Welcome to the website of the ACL Special Interest Group on Representation Learning (SIGREP). We promote research on representation learning in Natural Language Processing, specifically methods for inferring representations from data, as well as studying evaluation and transferability of representations.
We organise the annual ACL workshop on Representation Learning for NLP (Repl4NLP). The RepL4NLP workshop was introduced as a synthesis of several years of independent *CL workshops focusing on vector space models of meaning, compositionality, and the application of deep neural networks and spectral methods to NLP. It provides a forum for discussing recent advances on these topics, as well as future research directions in linguistically motivated vector-based models in NLP. It has been co-located with ACL since 2016, and regularly attracts around 250 attendees.