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Guiding Attention in Sequence-to-Sequence Models for Dialogue Act Prediction

AAAI 2020 · Architectures and efficiency › Attention and transformers · approach: Language model pretraining and induction · 49 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use seq2seq instead of CRF with a GRU encoderDialogue act prediction · SwDA devaccuracy: 77.7 -> 81.9Helped
Use seq2seq instead of CRF with a GRU encoderDialogue act prediction · MRDA devaccuracy: 88.3 -> 88.5Helped
Use seq2seq instead of CRF with an HGRU encoderDialogue act prediction · SwDA devaccuracy: 81.6 -> 82.4Helped
Use seq2seq instead of CRF with an HGRU encoderDialogue act prediction · MRDA devaccuracy: 90.0 -> 90.0No clear effect
Add hierarchical word-and-utterance encoding instead of a vanilla encoder (ablation)seq2seq · SwDA devaccuracy: 81.6 -> 82.4Helped
Add hierarchical word-and-utterance encoding instead of a vanilla encoder (ablation)seq2seq · MRDA devaccuracy: 88.5 -> 90.0Helped
Add hard guided attention rather than no attention (ablation)seq2seq + HGRU · SwDA devaccuracy: 82.4 -> 84.0Helped
Add hard guided attention rather than no attention (ablation)seq2seq + HGRU · MRDA devaccuracy: 90.0 -> 90.2Helped
Replace hard guided attention with vanilla attention (ablation)seq2seq + HGRU · SwDA devaccuracy: 84.0 -> 82.3Hurt
Replace hard guided attention with vanilla attention (ablation)seq2seq + HGRU · MRDA devaccuracy: 90.2 -> 89.9Hurt
Add a persona layer to the hierarchical encoder (ablation)seq2seq + hard guided attention · SwDA devaccuracy: 84.0 -> 83.5Hurt
Add a persona layer to the hierarchical encoder (ablation)seq2seq + hard guided attention · MRDA devaccuracy: 90.2 -> 86.9Hurt

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