12 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CL2021
Obtaining Better Static Word Embeddings Using Contextual Embedding Models
Prakhar Gupta, Martin Jaggi
The advent of contextual word embeddings -- representations of words which incorporate semantic and syntactic information from their context -- has led to tremendous improvements o…
cs.CL2021
Lightweight Cross-Lingual Sentence Representation Learning
Zhuoyuan Mao, Prakhar Gupta, Pei Wang +3
Large-scale models for learning fixed-dimensional cross-lingual sentence representations like LASER (Artetxe and Schwenk, 2019b) lead to significant improvement in performance on d…
cs.CL2019★ 12 cited
Robust Cross-lingual Embeddings from Parallel Sentences
Ali Sabet, Prakhar Gupta, Jean-Baptiste Cordonnier +2
Recent advances in cross-lingual word embeddings have primarily relied on mapping-based methods, which project pretrained word embeddings from different languages into a shared spa…