging task is affected by the age confound. By building a generation engine that can preserve content while controlling for style, we can now produce demographically balanced datasets for these NLP tasks. We are also looking at using these downstream tasks to automatically evaluate style transfer models.

A Dataset for Document Grounded Conversations

This work introduces a document grounded dataset for conversations using Wikipedia articles on movies. The dataset contains 4112 conversations with an average of 21.43 turns per conversation. We describe two neural architectures that provide benchmark performance on the task of generating the next response.

Associated Publication: A Dataset for Document Grounded Conversations at EMNLP 2018

Teaching

Guest Lectures

Style Transfer

Machine Translation and Sequence-to-sequence Models
CS 11-731, Carnegie Mellon University, Fall 2018

Ethics in Conversational Agents

Computational Ethics in NLP
CS 11-830, Carnegie Mellon University, Spring 2018, Spring 2019 and Spring 2020

Chatbots

Speech Processing
CS 11-492 11-692 11-892, Carnegie Mellon University, Fall 2017, 2018, and Fall 2019

Neural Dialogue

Speech Processing
CS 11-492 11-692 11-892, Carnegie Mellon University, Fall 2017, 2018, and Fall 2019

Building an Alexa Skill

Speech Processing
CS 11-492 11-692 11-892, Carnegie Mellon University, Fall 2017, 2018, and Fall 2019

Chatting with Computers Workshop
OurCS, Carnegie Mellon University, Fall 2017.

Teaching Assistant

Computational Ethics in NLP

CS 11-830, Carnegie Mellon University, Spring 2018

Speech Processing

CS 11-492 11-692 11-892, Carnegie Mellon University, Fall 2017