Papers Word Alignment
“Word Alignment” 태그가 달린 논문 564편 · 필터 해제
Cross-Align: Modeling Deep Cross-lingual Interactions for Word Alignment
Word alignment which aims to extract lexicon translation equivalents between source and target sentences, serves as a fundamental tool for natural language processing. Recent studies in this area have yielded substantial…
Language ModelingLanguage ModellingSentenceTranslation+1Multi-Stage Framework with Refinement Based Point Set Registration for Unsupervised Bi-Lingual Word Alignment
Cross-lingual alignment of word embeddings are important in knowledge transfer across languages, for improving machine translation and other multi-lingual applications. Current unsupervised approaches relying on learning…
Machine TranslationTransfer LearningTranslationWord Alignment+2Exploring Word Alignment towards an Efficient Sentence Aligner for Filipino and Cebuano Languages
Building a robust machine translation (MT) system requires a large amount of parallel corpus which is an expensive resource for low-resourced languages. The two major languages being spoken in the Philippines which are F…
Machine TranslationSentenceTranslationWord AlignmentExtending Word-Level Quality Estimation for Post-Editing Assistance
We define a novel concept called extended word alignment in order to improve post-editing assistance efficiency. Based on extended word alignment, we further propose a novel task called refined word-level QE that outputs…
Word AlignmentXLM-REmbedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings
A popular natural language processing task decades ago, word alignment has been dominated until recently by GIZA++, a statistical method based on the 30-year-old IBM models. New methods that outperform GIZA++ primarily r…
de-enMachine TranslationTranslationWord AlignmentCorrespondence Matters for Video Referring Expression Comprehension
We investigate the problem of video Referring Expression Comprehension (REC), which aims to localize the referent objects described in the sentence to visual regions in the video frames. Despite the recent progress, exis…
Contrastive LearningReferring ExpressionReferring Expression ComprehensionSentence+1GERNERMED++: Transfer Learning in German Medical NLP
We present a statistical model for German medical natural language processing trained for named entity recognition (NER) as an open, publicly available model. The work serves as a refined successor to our first GERNERMED…
Machine Translationnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+3Atril: an XML Visualization System for Corpus Texts
This paper presents Atril, an XML visualization system for corpus texts, developed for, but not restricted to, the project Corpus de Audiências (CorAuDis), a corpus composed of transcripts of sessions of criminal proceed…
ManagementWord AlignmentUtilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
Word translation without parallel corpora has become feasible, rivaling the performance of supervised methods. Recent findings have shown that the accuracy and robustness of unsupervised word translation (UWT) can be imp…
TranslationWord AlignmentWord EmbeddingsWord TranslationSub-Word Alignment Is Still Useful: A Vest-Pocket Method for Enhancing Low-Resource Machine Translation
We leverage embedding duplication between aligned sub-words to extend the Parent-Child transfer learning method, so as to improve low-resource machine translation. We conduct experiments on benchmark datasets of My-En, I…
GPUMachine TranslationTransfer LearningTranslation+1Structural Supervision for Word Alignment and Machine Translation
Syntactic structure has long been argued to be potentially useful for enforcing accurate word alignment and improving generalization performance of machine translation. Unfortunately, existing wisdom demonstrates its sig…
DecoderMachine TranslationMulti-Task LearningTranslation+1When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?
Word alignment has proven to benefit many-to-many neural machine translation (NMT). However, high-quality ground-truth bilingual dictionaries were used for pre-editing in previous methods, which are unavailable for most …
Machine TranslationNMTRetrievalSentence+3Graph Neural Networks for Multiparallel Word Alignment
After a period of decrease, interest in word alignments is increasing again for their usefulness in domains such as typological research, cross-lingual annotation projection, and machine translation. Generally, alignment…
Community DetectionMachine TranslationTranslationWord AlignmentRevitalize Region Feature for Democratizing Video-Language Pre-training of Retrieval
Recent dominant methods for video-language pre-training (VLP) learn transferable representations from the raw pixels in an end-to-end manner to achieve advanced performance on downstream video-language retrieval. Despite…
Question AnsweringRetrievalText to Video RetrievalVideo Question Answering+2Improving Word Translation via Two-Stage Contrastive Learning
Word translation or bilingual lexicon induction (BLI) is a key cross-lingual task, aiming to bridge the lexical gap between different languages. In this work, we propose a robust and effective two-stage contrastive learn…
Bilingual Lexicon InductionContrastive LearningCross-Lingual Word EmbeddingsMachine Translation+7Embedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings
Word alignment has been dominated until recently by GIZA++, a statistical method based on the 30-year-old IBM models. New methods primarily rely on large machine translation models, massively multilingual language models…
de-enMachine TranslationTranslationWord AlignmentWhen do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?
Word alignment has proven to benefit many-to-many neural machine translation (NMT). However, high-quality ground-truth bilingual dictionaries were used for pre-editing in previous methods, which are unavailable for most …
Machine TranslationNMTRetrievalTranslation+1CL-NERIL: A Cross-Lingual Model for NER in Indian Languages
Developing Named Entity Recognition (NER) systems for Indian languages has been a long-standing challenge, mainly owing to the requirement of a large amount of annotated clean training instances. This paper proposes an e…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+3Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment
Cross-lingual alignment of word embeddings play an important role in knowledge transfer across languages, for improving machine translation and other multi-lingual applications. Current unsupervised approaches rely on le…
Machine TranslationSentenceTransfer LearningTranslation+3Improving Word Translation via Two-Stage Contrastive Learning
Word translation or bilingual lexicon induction (BLI) is a key cross-lingual task, aiming to bridge the lexical gap between different languages. In this work, we propose a robust and effective two-stage contrastive learn…
Bilingual Lexicon InductionContrastive LearningCross-Lingual Word EmbeddingsMachine Translation+8