I am a
second third year PhD Student at the Center for Data Science at New York University where I am advised by Prof. He He. My research is broadly in the field of natural language processing and machine learning. I’m currently working on collaborative text generation for creative writing tasks and other interactive settings. I also help organize the NYU NLP and Text-as-Data talk series.
Prior to this, I completed my MS in Computer Science at NYU’s Courant Institute of Mathematical Sciences during which I was a Graduate Research Associate at the Center for Social Media and Politics working on political stance classification and multimodel content sharing in online disinformation campaigns. I also interned at LAER.AI in New York City where I did some work on unstructured document retrieval and active learning.
I did my undergrad at the National Institute of Technology - Karnataka where my thesis was advised by Prof. Sowmya Kamath.
Here’s my CV and Google Scholar page. Head over to my personal blog for more light hearted content. All the other relevant links are in the footer. You can contact me at firstname.lastname@example.org.
Extrapolative Controlled Sequence Generation via Iterative Refinement
Vishakh Padmakumar*, Richard Yuanzhe Pang, He He, Ankur P. Parikh
Help me write a Poem - Instruction Tuning as a Vehicle for Collaborative Poetry Writing
Tuhin Chakrabarty*, Vishakh Padmakumar*, He He
Machine-in-the-Loop Rewriting for Creative Image Captioning
Vishakh Padmakumar, He He
Previously presented at Novel Ideas in Learning-to-Learn through Interaction - Workshop @ EMNLP 2021
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
QuALITY: Question Answering with Long Input Texts, Yes!
Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He and Sam Bowman
BBQ: A Hand-Built Bias Benchmark for Question Answering
Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Thompson, Phu Mon Htut, Samuel R. Bowman
ACL Findings 2022
Unsupervised Extractive Summarization with Mutual Information
Vishakh Padmakumar, He He
A comparison of methods in political science text classification: Transfer learning language models for politics
Zhanna Terechshenko, Fridolin Linder, Vishakh Padmakumar, Michael Liu, Jonathan Nagler, Josh Tucker, Richard Bonneau
Multi-Modal Content Similarities in Online Disinformation Campaigns
Cody Buntain, Vishakh Padmakumar, Richard Bonneau, Jonathan Nagler, Josh Tucker
ACM Conference on Collective Intelligence, 2020
A Robust Approach to Open Vocabulary Image Retrieval with Deep Convolutional Neural Networks and Transfer Learning
Vishakh Padmakumar, Rishab Ranga, Srivalya Elluru, Sowmya Kamath S.
2018 Pacific Neighborhood Consortium Annual Conference and Joint Meetings (PNC), IEEE
Counterfactual Logit Pairing with Asymmetric Counterfactuals in Text Classification
Lucius Bynum, Vishakh Padmakumar
Transfer of Reinforcement Learning in a Natural Language Action Space
Vishakh Padmakumar, Francesco Preta