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 491500 of 551 papers

TitleStatusHype
Reversing Morphological Tokenization in English-to-Arabic SMT0
A Systematic Bayesian Treatment of the IBM Alignment Models0
Cross-Lingual Semantic Similarity of Words as the Similarity of Their Semantic Word Responses0
Knowledge-Rich Morphological Priors for Bayesian Language Models0
Distant annotation of Chinese tense and modality0
Learning to translate with products of novices: a suite of open-ended challenge problems for teaching MT0
Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction0
Large-scale Word Alignment Using Soft Dependency Cohesion Constraints0
Combining Multiple Alignments to Improve Machine Translation0
Cross-Lingual Identification of Ambiguous Discourse Connectives for Resource-Poor Language0
Show:102550
← PrevPage 50 of 56Next →

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