Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Adversarial Removal of Demographic Attributes from Text Data
Recent advances in Representation Learning and Adversarial Training seem to succeed in removing unwanted features from the learned representation. We show that demographic information of authors is…
Can LSTM Learn to Capture Agreement? The Case of Basque
Sequential neural networks models are powerful tools in a variety of Natural Language Processing (NLP) tasks. The sequential nature of these models raises the questions: to what extent can these…
Decoupling Structure and Lexicon for Zero-Shot Semantic Parsing
Building a semantic parser quickly in a new domain is a fundamental challenge for conversational interfaces, as current semantic parsers require expensive supervision and lack the ability to…
Understanding Convolutional Neural Networks for Text Classification
We present an analysis into the inner workings of Convolutional Neural Networks (CNNs) for processing text. CNNs used for computer vision can be interpreted by projecting filters into image space,…
Word Sense Induction with Neural biLM and Symmetric Patterns
An established method for Word Sense Induction (WSI) uses a language model to predict probable substitutes for target words, and induces senses by clustering these resulting substitute vectors. We…
The Web as a Knowledge-base for Answering Complex Questions
Answering complex questions is a time-consuming activity for humans that requires reasoning and integration of information. Recent work on reading comprehension made headway in answering simple…
Freebase QA: Information Extraction or Semantic Parsing?
We contrast two seemingly distinct approaches to the task of question answering (QA) using Freebase: one based on information extraction techniques, the other on semantic parsing. Results over the…
Modeling Biological Processes for Reading Comprehension
Machine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. In this paper, we focus on a new reading…
Learning Biological Processes with Global Constraints
Biological processes are complex phenomena involving a series of events that are related to one another through various relationships. Systems that can understand and reason over biological…