Maglev: Sliding Recurrent Memory

Benchmark Model Rank Results
common-sense-reasoning-on-winograndeMaglev (lambda=0.1)–Accuracy: 58.7
language-modelling-on-lambadaMaglev (separate parameters, lambda=0.1)–Accuracy: 48.7Perplexity: 7.73
multiple-choice-question-answering-mcqa-on-arc-eMaglev (lambda=0.1)–Accuracy: 70.0
question-answering-on-boolqMaglev (separate parameters, lambda=1)–Accuracy: 64.0
question-answering-on-piqaMaglev (separate parameters, lambda=1)–Accuracy: 72.6
social-commonsense-reasoning-on-siqaMaglev (separate parameters, lambda=0.1)–Accuracy: 42.7