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07/11/2023
Improving RNN-Transducers with Acoustic LookAhead
RNN-Transducers (RNN-Ts) have gained widespread acceptance as an end-to-...
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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...
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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 ...
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10/13/2022
Bootstrapping Multilingual Semantic Parsers using Large Language Models
Despite cross-lingual generalization demonstrated by pre-trained multili...
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04/02/2022
Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding
Online alignment in machine translation refers to the task of aligning a...
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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...
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02/21/2022
Adaptive Discounting of Implicit Language Models in RNN-Transducers
RNN-Transducer (RNN-T) models have become synonymous with streaming end-...
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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...
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10/06/2021
Focus on the Common Good: Group Distributional Robustness Follows
We consider the problem of training a classification model with group an...
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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...
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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...
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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...
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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 ...
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03/04/2021
Error-driven Fixed-Budget ASR Personalization for Accented Speakers
We consider the task of personalizing ASR models while being constrained...
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03/02/2021
Missing Value Imputation on Multidimensional Time Series
We present DeepMVI, a deep learning method for missing value imputation ...
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01/08/2021
Long Horizon Forecasting With Temporal Point Processes
In recent years, marked temporal point processes (MTPPs) have emerged as...
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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...
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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...
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06/24/2020
Black-box Adaptation of ASR for Accented Speech
We introduce the problem of adapting a black-box, cloud-based ASR system...
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04/13/2020
Learning from Rules Generalizing Labeled Exemplars
In many applications labeled data is not readily available, and needs to...
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03/28/2020
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Domain generalization refers to the task of training a model which gener...
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11/22/2019
Data Programming using Continuous and Quality-Guided Labeling Functions
Scarcity of labeled data is a bottleneck for supervised learning models....
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10/07/2019
Parallel Iterative Edit Models for Local Sequence Transduction
We present a Parallel Iterative Edit (PIE) model for the problem of loca...
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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...
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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,...
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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...
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04/28/2018
Generalizing Across Domains via Cross-Gradient Training
We present CROSSGRAD, a method to use multi-domain training data to lear...
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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...
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07/05/2017
Labeled Memory Networks for Online Model Adaptation
Augmenting a neural network with memory that can grow without growing th...
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06/10/2016
Length bias in Encoder Decoder Models and a Case for Global Conditioning
Encoder-decoder networks are popular for modeling sequences probabilisti...
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05/14/2016
Occurrence Statistics of Entities, Relations and Types on the Web
The problem of collecting reliable estimates of occurrence of entities o...
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05/01/2010
Joint Structured Models for Extraction from Overlapping Sources
We consider the problem of jointly training structured models for extrac...
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07/03/2009