activity
20092022
most citedEfficient Domain Generalization via Common-Specific Low-Rank Decomposition

57 citations · 148 across the 16 of their papers we have counts for

collaborators

23 papers

cs.CL20221 cited

Diverse Parallel Data Synthesis for Cross-Database Adaptation of Text-to-SQL Parsers

Abhijeet Awasthi, Ashutosh Sathe, Sunita Sarawagi

Text-to-SQL parsers typically struggle with databases unseen during the train time. Adapting parsers to new databases is a challenging problem due to the lack of natural language q…

cs.CL2022

Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding

Soumya Chatterjee, Sunita Sarawagi, Preethi Jyothi

Online alignment in machine translation refers to the task of aligning a target word to a source word when the target sequence has only been partially decoded. Good online alignmen…

cs.CL2022

Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related Languages

Vaidehi Patil, Partha Talukdar, Sunita Sarawagi

Pre-trained multilingual language models such as mBERT and XLM-R have demonstrated great potential for zero-shot cross-lingual transfer to low web-resource languages (LRL). However…

cs.CL2022

Adaptive Discounting of Implicit Language Models in RNN-Transducers

Vinit Unni, Shreya Khare, Ashish Mittal +3

RNN-Transducer (RNN-T) models have become synonymous with streaming end-to-end ASR systems. While they perform competitively on a number of evaluation categories, rare words pose a…

cs.LG2021

Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations

Vihari Piratla, Soumen Chakrabarty, Sunita Sarawagi

Our goal is to evaluate the accuracy of a black-box classification model, not as a single aggregate on a given test data distribution, but as a surface over a large number of combi…

cs.CL2021

Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages Study

Yash Khemchandani, Sarvesh Mehtani, Vaidehi Patil +3

Recent research in multilingual language models (LM) has demonstrated their ability to effectively handle multiple languages in a single model. This holds promise for low web-resou…