366 citations · 952 across the 45 of their papers we have counts for
7 papers · 1 filter
Automatically Extracting Action Graphs from Materials Science Synthesis Procedures
Sheshera Mysore, Edward Kim, Emma Strubell +6
Computational synthesis planning approaches have achieved recent success in organic chemistry, where tabulated synthesis procedures are readily available for supervised learning. T…
Finer Grained Entity Typing with TypeNet
Shikhar Murty, Patrick Verga, Luke Vilnis +1
We consider the challenging problem of entity typing over an extremely fine grained set of types, wherein a single mention or entity can have many simultaneous and often hierarchic…
Attending to All Mention Pairs for Full Abstract Biological Relation Extraction
Patrick Verga, Emma Strubell, Ofer Shai +1
Most work in relation extraction forms a prediction by looking at a short span of text within a single sentence containing a single entity pair mention. However, many relation type…
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling
Dung Thai, Shikhar Murty, Trapit Bansal +3
In textual information extraction and other sequence labeling tasks it is now common to use recurrent neural networks (such as LSTM) to form rich embedded representations of long-t…
Improved Representation Learning for Predicting Commonsense Ontologies
Xiang Li, Luke Vilnis, Andrew McCallum
Recent work in learning ontologies (hierarchical and partially-ordered structures) has leveraged the intrinsic geometry of spaces of learned representations to make predictions tha…
RelNet: End-to-End Modeling of Entities & Relations
Trapit Bansal, Arvind Neelakantan, Andrew McCallum
We introduce RelNet: a new model for relational reasoning. RelNet is a memory augmented neural network which models entities as abstract memory slots and is equipped with an additi…