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 321330 of 551 papers

TitleStatusHype
Inducing Multilingual Text Analysis Tools Using Bidirectional Recurrent Neural Networks0
Innovations in Parallel Corpus Search Tools0
Insertion and Deletion Models for Statistical Machine Translation0
Insertion Position Selection Model for Flexible Non-Terminals in Dependency Tree-to-Tree Machine Translation0
Integrating empty category detection into preordering Machine Translation0
Interconnecting lexical resources and word alignment: How do learners get on with particle verbs?0
Inverted indexing for cross-lingual NLP0
Investigating Connectivity and Consistency Criteria for Phrase Pair Extraction in Statistical Machine Translation0
Investigating the Influence of Bilingual MWU on Trainee Translation Quality0
ISCAS\_NLP at SemEval-2016 Task 1: Sentence Similarity Based on Support Vector Regression using Multiple Features0
Show:102550
← PrevPage 33 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