Search Results for author:
Found 13 papers, 6 papers with code
TaTa: A Multilingual Table-to-Text Dataset for African Languages
To address this lack of data, we create Table-to-Text in African languages (TaTa), the first large multilingual table-to-text dataset with a focus on African languages.
FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation
We present FRMT, a new dataset and evaluation benchmark for Few-shot Region-aware Machine Translation, a type of style-targeted translation.
MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network
We present an instance-based nearest neighbor approach to entity linking.
Entity Linking in 100 Languages
We propose a new formulation for multilingual entity linking, where language-specific mentions resolve to a language-agnostic Knowledge Base.
Ranked #1 on
Entity Disambiguation
on Mewsli-9
(using extra training data)
Asking without Telling: Exploring Latent Ontologies in Contextual Representations
The success of pretrained contextual encoders, such as ELMo and BERT, has brought a great deal of interest in what these models learn: do they, without explicit supervision, learn to encode meaningful notions of linguistic structure?
Learning To Split and Rephrase From Wikipedia Edit History
Split and rephrase is the task of breaking down a sentence into shorter ones that together convey the same meaning.
Natural Language Processing with Small Feed-Forward Networks
We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while being considerably cheaper in memory and computational requirements than deep recurrent models.
Cross-Lingual Morphological Tagging for Low-Resource Languages
We propose a tagging model using Wsabie, a discriminative embedding-based model with rank-based learning.
Probabilistic Modelling of Morphologically Rich Languages
We formulate a novel model that can learn discontiguous morphemes in addition to the more conventional contiguous morphemes that most previous models are limited to.
Compositional Morphology for Word Representations and Language Modelling
This paper presents a scalable method for integrating compositional morphological representations into a vector-based probabilistic language model.
