22 citations · 39 across the 2 of their papers we have counts for
6 papers
Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking
Thibault Févry, Nicholas FitzGerald, Livio Baldini Soares +1
In this work, we present an entity linking model which combines a Transformer architecture with large scale pretraining from Wikipedia links. Our model achieves the state-of-the-ar…
Entities as Experts: Sparse Memory Access with Entity Supervision
Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald +2
We focus on the problem of capturing declarative knowledge about entities in the learned parameters of a language model. We introduce a new model - Entities as Experts (EAE) - that…
Learning Cross-Context Entity Representations from Text
Jeffrey Ling, Nicholas FitzGerald, Zifei Shan +4
Language modeling tasks, in which words, or word-pieces, are predicted on the basis of a local context, have been very effective for learning word embeddings and context dependent…
Matching the Blanks: Distributional Similarity for Relation Learning
Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling +1
General purpose relation extractors, which can model arbitrary relations, are a core aspiration in information extraction. Efforts have been made to build general purpose extractor…
Large-Scale QA-SRL Parsing
Nicholas FitzGerald, Julian Michael, Luheng He +1
We present a new large-scale corpus of Question-Answer driven Semantic Role Labeling (QA-SRL) annotations, and the first high-quality QA-SRL parser. Our corpus, QA-SRL Bank 2.0, co…
Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum
Omer Levy, Kenton Lee, Nicholas FitzGerald +1
LSTMs were introduced to combat vanishing gradients in simple RNNs by augmenting them with gated additive recurrent connections. We present an alternative view to explain the succe…