Jonathan K. Kummerfeld | DeepAI

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∙ 05/12/2023

Interactive Text-to-SQL Generation via Editable Step-by-Step Explanations

Relational databases play an important role in this Big Data era. Howeve...

0 Yuan Tian, et al. ∙

∙ 10/24/2022

Augmenting Task-Oriented Dialogue Systems with Relation Extraction

The standard task-oriented dialogue pipeline uses intent classification ...

0 Andrew Lee, et al. ∙

∙ 07/12/2022

Using Paraphrases to Study Properties of Contextual Embeddings

We use paraphrases as a unique source of data to analyze contextualized ...

4 Laura Burdick, et al. ∙

∙ 09/28/2021

Micromodels for Efficient, Explainable, and Reusable Systems: A Case Study on Mental Health

Many statistical models have high accuracy on test benchmarks, but are n...

0 Andrew Lee, et al. ∙

∙ 06/24/2021

Exploring Self-Identified Counseling Expertise in Online Support Forums

A growing number of people engage in online health forums, making it imp...

2 Allison Lahnala, et al. ∙

∙ 05/26/2021

Quantifying and Avoiding Unfair Qualification Labour in Crowdsourcing

Extensive work has argued in favour of paying crowd workers a wage that ...

0 Jonathan K. Kummerfeld, et al. ∙

∙ 02/04/2021

Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction

Natural language processing methods have been applied in a variety of mu...

4 Allison Lahnala, et al. ∙

∙ 11/11/2020

Exploring the Value of Personalized Word Embeddings

In this paper, we introduce personalized word embeddings, and examine th...

4 Charles Welch, et al. ∙

∙ 10/06/2020

Compositional Demographic Word Embeddings

Word embeddings are usually derived from corpora containing text from ma...

7 Charles Welch, et al. ∙

∙ 09/29/2020

Improving Low Compute Language Modeling with In-Domain Embedding Initialisation

Many NLP applications, such as biomedical data and technical support, ha...

0 Charles Welch, et al. ∙

∙ 04/30/2020

Analyzing the Surprising Variability in Word Embedding Stability Across Languages

Word embeddings are powerful representations that form the foundation of...

0 Laura Burdick, et al. ∙

∙ 11/14/2019

The Eighth Dialog System Technology Challenge

This paper introduces the Eighth Dialog System Technology Challenge. In ...

0 Seokhwan Kim, et al. ∙

∙ 09/04/2019

No Press Diplomacy: Modeling Multi-Agent Gameplay

Diplomacy is a seven-player non-stochastic, non-cooperative game, where ...

4 Philip Paquette, et al. ∙

∙ 09/04/2019

An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction

Task-oriented dialog systems need to know when a query falls outside the...

0 Stefan Larson, et al. ∙

∙ 07/18/2019

SLATE: A Super-Lightweight Annotation Tool for Experts

Many annotation tools have been developed, covering a wide variety of ta...

0 Jonathan K. Kummerfeld, et al. ∙

∙ 04/25/2019

Look Who's Talking: Inferring Speaker Attributes from Personal Longitudinal Dialog

We examine a large dialog corpus obtained from the conversation history ...

2 Charles Welch, et al. ∙

∙ 04/05/2019

Outlier Detection for Improved Data Quality and Diversity in Dialog Systems

In a corpus of data, outliers are either errors: mistakes in the data th...

0 Stefan Larson, et al. ∙

∙ 01/11/2019

Dialog System Technology Challenge 7

This paper introduces the Seventh Dialog System Technology Challenges (D...

0 Koichiro Yoshino, et al. ∙

∙ 10/25/2018

Analyzing Assumptions in Conversation Disentanglement Research Through the Lens of a New Dataset and Model

Disentangling conversations mixed together in a single stream of message...

0 Jonathan K. Kummerfeld, et al. ∙

∙ 06/23/2018

Improving Text-to-SQL Evaluation Methodology

To be informative, an evaluation must measure how well systems generaliz...

8 Catherine Finegan-Dollak, et al. ∙

∙ 04/25/2018

Factors Influencing the Surprising Instability of Word Embeddings

Despite the recent popularity of word embedding methods, there is only a...

0 Laura Wendlandt, et al. ∙

∙ 08/31/2017

Identifying Products in Online Cybercrime Marketplaces: A Dataset for Fine-grained Domain Adaptation

One weakness of machine-learned NLP models is that they typically perfor...

0 Greg Durrett, et al. ∙

∙ 07/13/2017

Parsing with Traces: An O(n^4) Algorithm and a Structural Representation

General treebank analyses are graph structured, but parsers are typicall...

0 Jonathan K. Kummerfeld, et al. ∙

∙ 04/19/2017

Understanding Task Design Trade-offs in Crowdsourced Paraphrase Collection

Linguistically diverse datasets are critical for training and evaluating...

0 Youxuan Jiang, et al. ∙

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