3.8k citations · 4k across the 9 of their papers we have counts for
6 papers · 1 filter
Evaluating Online Continual Learning with CALM
Germán Kruszewski, Ionut-Teodor Sorodoc, Tomas Mikolov
Online Continual Learning (OCL) studies learning over a continuous data stream without observing any single example more than once, a setting that is closer to the experience of hu…
Updating Pre-trained Word Vectors and Text Classifiers using Monolingual Alignment
Piotr Bojanowski, Onur Celebi, Tomas Mikolov +2
In this paper, we focus on the problem of adapting word vector-based models to new textual data. Given a model pre-trained on large reference data, how can we adapt it to a smaller…
Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion
Armand Joulin, Piotr Bojanowski, Tomas Mikolov +2
Continuous word representations learned separately on distinct languages can be aligned so that their words become comparable in a common space. Existing works typically solve a le…
Learning Word Vectors for 157 Languages
Edouard Grave, Piotr Bojanowski, Prakhar Gupta +2
Distributed word representations, or word vectors, have recently been applied to many tasks in natural language processing, leading to state-of-the-art performance. A key ingredien…
Efficient Large-Scale Multi-Modal Classification
D. Kiela, E. Grave, A. Joulin +1
While the incipient internet was largely text-based, the modern digital world is becoming increasingly multi-modal. Here, we examine multi-modal classification where one modality i…
Advances in Pre-Training Distributed Word Representations
Tomas Mikolov, Edouard Grave, Piotr Bojanowski +2
Many Natural Language Processing applications nowadays rely on pre-trained word representations estimated from large text corpora such as news collections, Wikipedia and Web Crawl.…