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Tuhin Chakrabarty

Ph.D. Student in CS @ Columbia

Hey there!

I am a PhD student in Computer Science at Columbia University. Within the department I am a part of the Natural Language Processing group , where I am advised by Smaranda Muresan .I also work with Violet Peng and Kathleen Mckeown. My research interests are broadly in Natural Language Processing and Machine Learning, with special focus in Creative language generation (both at sentence level and Long Form), Role Of Structured Common sense in Language Generation and teaching machines how to think critically in the realms of Discourse and Argumentation (Understanding and Generation). Prior to joining Grad school I was an engineer at UBER. For more information about me, see my CV or contact me.
I am happy to advise undergrads and master students about grad school applications, how to get involved in NLP research. If you are at Columbia and want to work with me , please send me an email.


Columbia University

Ph.D. in Computer Science

Columbia University

M.S. in Computer Science

Jadavpur University

Bachelors of Engineering in Computer Science

Professional Experience

Amazon Alexa

Applied Scientist Intern

UBER (Revenue Team)

Machine Learning Engineer

For more details, please see my full CV (PDF).



Generating similes effortlessly like a Pro : A Style Transfer Approach for Simile Generation

Tuhin Chakrabarty , Smaranda Muresan and Nanyun Peng
In Proceedings of EMNLP 2020 ,Punta Cana, Dominican Republic.
Tags: Creative Language Generation, Figurative Langugage, Computational Creativity

Content Planning for Neural Story Generation with Aristotelian Rescoring

Seraphina Goldfarb-Tarrant, Tuhin Chakrabarty , Ralph Weischedel and Nanyun Peng
In Proceedings of EMNLP 2020 ,Punta Cana, Dominican Republic.
Tags: Creative Language Generation, Narrative, Computational Creativity

R^3: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledge

Tuhin Chakrabarty , Debanjan Ghosh, Smaranda Muresan and Nanyun Peng
In Proceedings of ACL 2020 ,Seattle, WA.
Tags: Creative Language Generation, Figurative Langugage, Computational Creativity

DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking

Christopher Hidey, Tuhin Chakrabarty , Tariq Alhindi, Siddharth Varia, Kriste Krstovski, Mona Diab and Smaranda Muresan.
In Proceedings of ACL 2020 ,Seattle, WA.
Tags: Fact Checking, Discourse, Argumentation


AMPERSAND: Argument Mining for PERSuAsive oNline Discussions

Tuhin Chakrabarty , Christopher Hidey, Smaranda Muresan, Kathy McKeown and Alyssa Hwang.
In Proceedings of EMNLP 2019 ,Hong Kong.
Tags: Discourse, Argumentation

IMHO Fine Tuning Improves Claim Detection

Tuhin Chakrabarty , Christopher Hidey and Kathy McKeown.
In Proceedings of NAACL 2019 ,Minneapolis, MN.
Tags: Discourse, Argumentation

Discourse Relation Prediction: Revisiting Word Pairs with Convolutional Networks

Siddharth Varia ,Christopher Hidey, Tuhin Chakrabarty
In Proceedings of SIGDIAL 2019 ,Stockholm, Sweden
[PDF] [Code] [Slides]
Tags: , Discourse

Pay "Attention'' to your Context when Classifying Abusive Language

Tuhin Chakrabarty ,Kilol Gupta, Smaranda Muresan.
In Proceedings of 3rd Abusive Language Workshop ,ACL 2019 Florence, Italy.
[PDF] [Code]
Tags: NLP For Social Good

The Answer is Language Model Fine-tuning

Tuhin Chakrabarty ,Smaranda Muresan.
In Proceedings of the 13th International Workshop on Semantic Evaluation , NAACL-HLT , Minneapolis, USA, June 2019
Tags: Discourse, Argumentation


Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification

Tuhin Chakrabarty ,Tariq Alhindi , Smaranda Muresan
In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER) ,EMNLP ,Brussels ,2018
[PDF] [Code]


E-mail: <x>, where x=tuhin.chakr.
The Interchurch Center 61 Claremont Avenue, Data Science Institute , 3rd floor (map).