Neural Nets for NLP 2021 - Multilingual Learning

Explore multilingual learning in neural networks for NLP through this lecture from CMU's CS 11-747 course. Delve into topics such as generative vs. discriminative models, deterministic vs. random variables, variational autoencoders, and handling discrete latent variables. Examine practical examples of variational autoencoders in NLP applications. Gain insights into multilingual models, heuristic sampling, parameter sharing, and adapters. Investigate crosslingual word recovery, benchmarks, and transfer learning techniques. Learn about annotation projection, language overlap, syntax considerations, and active learning approaches for multilingual NLP tasks.