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06/14/2023
Recipes for Sequential Pre-training of Multilingual Encoder and Seq2Seq Models
Pre-trained encoder-only and sequence-to-sequence (seq2seq) models each ...
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04/04/2023
Scalable and Accurate Self-supervised Multimodal Representation Learning without Aligned Video and Text Data
Scaling up weakly-supervised datasets has shown to be highly effective i...
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01/24/2023
Low-Resource Compositional Semantic Parsing with Concept Pretraining
Semantic parsing plays a key role in digital voice assistants such as Al...
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10/13/2022
CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing
A bottleneck to developing Semantic Parsing (SP) models is the need for ...
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09/20/2022
LINGUIST: Language Model Instruction Tuning to Generate Annotated Utterances for Intent Classification and Slot Tagging
We present LINGUIST, a method for generating annotated data for Intent C...
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08/02/2022
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model
In this work, we demonstrate that multilingual large-scale sequence-to-s...
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06/15/2022
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems
We present results from a large-scale experiment on pretraining encoders...
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04/29/2022
Training Naturalized Semantic Parsers with Very Little Data
Semantic parsing is an important NLP problem, particularly for voice ass...
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04/28/2022
Instilling Type Knowledge in Language Models via Multi-Task QA
Understanding human language often necessitates understanding entities a...
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01/20/2021
Zero-shot Generalization in Dialog State Tracking through Generative Question Answering
Dialog State Tracking (DST), an integral part of modern dialog systems, ...
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12/15/2020
Exploring Transfer Learning For End-to-End Spoken Language Understanding
Voice Assistants such as Alexa, Siri, and Google Assistant typically use...
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12/04/2020
Delexicalized Paraphrase Generation
We present a neural model for paraphrasing and train it to generate dele...
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10/09/2020
Style Attuned Pre-training and Parameter Efficient Fine-tuning for Spoken Language Understanding
Neural models have yielded state-of-the-art results in deciphering spoke...
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10/08/2020
Don't Parse, Insert: Multilingual Semantic Parsing with Insertion Based Decoding
Semantic parsing is one of the key components of natural language unders...
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01/30/2020
Don't Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsing
Virtual assistants such as Amazon Alexa, Apple Siri, and Google Assistan...
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01/11/2020
Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses
In a modern spoken language understanding (SLU) system, the natural lang...
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06/26/2018
Neural Cross-Lingual Coreference Resolution and its Application to Entity Linking
We propose an entity-centric neural cross-lingual coreference model that...
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12/05/2017
Neural Cross-Lingual Entity Linking
A major challenge in Entity Linking (EL) is making effective use of cont...
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09/04/2017
A Unified Query-based Generative Model for Question Generation and Question Answering
We propose a query-based generative model for solving both tasks of ques...
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08/25/2017
k-Nearest Neighbor Augmented Neural Networks for Text Classification
In recent years, many deep-learning based models are proposed for text c...
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03/13/2017
Reinforcement Learning for Transition-Based Mention Detection
This paper describes an application of reinforcement learning to the men...
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02/13/2017
Bilateral Multi-Perspective Matching for Natural Language Sentences
Natural language sentence matching is a fundamental technology for a var...
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12/13/2016
