activity
20132017
most citedInteractive Knowledge Base Population

4 citations · 4 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2017

Feature Generation for Robust Semantic Role Labeling

Travis Wolfe, Mark Dredze, Benjamin Van Durme

Hand-engineered feature sets are a well understood method for creating robust NLP models, but they require a lot of expertise and effort to create. In this work we describe how to…

cs.CL2017

Harmonic Grammar, Optimality Theory, and Syntax Learnability: An Empirical Exploration of Czech Word Order

Ann Irvine, Mark Dredze

This work presents a systematic theoretical and empirical comparison of the major algorithms that have been proposed for learning Harmonic and Optimality Theory grammars (HG and OT…

cs.SI2016

Twitter as a Source of Global Mobility Patterns for Social Good

Mark Dredze, Manuel García-Herranz, Alex Rutherford +1

Data on human spatial distribution and movement is essential for understanding and analyzing social systems. However existing sources for this data are lacking in various ways; dif…

cs.CL2016

Embedding Lexical Features via Low-Rank Tensors

Mo Yu, Mark Dredze, Raman Arora +1

Modern NLP models rely heavily on engineered features, which often combine word and contextual information into complex lexical features. Such combination results in large numbers…

cs.AI20154 cited

Interactive Knowledge Base Population

Travis Wolfe, Mark Dredze, James Mayfield +4

Most work on building knowledge bases has focused on collecting entities and facts from as large a collection of documents as possible. We argue for and describe a new paradigm whe…

cs.CL2013

Estimating Confusions in the ASR Channel for Improved Topic-based Language Model Adaptation

Damianos Karakos, Mark Dredze, Sanjeev Khudanpur

Human language is a combination of elemental languages/domains/styles that change across and sometimes within discourses. Language models, which play a crucial role in speech recog…