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 401410 of 551 papers

TitleStatusHype
Subword Sampling for Low Resource Word Alignment0
Umelb: Cross-lingual Textual Entailment with Word Alignment and String Similarity Features0
Unified Expectation Maximization0
Unsupervised and Lightly Supervised Part-of-Speech Tagging Using Recurrent Neural Networks0
Unsupervised Coreference Resolution by Utilizing the Most Informative Relations0
Unsupervised Cross-Lingual Part-of-Speech Tagging for Truly Low-Resource Scenarios0
Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models0
Unsupervised Event Clustering and Aggregation from Newswire and Web Articles0
Unsupervised False Friend Disambiguation Using Contextual Word Clusters and Parallel Word Alignments0
Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss0
Show:102550
← PrevPage 41 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