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 161170 of 551 papers

TitleStatusHype
DLS@CU: Sentence Similarity from Word Alignment0
Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment0
Bilingually-constrained Phrase Embeddings for Machine Translation0
DOMCAT: A Bilingual Concordancer for Domain-Specific Computer Assisted Translation0
An Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation0
Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction0
ECNU at SemEval-2016 Task 1: Leveraging Word Embedding From Macro and Micro Views to Boost Performance for Semantic Textual Similarity0
ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation0
Edinburgh's Statistical Machine Translation Systems for WMT160
Cross-Lingual Named Entity Recognition via FastAlign: a Case Study0
Show:102550
← PrevPage 17 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