479 citations · 1.1k across the 12 of their papers we have counts for
12 papers
Learning Robust and Multilingual Speech Representations
Kazuya Kawakami, Luyu Wang, Chris Dyer +2
Unsupervised speech representation learning has shown remarkable success at finding representations that correlate with phonetic structures and improve downstream speech recognitio…
Learning and Evaluating General Linguistic Intelligence
Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor +8
We define general linguistic intelligence as the ability to reuse previously acquired knowledge about a language's lexicon, syntax, semantics, and pragmatic conventions to adapt to…
Learning to Compose Words into Sentences with Reinforcement Learning
Dani Yogatama, Phil Blunsom, Chris Dyer +2
We use reinforcement learning to learn tree-structured neural networks for computing representations of natural language sentences. In contrast with prior work on tree-structured m…
Language as a Latent Variable: Discrete Generative Models for Sentence Compression
Yishu Miao, Phil Blunsom
In this work we explore deep generative models of text in which the latent representation of a document is itself drawn from a discrete language model distribution. We formulate a…
Online Segment to Segment Neural Transduction
Lei Yu, Jan Buys, Phil Blunsom
We introduce an online neural sequence to sequence model that learns to alternate between encoding and decoding segments of the input as it is read. By independently tracking the e…
Deep Multi-Instance Transfer Learning
Dimitrios Kotzias, Misha Denil, Phil Blunsom +1
We present a new approach for transferring knowledge from groups to individuals that comprise them. We evaluate our method in text, by inferring the ratings of individual sentences…