6 citations · 10 across the 7 of their papers we have counts for
12 papers
Using dependency parsing for few-shot learning in distributional semantics
Stefania Preda, Guy Emerson
In this work, we explore the novel idea of employing dependency parsing information in the context of few-shot learning, the task of learning the meaning of a rare word based on a…
Learning Functional Distributional Semantics with Visual Data
Yinhong Liu, Guy Emerson
Functional Distributional Semantics is a recently proposed framework for learning distributional semantics that provides linguistic interpretability. It models the meaning of a wor…
Incremental Beam Manipulation for Natural Language Generation
James Hargreaves, Andreas Vlachos, Guy Emerson
The performance of natural language generation systems has improved substantially with modern neural networks. At test time they typically employ beam search to avoid locally optim…
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model
Jun Yen Leung, Guy Emerson, Ryan Cotterell
Across languages, multiple consecutive adjectives modifying a noun (e.g. "the big red dog") follow certain unmarked ordering rules. While explanatory accounts have been put forward…
Linguists Who Use Probabilistic Models Love Them: Quantification in Functional Distributional Semantics
Guy Emerson
Functional Distributional Semantics provides a computationally tractable framework for learning truth-conditional semantics from a corpus. Previous work in this framework has provi…
Autoencoding Pixies: Amortised Variational Inference with Graph Convolutions for Functional Distributional Semantics
Guy Emerson
Functional Distributional Semantics provides a linguistically interpretable framework for distributional semantics, by representing the meaning of a word as a function (a binary cl…