Review - Decision Transformer & SPIRAL

This week's Deep Learning Paper Reviews feature two notable papers: Decision Transformer and SPIRAL. Decision Transformer casts Reinforcement Learning (RL) as a sequence modeling task, outperforming behavior cloning and being competitive with State-of-the-Art Temporal Difference learning techniques. It is particularly capable in tasks involving long-term credit assignment. On the other hand, SPIRAL offers an alternative ASR speech pre-training method that claims to reduce training costs by 80% compared to wav2vec2 for the base model and 65% for the large model. Through aggressive downsampling, SPIRAL matches the performance of wav2vec2 while handling noisy inputs better, making it an attractive alternative SSL pre-training method.