SOTAVerified

Word Alignment

Word Alignment is the task of finding the correspondence between source and target words in a pair of sentences that are translations of each other.

Source: Neural Network-based Word Alignment through Score Aggregation

Papers

Showing 511520 of 551 papers

TitleStatusHype
A Bayesian Model for Learning SCFGs with Discontiguous Rules0
Generalizing Sub-sentential Paraphrase Acquisition across Original Signal Type of Text Pairs0
Re-training Monolingual Parser Bilingually for Syntactic SMT0
Forced Derivation Tree based Model Training to Statistical Machine Translation0
HDU: Cross-lingual Textual Entailment with SMT Features0
DOMCAT: A Bilingual Concordancer for Domain-Specific Computer Assisted Translation0
Learning Better Rule Extraction with Translation Span Alignment0
Translation Model Size Reduction for Hierarchical Phrase-based Statistical Machine Translation0
Enhancing Statistical Machine Translation with Character Alignment0
Smaller Alignment Models for Better Translations: Unsupervised Word Alignment with the l0-norm0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@184.26Unverified
2Adv - Refine - CSLSP@181.7Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@182.94Unverified
2Adv - Refine - CSLSP@182.3Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@183.5Unverified
2Adv - Refine - CSLSP@183.3Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@183.23Unverified
2Adv - Refine - CSLSP@182.1Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@181.45Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@174.08Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@184.65Unverified