activity
20162022
most citedLearning and Evaluating General Linguistic Intelligence

157 citations · 166 across the 2 of their papers we have counts for

collaborators

8 papers

cs.CL20229 cited

Towards Coherent and Consistent Use of Entities in Narrative Generation

Pinelopi Papalampidi, Kris Cao, Tomas Kocisky

Large pre-trained language models (LMs) have demonstrated impressive capabilities in generating long, fluent text; however, there is little to no analysis on their ability to maint…

cs.CL2021

Mind the Gap: Assessing Temporal Generalization in Neural Language Models

Angeliki Lazaridou, Adhiguna Kuncoro, Elena Gribovskaya +11

Our world is open-ended, non-stationary, and constantly evolving; thus what we talk about and how we talk about it change over time. This inherent dynamic nature of language contra…

cs.LG2019157 cited

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…

cs.CL2018

Encoding Spatial Relations from Natural Language

Tiago Ramalho, Tomáš Kočiský, Frederic Besse +5

Natural language processing has made significant inroads into learning the semantics of words through distributional approaches, however representations learnt via these methods fa…

stat.ML2018

Pushing the bounds of dropout

Gábor Melis, Charles Blundell, Tomáš Kočiský +3

We show that dropout training is best understood as performing MAP estimation concurrently for a family of conditional models whose objectives are themselves lower bounded by the o…

cs.CL2017

The NarrativeQA Reading Comprehension Challenge

Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom +4

Reading comprehension (RC)---in contrast to information retrieval---requires integrating information and reasoning about events, entities, and their relations across a full documen…