20 citations · 27 across the 4 of their papers we have counts for
5 papers
From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction
Robert Vacareanu, Marco A. Valenzuela-Escarcega, George C. G. Barbosa +2
While deep learning approaches to information extraction have had many successes, they can be difficult to augment or maintain as needs shift. Rule-based methods, on the other hand…
AutoMATES: Automated Model Assembly from Text, Equations, and Software
Adarsh Pyarelal, Marco A. Valenzuela-Escarcega, Rebecca Sharp +6
Models of complicated systems can be represented in different ways - in scientific papers, they are represented using natural language text as well as equations. But to be of real…
On the Importance of Delexicalization for Fact Verification
Sandeep Suntwal, Mithun Paul, Rebecca Sharp +1
In this work we aim to understand and estimate the importance that a neural network assigns to various aspects of the data while learning and making predictions. Here we focus on t…
Sanity Check: A Strong Alignment and Information Retrieval Baseline for Question Answering
Vikas Yadav, Rebecca Sharp, Mihai Surdeanu
While increasingly complex approaches to question answering (QA) have been proposed, the true gain of these systems, particularly with respect to their expensive training requireme…
Creating Causal Embeddings for Question Answering with Minimal Supervision
Rebecca Sharp, Mihai Surdeanu, Peter Jansen +2
A common model for question answering (QA) is that a good answer is one that is closely related to the question, where relatedness is often determined using general-purpose lexical…