What is debiasing of word embeddings?

GloVe Global Vectors for Word Representation new arrivals, NLP Word Embedding GloVe. BERT is a major milestone in new arrivals, Transfer Learning with GloVe ... Dec 15, 2020 ... Recently, encoding word properties into low-dimensional vector spaces using neural networks has become increasingly popular. Word embeddings are ... Word embeddings are a way of representing words as vectors in a multi-dimensional space, where the distance and direction between vectors reflect the ... Jul 4, 2019 ... Hello, I read quite a lot about the importance of word embedding in the context of NLP, but i've never seen the following issue beeing ... We can also apply pre-trained word embeddings to the word analogy problem. For example, “man : woman :: son : daughter” is an analogy. This sentence can also be ... Mar 16, 2022 ... A deep dive into word embeddings (NLP). When I first started learning about word2vec, BERT, and advanced text embeddings, my head hurt. I had a ... Nov 3, 2021 ... Word vector representations have a long tradition in several research fields, such as cognitive science or computational linguistics. May 7, 2023 ... Word embeddings are a popular technique used in NLP to represent words in a way that can be processed by machine learning algorithms. Feb 5, 2025 ... Word embeddings (also known as word vectors) are the vectors that are created to represent words — and their context — or the relationships ... Jan 24, 2018 ... ... natural language processing (NLP) at Facebook scale. To better ... word embedding vectors are preserved. We integrated these embeddings ...