526 citations · 1.2k across the 21 of their papers we have counts for
11 papers · 1 filter
Sentence Encoding with Tree-constrained Relation Networks
Lei Yu, Cyprien de Masson d'Autume, Chris Dyer +3
The meaning of a sentence is a function of the relations that hold between its words. We instantiate this relational view of semantics in a series of neural models based on variant…
Learning to Discover, Ground and Use Words with Segmental Neural Language Models
Kazuya Kawakami, Chris Dyer, Phil Blunsom
We propose a segmental neural language model that combines the generalization power of neural networks with the ability to discover word-like units that are latent in unsegmented c…
Syntactic Scaffolds for Semantic Structures
Swabha Swayamdipta, Sam Thomson, Kenton Lee +3
We introduce the syntactic scaffold, an approach to incorporating syntactic information into semantic tasks. Syntactic scaffolds avoid expensive syntactic processing at runtime, on…
Neural Arithmetic Logic Units
Andrew Trask, Felix Hill, Scott Reed +3
Neural networks can learn to represent and manipulate numerical information, but they seldom generalize well outside of the range of numerical values encountered during training. T…
Finding Syntax in Human Encephalography with Beam Search
John Hale, Chris Dyer, Adhiguna Kuncoro +1
Recurrent neural network grammars (RNNGs) are generative models of (tree,string) pairs that rely on neural networks to evaluate derivational choices. Parsing with them using beam s…
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst +24
Artificial intelligence (AI) has undergone a renaissance recently, making major progress in key domains such as vision, language, control, and decision-making. This has been due, i…