Tag: Recurrent Neural Network

AI Machine Learning & Data Science Nature Language Tech Research

Google & IDSIA’s Block-Recurrent Transformer Dramatically Outperforms Transformers Over Very Long Sequences

A team from Google Research and the Swiss AI Lab IDSIA proposes the Block-Recurrent Transformer, a novel long-sequence processing approach that has the same computation time and parameter count costs as a conventional transformer layer but achieves significant perplexity improvements in language modelling tasks over very long sequences.

AI Machine Learning & Data Science Research

Yoshua Bengio Team’s Recurrent Independent Mechanisms Endow RL Agents With Out-of-Distribution Adaptation and Generalization Abilities

A research team from the University of Montreal and Max Planck Institute for Intelligent Systems constructs a reinforcement learning agent whose knowledge and reward function can be reused across tasks, along with an attention mechanism that dynamically selects unchangeable knowledge pieces to enable out-of-distribution adaptation and generalization.