I am broadly interested in Natural Language Processing, Speech Recognition and Machine Learning Security & Privacy.
Hurdles to Progress in Long-form Question Answering
Kalpesh Krishna, Aurko Roy, Mohit Iyyer
blog // external summaries: video1, video2, VentureBeat, Ruder’s newsletter, MarkTechPost, TechStory
Reformulating Unsupervised Style Transfer as Paraphrase Generation
Kalpesh Krishna, John Wieting, Mohit Iyyer
project page (demo + code + data + slides + talk video) // external video
Thieves on Sesame Street! Model Extraction of BERT-based APIs
Kalpesh Krishna, Gaurav Singh Tomar, Ankur P. Parikh, Nicolas Papernot, Mohit Iyyer
blog // project page (code + slides + Twitter + external coverage)
Weakly-Supervised Open-Retrieval Conversational Question Answering
Chen Qu, Liu Yang, Cen Chen, W. Bruce Croft, Kalpesh Krishna and Mohit Iyyer
An Analysis of Frame-skipping in Reinforcement Learning
Shivaram Kalyanakrishnan, Siddharth Aravindan, Vishwajeet Bagdawat, Varun Bhatt, Harshith Goka, Archit Gupta, Kalpesh Krishna, Vihari Piratla
Long Document Summarization in a Low Resource Setting using Pretrained Language Models
Ahsaas Bajaj*, Pavitra Dangati*, Kalpesh Krishna, Pradhiksha Ashok Kumar, Rheeya Uppaal, Bradford Windsor, Eliot Brenner, Dominic Dotterrer, Rajarshi Das and Andrew McCallum
SunPy: A Python package for Solar Physics
Stuart J. Mumford and others
Syntactically Supervised Transformers for Faster Neural Machine Translation
Nader Akoury, Kalpesh Krishna, Mohit Iyyer
code // poster
Trick or TReAT: Thematic Reinforcement for Artistic Typography
Purva Tendulkar, Kalpesh Krishna, Ramprasaath R. Selvaraju, Devi Parikh
ICCC 2019 (oral presentation, Best Presentation Award)
code // slides // video // demo
Revisiting the Importance of Encoding Logic Rules in Sentiment Classification
Kalpesh Krishna, Preethi Jyothi, Mohit Iyyer
EMNLP 2018 (oral presentation, short paper)
code + data // slides // video
Hierarchical Multitask Learning for CTC-based Speech Recognition
Kalpesh Krishna, Shubham Toshniwal, Karen Livescu
A Study of All-Convolutional Encoders for Connectionist Temporal Classification
Kalpesh Krishna, Liang Lu, Kevin Gimpel, Karen Livescu
ICASSP 2018 (Awarded SPS Travel Grant)
Main Collaborators (in order of publication date): Karen Livescu, Kevin Gimpel, Liang Lu, Shubham Toshniwal, Preethi Jyothi, Mohit Iyyer, Purva Tendulkar, Ramprasaath R. Selvaraju, Devi Parikh, Nader Akoury, Gaurav Singh Tomar, Ankur P. Parikh, Nicolas Papernot, John Wieting, Aurko Roy
Other Research (Course Projects)
MixMatch on Vision + Language Tasks (NLVR2): An attempt to integrate the MixMatch data augmentation algorithm for semi-supervised image classification to the challenging setting of NLVR2, where the input space has both images and text (report).
Research Exchange - A Collaborative Paper Annotation Tool - A platform to collaboratively annotate scientific literature to help newcomers understand research papers, built during an Human Computer Interaction course project (report).
Inference Networks for Structured Prediction - A TensorFlow implementation for the multi-label classification experiments in Learning Approximate Inference Networks for Structured Prediction. Also contains experiments on the FIGMENT dataset and a extension to Inference Network training algorithm based on Wasserstein GANs (report).
Diversity Sampling in Machine Learning - An implementation of Diverse Beam Search for Neural Networks in Language Modelling. Also contains the original (slightly modified code) for the interactive segmentation experiments in Diverse M-Best Solutions in MRFs (report).
Macro Actions in Reinforcement Learning - A suite of five algorithms (including ideas from “Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning”) encouraging agents to repeat actions (report).
Single Image Haze Removal - An implementation of He et al. 2009, “Single Image Haze Removal using Dark Channel Prior” and an ongoing implementation of Bahat & Irani 2016, “Blind Dehazing using Internal Patch Recurrence” (report).
CNNs for Sentence Classification - A TensorFlow 1.1 implementation of Kim 2014, “Convolutional Neural Networks for Sentence Classification”.
Brittle Fracture Simulation - Python implementation of O’Brien and Hodgins 1999, “Graphical Modeling and Animation of Brittle Fracture”.
ECG Signal Analysis - Python implementation of parts of Christopher Buck, Aneesh Sampath 2013, “ECG Signal Analysis for Myocardial Infarction Detection.”.
Indian Language Datasets
As a part of my RnD project at IIT Bombay, I am releasing the dataset used to train my neural network language models. These have been mined from Wikipedia and I hope this will help further research in language modelling for Indian morphologically rich languages. The folder also contains the original PTB dataset.
- Malayalam (denoted by
- Tamil (denoted by
- Kannada (denoted by
- Telugu (denoted by
- Hindi (denoted by
- PTB (denoted by
All these datasets are compatible with SRILM. Files marked with
unk have replaced all singletons with
<unk> tokens. Files marked with
char are character versions. All datasets have a
test file. You will find the dataset here.