Mari Ostendorf

research

∙ 06/02/2023

Fine-Grained Human Feedback Gives Better Rewards for Language Model Training

Language models (LMs) often exhibit undesirable text generation behavior...

0 Zeqiu Wu, et al. ∙

research

∙ 10/06/2022

Binding Language Models in Symbolic Languages

Though end-to-end neural approaches have recently been dominating NLP ta...

2 Zhoujun Cheng, et al. ∙

research

∙ 09/20/2022

Generalizing through Forgetting – Domain Generalization for Symptom Event Extraction in Clinical Notes

Symptom information is primarily documented in free-text clinical notes ...

0 Sitong Zhou, et al. ∙

research

∙ 07/02/2022

INSCIT: Information-Seeking Conversations with Mixed-Initiative Interactions

In an information-seeking conversation, a user converses with an agent t...

0 Zeqiu Wu, et al. ∙

research

∙ 05/24/2022

Unsupervised Learning of Hierarchical Conversation Structure

Human conversations can evolve in many different ways, creating challeng...

11 Bo-Ru Lu, et al. ∙

research

∙ 04/03/2022

Automatic Dialect Density Estimation for African American English

In this paper, we explore automatic prediction of dialect density of the...

5 Alexander Johnson, et al. ∙

research

∙ 03/16/2022

In-Context Learning for Few-Shot Dialogue State Tracking

Collecting and annotating task-oriented dialogues is time-consuming and ...

0 Yushi Hu, et al. ∙

research

∙ 09/15/2021

Dialogue State Tracking with a Language Model using Schema-Driven Prompting

Task-oriented conversational systems often use dialogue state tracking t...

0 Chia-Hsuan Lee, et al. ∙

research

∙ 09/10/2021

DIALKI: Knowledge Identification in Conversational Systems through Dialogue-Document Contextualization

Identifying relevant knowledge to be used in conversational systems that...

0 Zeqiu Wu, et al. ∙

research

∙ 06/14/2021

Assessing the Use of Prosody in Constituency Parsing of Imperfect Transcripts

This work explores constituency parsing on automatically recognized tran...

0 Trang Tran, et al. ∙

research

∙ 01/26/2021

Representations for Question Answering from Documents with Tables and Text

Tables in Web documents are pervasive and can be directly used to answer...

0 Vicky Zayats, et al. ∙

research

∙ 12/02/2020

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 ...

0 Kevin Lybarger, et al. ∙

research

∙ 10/08/2020

Analysis of Disfluency in Children's Speech

Disfluencies are prevalent in spontaneous speech, as shown in many studi...

0 Trang Tran, et al. ∙

research

∙ 10/08/2020

On the Role of Style in Parsing Speech with Neural Models

The differences in written text and conversational speech are substantia...

0 Trang Tran, et al. ∙

research

∙ 09/19/2020

Extracting Summary Knowledge Graphs from Long Documents

Knowledge graphs capture entities and relations from long documents and ...

0 Zeqiu Wu, et al. ∙

research

∙ 05/01/2020

A Controllable Model of Grounded Response Generation

Current end-to-end neural conversation models inherently lack the flexib...

0 Zeqiu Wu, et al. ∙

research

∙ 04/11/2020

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...

0 Kevin Lybarger, et al. ∙

research

∙ 04/08/2019

Disfluencies and Human Speech Transcription Errors

This paper explores contexts associated with errors in transcrip-tion of...

0 Vicky Zayats, et al. ∙

research

∙ 04/08/2019

Giving Attention to the Unexpected: Using Prosody Innovations in Disfluency Detection

Disfluencies in spontaneous speech are known to be associated with proso...

0 Vicky Zayats, et al. ∙

research

∙ 04/05/2019

A General Framework for Information Extraction using Dynamic Span Graphs

We introduce a general framework for several information extraction task...

0 Yi Luan, et al. ∙

research

∙ 11/17/2018

Robust cross-domain disfluency detection with pattern match networks

In this paper we introduce a novel pattern match neural network architec...

0 Vicky Zayats, et al. ∙

research

∙ 08/29/2018

Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction

We introduce a multi-task setup of identifying and classifying entities,...

0 Yi Luan, et al. ∙

research

∙ 08/26/2018

Scientific Relation Extraction with Selectively Incorporated Concept Embeddings

This paper describes our submission for the SemEval 2018 Task 7 shared t...

0 Yi Luan, et al. ∙

research

∙ 06/07/2018

Domain Adversarial Training for Accented Speech Recognition

In this paper, we propose a domain adversarial training (DAT) algorithm ...

0 Sining Sun, et al. ∙

research

∙ 06/07/2018

Training Augmentation with Adversarial Examples for Robust Speech Recognition

This paper explores the use of adversarial examples in training speech r...

0 Sining Sun, et al. ∙

research

∙ 04/26/2018

Sounding Board: A User-Centric and Content-Driven Social Chatbot

We present Sounding Board, a social chatbot that won the 2017 Amazon Ale...

0 Hao Fang, et al. ∙

research

∙ 04/25/2018

Personalized Language Model for Query Auto-Completion

Query auto-completion is a search engine feature whereby the system sugg...

0 Aaron Jaech, et al. ∙

research

∙ 04/16/2018

Community Member Retrieval on Social Media using Textual Information

This paper addresses the problem of community membership detection using...

0 Aaron Jaech, et al. ∙

research

∙ 04/03/2018

Real-Time Prediction of the Duration of Distribution System Outages

This paper addresses the problem of predicting duration of unplanned pow...

0 Aaron Jaech, et al. ∙

research

∙ 10/06/2017

Low-Rank RNN Adaptation for Context-Aware Language Modeling

A context-aware language model uses location, user and/or domain metadat...

0 Aaron Jaech, et al. ∙

research

∙ 08/21/2017

Scientific Information Extraction with Semi-supervised Neural Tagging

This paper addresses the problem of extracting keyphrases from scientifi...

0 Yi Luan, et al. ∙

research

∙ 04/24/2017

Joint Modeling of Text and Acoustic-Prosodic Cues for Neural Parsing

In conversational speech, the acoustic signal provides cues that help li...

0 Trang Tran, et al. ∙

research

∙ 04/21/2017

Improving Context Aware Language Models

Increased adaptability of RNN language models leads to improved predicti...

0 Aaron Jaech, et al. ∙

research

∙ 04/20/2017

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...

0 Ji He, et al. ∙

research

∙ 04/07/2017

Conversation Modeling on Reddit using a Graph-Structured LSTM

This paper presents a novel approach for modeling threaded discussions o...

0 Vicky Zayats, et al. ∙

research

∙ 09/15/2016

Characterizing the Language of Online Communities and its Relation to Community Reception

This work investigates style and topic aspects of language in online com...

0 Trang Tran, et al. ∙

research

∙ 08/16/2016

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...

0 Hao Fang, et al. ∙

research

∙ 08/10/2016

Hierarchical Character-Word Models for Language Identification

Social media messages' brevity and unconventional spelling pose a challe...

0 Aaron Jaech, et al. ∙

research

∙ 06/12/2016

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...

0 Ji He, et al. ∙

research

∙ 04/12/2016

Disfluency Detection using a Bidirectional LSTM

We introduce a new approach for disfluency detection using a Bidirection...

0 Vicky Zayats, et al. ∙

research

∙ 04/01/2016

Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding

The goal of this paper is to use multi-task learning to efficiently scal...

0 Aaron Jaech, et al. ∙

research

∙ 03/31/2016

LSTM based Conversation Models

In this paper, we present a conversational model that incorporates both ...

0 Yi Luan, et al. ∙

research

∙ 11/14/2015

Deep Reinforcement Learning with a Natural Language Action Space

This paper introduces a novel architecture for reinforcement learning wi...

0 Ji He, et al. ∙

research

∙ 07/08/2015

Talking to the crowd: What do people react to in online discussions?

This paper addresses the question of how language use affects community ...

0 Aaron Jaech, et al. ∙

research

∙ 07/08/2015

What Your Username Says About You

Usernames are ubiquitous on the Internet, and they are often suggestive ...

0 Aaron Jaech, et al. ∙

research

∙ 04/09/2015

Leveraging Twitter for Low-Resource Conversational Speech Language Modeling

In applications involving conversational speech, data sparsity is a limi...

0 Aaron Jaech, et al. ∙

Mari Ostendorf

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