Workshop / Overview

This workshop will focus on the domain of Cross-Lingual Natural Language Processing (NLP) which concerns the development of methods that can leverage data and models from languages rich in resources (for example English) to tackle tasks in low-resource languages (for example Swiss German).

More specifically, in the workshop the participants will have the chance to explore the current state-of-the-art of cross-lingual and multi-lingual models, like for example LASER and BERT, and acquire hands-on experience on leveraging such approaches in order to solve cross-lingual tasks.

The workshop will be structured as follows. A short introduction to word embeddings and cross-lingual word embeddings will be given, where the participants will be enabled to leverage them in order to solve downstream tasks (e.g. sentiment classification, sentence retrieval etc.) with baseline approaches. Then, the participants will have the chance to apply state-of-the-art neural models that use cross-lingual word embeddings on various tasks like sentiment classification or cross-lingual sentence retrieval.

Workshop / Outcome

The participants will be given a short introduction to Cross-Lingual NLP as well as to recent advances developed in the domain of Deep Neural Networks. Also, the participants will acquire hands-on experience on using such techniques in order to solve NLP tasks in low-resource languages.

Workshop / Difficulty

Intermediate level

Workshop / Prerequisites

  • Knowledge of Python
  • Own laptop
  • A google account (access Colab which will be used for the practical work)
  • Repository

Track / Co-organizers

Ioannis Partalas

Lead Data Scientist, Expedia

Georgios Balikas

Senior Data Scientist, Salesforce

Eric Bruno

Senior Machine Learning Scientist, Expedia Group

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