24 citations · 41 across the 4 of their papers we have counts for
6 papers
Boosting Entity Linking Performance by Leveraging Unlabeled Documents
Phong Le, Ivan Titov
Modern entity linking systems rely on large collections of documents specifically annotated for the task (e.g., AIDA CoNLL). In contrast, we propose an approach which exploits only…
Distant Learning for Entity Linking with Automatic Noise Detection
Phong Le, Ivan Titov
Accurate entity linkers have been produced for domains and languages where annotated data (i.e., texts linked to a knowledge base) is available. However, little progress has been m…
LSTM-based Mixture-of-Experts for Knowledge-Aware Dialogues
Phong Le, Marc Dymetman, Jean-Michel Renders
We introduce an LSTM-based method for dynamically integrating several word-prediction experts to obtain a conditional language model which can be good simultaneously at several sub…
Quantifying the vanishing gradient and long distance dependency problem in recursive neural networks and recursive LSTMs
Phong Le, Willem Zuidema
Recursive neural networks (RNN) and their recently proposed extension recursive long short term memory networks (RLSTM) are models that compute representations for sentences, by re…
Unsupervised Dependency Parsing: Let's Use Supervised Parsers
Phong Le, Willem Zuidema
We present a self-training approach to unsupervised dependency parsing that reuses existing supervised and unsupervised parsing algorithms. Our approach, called `iterated reranking…
Compositional Distributional Semantics with Long Short Term Memory
Phong Le, Willem Zuidema
We are proposing an extension of the recursive neural network that makes use of a variant of the long short-term memory architecture. The extension allows information low in parse…