Sunita Sarawagi

research

∙ 07/11/2023

Improving RNN-Transducers with Acoustic LookAhead

RNN-Transducers (RNN-Ts) have gained widespread acceptance as an end-to-...

0 Vinit S. Unni, et al. ∙

research

∙ 01/10/2023

Structured Case-based Reasoning for Inference-time Adaptation of Text-to-SQL parsers

Inference-time adaptation methods for semantic parsing are useful for le...

0 Abhijeet Awasthi, et al. ∙

research

∙ 10/29/2022

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

Text-to-SQL parsers typically struggle with databases unseen during the ...

0 Abhijeet Awasthi, et al. ∙

research

∙ 10/13/2022

Bootstrapping Multilingual Semantic Parsers using Large Language Models

Despite cross-lingual generalization demonstrated by pre-trained multili...

0 Abhijeet Awasthi, et al. ∙

research

∙ 04/02/2022

Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding

Online alignment in machine translation refers to the task of aligning a...

0 Soumya Chatterjee, et al. ∙

research

∙ 03/03/2022

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

Pre-trained multilingual language models such as mBERT and XLM-R have de...

0 Vaidehi Patil, et al. ∙

research

∙ 02/21/2022

Adaptive Discounting of Implicit Language Models in RNN-Transducers

RNN-Transducer (RNN-T) models have become synonymous with streaming end-...

0 Vinit Unni, et al. ∙

research

∙ 11/05/2021

Long Range Probabilistic Forecasting in Time-Series using High Order Statistics

Long range forecasts are the starting point of many decision support sys...

0 Prathamesh Deshpande, et al. ∙

research

∙ 10/06/2021

Focus on the Common Good: Group Distributional Robustness Follows

We consider the problem of training a classification model with group an...

2 Vihari Piratla, et al. ∙

research

∙ 08/15/2021

Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time

In several real world applications, machine learning models are deployed...

0 Anshul Nasery, et al. ∙

research

∙ 08/14/2021

Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations

Our goal is to evaluate the accuracy of a black-box classification model...

0 Vihari Piratla, et al. ∙

research

∙ 06/07/2021

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

Recent research in multilingual language models (LM) has demonstrated th...

0 Yash Khemchandani, et al. ∙

research

∙ 04/08/2021

Deep Indexed Active Learning for Matching Heterogeneous Entity Representations

Given two large lists of records, the task in entity resolution (ER) is ...

0 Arjit Jain, et al. ∙

research

∙ 03/04/2021

Error-driven Fixed-Budget ASR Personalization for Accented Speakers

We consider the task of personalizing ASR models while being constrained...

0 Abhijeet Awasthi, et al. ∙

research

∙ 03/02/2021

Missing Value Imputation on Multidimensional Time Series

We present DeepMVI, a deep learning method for missing value imputation ...

0 Parikshit Bansal, et al. ∙

research

∙ 01/08/2021

Long Horizon Forecasting With Temporal Point Processes

In recent years, marked temporal point processes (MTPPs) have emerged as...

0 Prathamesh Deshpande, et al. ∙

research

∙ 10/04/2020

NLP Service APIs and Models for Efficient Registration of New Clients

State-of-the-art NLP inference uses enormous neural architectures and mo...

0 Sahil Shah, et al. ∙

research

∙ 07/14/2020

What's in a Name? Are BERT Named Entity Representations just as Good for any other Name?

We evaluate named entity representations of BERT-based NLP models by inv...

0 Sriram Balasubramanian, et al. ∙

research

∙ 06/24/2020

Black-box Adaptation of ASR for Accented Speech

We introduce the problem of adapting a black-box, cloud-based ASR system...

0 Kartik Khandelwal, et al. ∙

research

∙ 04/13/2020

Learning from Rules Generalizing Labeled Exemplars

In many applications labeled data is not readily available, and needs to...

0 Abhijeet Awasthi, et al. ∙

research

∙ 03/28/2020

Efficient Domain Generalization via Common-Specific Low-Rank Decomposition

Domain generalization refers to the task of training a model which gener...

0 Vihari Piratla, et al. ∙

research

∙ 11/22/2019

Data Programming using Continuous and Quality-Guided Labeling Functions

Scarcity of labeled data is a bottleneck for supervised learning models....

0 Oishik Chatterjee, et al. ∙

research

∙ 10/07/2019

Parallel Iterative Edit Models for Local Sequence Transduction

We present a Parallel Iterative Edit (PIE) model for the problem of loca...

0 Abhijeet Awasthi, et al. ∙

research

∙ 06/24/2019

Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units

We present ARU, an Adaptive Recurrent Unit for streaming adaptation of d...

0 Prathamesh Deshpande, et al. ∙

research

∙ 06/05/2019

Topic Sensitive Attention on Generic Corpora Corrects Sense Bias in Pretrained Embeddings

Given a small corpus D_T pertaining to a limited set of focused topics,...

0 Vihari Piratla, et al. ∙

research

∙ 03/03/2019

Calibration of Encoder Decoder Models for Neural Machine Translation

We study the calibration of several state of the art neural machine tran...

0 Aviral Kumar, et al. ∙

research

∙ 04/28/2018

Generalizing Across Domains via Cross-Gradient Training

We present CROSSGRAD, a method to use multi-domain training data to lear...

0 Shiv Shankar, et al. ∙

research

∙ 03/10/2018

ARMDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting

Accurate demand forecasts can help on-line retail organizations better p...

0 Srayanta Mukherjee, et al. ∙

research

∙ 07/05/2017

Labeled Memory Networks for Online Model Adaptation

Augmenting a neural network with memory that can grow without growing th...

0 Shiv Shankar, et al. ∙

research

∙ 06/10/2016

Length bias in Encoder Decoder Models and a Case for Global Conditioning

Encoder-decoder networks are popular for modeling sequences probabilisti...

0 Pavel Sountsov, et al. ∙

research

∙ 05/14/2016

Occurrence Statistics of Entities, Relations and Types on the Web

The problem of collecting reliable estimates of occurrence of entities o...

0 Aman Madaan, et al. ∙

research

∙ 05/01/2010

Joint Structured Models for Extraction from Overlapping Sources

We consider the problem of jointly training structured models for extrac...

0 Rahul Gupta, et al. ∙

research

∙ 07/03/2009

Generalized Collective Inference with Symmetric Clique Potentials

Collective graphical models exploit inter-instance associative dependenc...

0 Rahul Gupta, et al. ∙

Sunita Sarawagi

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