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Extracting COVID-19 Diagnoses and Symptoms From Clinical Text: A New Annotated Corpus and Neural Event Extraction Framework
Coronavirus disease 2019 (COVID-19) is a global pandemic. Although much ...
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Analysis of Disfluency in Children's Speech
Disfluencies are prevalent in spontaneous speech, as shown in many studi...
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On the Role of Style in Parsing Speech with Neural Models
The differences in written text and conversational speech are substantia...
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Extracting Summary Knowledge Graphs from Long Documents
Knowledge graphs capture entities and relations from long documents and ...
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A Controllable Model of Grounded Response Generation
Current end-to-end neural conversation models inherently lack the flexib...
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Annotating Social Determinants of Health Using Active Learning, and Characterizing Determinants Using Neural Event Extraction
Social determinants of health (SDOH) affect health outcomes, and knowled...
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Disfluencies and Human Speech Transcription Errors
This paper explores contexts associated with errors in transcrip-tion of...
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Giving Attention to the Unexpected: Using Prosody Innovations in Disfluency Detection
Disfluencies in spontaneous speech are known to be associated with proso...
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A General Framework for Information Extraction using Dynamic Span Graphs
We introduce a general framework for several information extraction task...
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Robust cross-domain disfluency detection with pattern match networks
In this paper we introduce a novel pattern match neural network architec...
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Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction
We introduce a multi-task setup of identifying and classifying entities,...
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Scientific Relation Extraction with Selectively Incorporated Concept Embeddings
This paper describes our submission for the SemEval 2018 Task 7 shared t...
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Domain Adversarial Training for Accented Speech Recognition
In this paper, we propose a domain adversarial training (DAT) algorithm ...
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Training Augmentation with Adversarial Examples for Robust Speech Recognition
This paper explores the use of adversarial examples in training speech r...
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Sounding Board: A User-Centric and Content-Driven Social Chatbot
We present Sounding Board, a social chatbot that won the 2017 Amazon Ale...
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Personalized Language Model for Query Auto-Completion
Query auto-completion is a search engine feature whereby the system sugg...
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Community Member Retrieval on Social Media using Textual Information
This paper addresses the problem of community membership detection using...
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Real-Time Prediction of the Duration of Distribution System Outages
This paper addresses the problem of predicting duration of unplanned pow...
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Low-Rank RNN Adaptation for Context-Aware Language Modeling
A context-aware language model uses location, user and/or domain metadat...
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Scientific Information Extraction with Semi-supervised Neural Tagging
This paper addresses the problem of extracting keyphrases from scientifi...
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Joint Modeling of Text and Acoustic-Prosodic Cues for Neural Parsing
In conversational speech, the acoustic signal provides cues that help li...
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Improving Context Aware Language Models
Increased adaptability of RNN language models leads to improved predicti...
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Reinforcement Learning with External Knowledge and Two-Stage Q-functions for Predicting Popular Reddit Threads
This paper addresses the problem of predicting popularity of comments in...
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Conversation Modeling on Reddit using a Graph-Structured LSTM
This paper presents a novel approach for modeling threaded discussions o...
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Characterizing the Language of Online Communities and its Relation to Community Reception
This work investigates style and topic aspects of language in online com...
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Learning Latent Local Conversation Modes for Predicting Community Endorsement in Online Discussions
Many social media platforms offer a mechanism for readers to react to co...
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Hierarchical Character-Word Models for Language Identification
Social media messages' brevity and unconventional spelling pose a challe...
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Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads
We introduce an online popularity prediction and tracking task as a benc...
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Disfluency Detection using a Bidirectional LSTM
We introduce a new approach for disfluency detection using a Bidirection...
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Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding
The goal of this paper is to use multi-task learning to efficiently scal...
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LSTM based Conversation Models
In this paper, we present a conversational model that incorporates both ...
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Deep Reinforcement Learning with a Natural Language Action Space
This paper introduces a novel architecture for reinforcement learning wi...
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Talking to the crowd: What do people react to in online discussions?
This paper addresses the question of how language use affects community ...
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What Your Username Says About You
Usernames are ubiquitous on the Internet, and they are often suggestive ...
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Leveraging Twitter for Low-Resource Conversational Speech Language Modeling
In applications involving conversational speech, data sparsity is a limi...
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