842 citations · 1k across the 13 of their papers we have counts for
14 papers
Learning Interpretable Spatial Operations in a Rich 3D Blocks World
Yonatan Bisk, Kevin J. Shih, Yejin Choi +1
In this paper, we study the problem of mapping natural language instructions to complex spatial actions in a 3D blocks world. We first introduce a new dataset that pairs complex 3D…
Unsupervised Neural Hidden Markov Models
Ke Tran, Yonatan Bisk, Ashish Vaswani +2
In this work, we present the first results for neuralizing an Unsupervised Hidden Markov Model. We evaluate our approach on tag in- duction. Our approach outperforms existing gener…
Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text
Sahil Garg, Aram Galstyan, Ulf Hermjakob +1
We advance the state of the art in biomolecular interaction extraction with three contributions: (i) We show that deep, Abstract Meaning Representations (AMR) significantly improve…
Using Syntax-Based Machine Translation to Parse English into Abstract Meaning Representation
Michael Pust, Ulf Hermjakob, Kevin Knight +2
We present a parser for Abstract Meaning Representation (AMR). We treat English-to-AMR conversion within the framework of string-to-tree, syntax-based machine translation (SBMT). T…
Domain Adaptation for Statistical Classifiers
H. Daume, D. Marcu
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicatio…
Bayesian Query-Focused Summarization
Hal Daumé
We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents a…