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Syntactic Skeleton-Based Translation

AAAI 2016 · Architectures and efficiency › RNNs and normalization · approach: Non-autoregressive translation · 10 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add syntactic skeleton with partially syntactic rules to hierarchical phrase-basedHierarchical Phrase-based · zh-en nw, zh-en web, en-zh testsBLEU: +0.95 average (binary trees)Helped
use binary parse trees instead of CTB-style trees for SYNSKEL (ablation)SYNSKEL · zh-en nw, zh-en web, en-zh testsBLEU: +0.71 -> +0.95Helped
use tree-parsing instead of string-parsing (ablation)SYNSKEL · zh-en nw, zh-en web, en-zh testsBLEU: +0.95 -> +0.91No clear effect
use binary forest instead of single binary tree (ablation)SYNSKEL · zh-en nw, zh-en web, en-zh testsBLEU: +0.91 -> +0.94No clear effect
SYNSKEL instead of Hier. + SAMT rulesSYNSKEL · zh-en nw, zh-en web, en-zh testsBLEU: +0.35 -> +0.95Helped
limit maximum skeleton depth to 5 or less instead of unlimited (ablation)SYNSKEL · zh-en newswire tuningBLEU and decoding timeMixed
use tree-to-string model alone instead of hierarchical phrase-basedTree-to-String · zh-en nw, zh-en web, en-zh testsBLEU: -0.77 (CTB), -0.39 (binary)Hurt
add source syntax features to hierarchical phrase-basedHierarchical Phrase-based · zh-en nw, zh-en web, en-zh testsBLEU: +0.23 (CTB), +0.29 (binary)Helped

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