Google AI's ALBERT claims top spot in multiple NLP performance benchmarks

Researchers from Google AI (formerly Google Research) and Toyota Technological Institute of Chicago have created ALBERT, an AI model that achieves state-of-the-art results that exceed human performance. ALBERT now claims first place on major NLP performance leaderboards for benchmarks like GLUE and SQuAD 2.0, and high RACE performance score. On the Stanford Question Answering Dataset benchmark (SQUAD), ALBERT achieves a score of 92.2, on General Language Understanding Evaluation (GLUE) benchmark, ALBERT achieves a score of 89.4, and on ReAding Comprehension from English Examinations (RACE) benchmark, ALBERT gets a score of 89.4%. ALBERT is a version of Transformer-based BERT that "uses parameter reduction techniques to lower memory consumption and increase the training speed of BERT," according to a paper published on OpenReview.net The paper was published alongside other papers being considered for publication as part of the International Conference of Learning Representations, which will take place in April 2020 in Addis Ababa, Ethiopia.