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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–210 of 551 papers

TitleStatusHype
CASICT-DCU Neural Machine Translation Systems for WMT17—0
A BiLSTM-based System for Cross-lingual Pronoun Prediction—0
Unsupervised Event Clustering and Aggregation from Newswire and Web Articles—0
Building a SentiWordNet for Odia—0
Log-linear Models for Uyghur Segmentation in Spoken Language Translation—0
Discovery of Discourse-Related Language Contrasts through Alignment Discrepancies in English-German Translation—0
CUNI Experiments for WMT17 Metrics Task—0
LIPN-IIMAS at SemEval-2017 Task 1: Subword Embeddings, Attention Recurrent Neural Networks and Cross Word Alignment for Semantic Textual Similarity—0
STS-UHH at SemEval-2017 Task 1: Scoring Semantic Textual Similarity Using Supervised and Unsupervised Ensemble—0
DT\_Team at SemEval-2017 Task 1: Semantic Similarity Using Alignments, Sentence-Level Embeddings and Gaussian Mixture Model Output—0
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All datasetsen-esen-fres-enfr-enen-itMUSE en-deMUSE en-pt

Benchmark Results

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