3.1k citations · 6.9k across the 91 of their papers we have counts for
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Deep Semi-Supervised Learning with Linguistically Motivated Sequence Labeling Task Hierarchies
Jonathan Godwin, Pontus Stenetorp, Sebastian Riedel
In this paper we present a novel Neural Network algorithm for conducting semi-supervised learning for sequence labeling tasks arranged in a linguistically motivated hierarchy. This…
Learning Python Code Suggestion with a Sparse Pointer Network
Avishkar Bhoopchand, Tim Rocktäschel, Earl Barr +1
To enhance developer productivity, all modern integrated development environments (IDEs) include code suggestion functionality that proposes likely next tokens at the cursor. While…
Learning to Reason With Adaptive Computation
Mark Neumann, Pontus Stenetorp, Sebastian Riedel
Multi-hop inference is necessary for machine learning systems to successfully solve tasks such as Recognising Textual Entailment and Machine Reading. In this work, we demonstrate t…
Represent, Aggregate, and Constrain: A Novel Architecture for Machine Reading from Noisy Sources
Jason Naradowsky, Sebastian Riedel
In order to extract event information from text, a machine reading model must learn to accurately read and interpret the ways in which that information is expressed. But it must al…
Clinical Text Prediction with Numerically Grounded Conditional Language Models
Georgios P. Spithourakis, Steffen E. Petersen, Sebastian Riedel
Assisted text input techniques can save time and effort and improve text quality. In this paper, we investigate how grounded and conditional extensions to standard neural language…
SentiHood: Targeted Aspect Based Sentiment Analysis Dataset for Urban Neighbourhoods
Marzieh Saeidi, Guillaume Bouchard, Maria Liakata +1
In this paper, we introduce the task of targeted aspect-based sentiment analysis. The goal is to extract fine-grained information with respect to entities mentioned in user comment…