398 citations · 870 across the 15 of their papers we have counts for
5 papers · 1 filter
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…
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer +5
Knowledge bases (KB), both automatically and manually constructed, are often incomplete --- many valid facts can be inferred from the KB by synthesizing existing information. A pop…
Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection
Haw-Shiuan Chang, ZiYun Wang, Luke Vilnis +1
Modeling hypernymy, such as poodle is-a dog, is an important generalization aid to many NLP tasks, such as entailment, coreference, relation extraction, and question answering. Sup…
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…