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Research map / Architectures and efficiency / Attention and transformers

Blockwise Parallel Decoding for Deep Autoregressive Models

NeurIPS 2018 · Architectures and efficiency › Attention and transformers · approach: State space and recurrent sequence models · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use blockwise parallel decoding with k = 8Transformer on newstest2014 · newstest2014wall-clock speedup: 3.31xHelped
Increase block size from k = 2 to k = 8Blockwise parallel decoding for Transformer · newstest2014BLEU: 28.95 -> 27.88Hurt
Use distilled rather than original training data (ablation)Blockwise decoding, frozen Transformer, k = 8 · newstest2013BLEU: 25.82 -> 26.25Helped
Fine-tune the base parameters (ablation)Blockwise decoding with original training data, k = 8 · newstest2013mean accepted block size: 1.76 -> 3.01Helped
Fine-tune the base parameters (ablation)Blockwise decoding with original training data, k = 8 · newstest2013BLEU: 25.82 -> 24.27Hurt
Combine distillation and fine-tuning (ablation)Blockwise decoding, k = 8 · newstest2013mean accepted block size: 1.91 -> 4.69Helped
Allow proposals from the scoring model's top-2 instead of requiring an exact greedy match (ablation)Blockwise decoding, distillation and fine-tuning, k = 8 · newstest2013mean accepted block size: 4.69 -> 5.34Helped
Allow proposals from the scoring model's top-2 instead of requiring an exact greedy match (ablation)Blockwise decoding, distillation and fine-tuning, k = 8 · newstest2013BLEU: 26.11 -> 25.71Hurt
Require a minimum block size of k = 2 or k = 3 (ablation)Blockwise decoding for machine translation · newstest2013BLEUHurt
Allow distance-based approximate acceptance with epsilon = 2 (ablation)Image Transformer with frozen base parameters, k = 10 · CelebA development setmean accepted block size: 1.10 -> 1.40Helped
Fine-tune base parameters (ablation)Image Transformer with exact acceptance, k = 10 · CelebA development setmean accepted block size: 1.10 -> 2.04Helped
Combine fine-tuning and distance-based approximate acceptance (ablation)Image Transformer, k = 10 · CelebA development setmean accepted block size: 1.10 -> 6.79Helped

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