Papers Word Alignment
“Word Alignment” 태그가 달린 논문 564편 · 필터 해제
Towards Arabic Multimodal Dataset for Sentiment Analysis
Multimodal Sentiment Analysis (MSA) has recently become a centric research direction for many real-world applications. This proliferation is due to the fact that opinions are central to almost all human activities and ar…
Multimodal Sentiment AnalysisSentiment AnalysisWord AlignmentWSPAlign: Word Alignment Pre-training via Large-Scale Weakly Supervised Span Prediction
Most existing word alignment methods rely on manual alignment datasets or parallel corpora, which limits their usefulness. Here, to mitigate the dependence on manual data, we broaden the source of supervision by relaxing…
Word AlignmentUnbalanced Optimal Transport for Unbalanced Word Alignment
Monolingual word alignment is crucial to model semantic interactions between sentences. In particular, null alignment, a phenomenon in which words have no corresponding counterparts, is pervasive and critical in handling…
Semantic SimilaritySemantic Textual SimilarityWord AlignmentDo GPTs Produce Less Literal Translations?
Large Language Models (LLMs) such as GPT-3 have emerged as general-purpose language models capable of addressing many natural language generation or understanding tasks. On the task of Machine Translation (MT), multiple …
Machine TranslationNMTText GenerationTranslation+1Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents
Automatically highlighting words that cause semantic differences between two documents could be useful for a wide range of applications. We formulate recognizing semantic differences (RSD) as a token-level regression tas…
Contrastive LearningLanguage ModelingLanguage Modellingregression+2AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation
Attention is the core mechanism of today's most used architectures for natural language processing and has been analyzed from many perspectives, including its effectiveness for machine translation-related tasks. Among th…
Machine TranslationTranslationWord AlignmentContextualized Word Vector-based Methods for Discovering Semantic Differences with No Training nor Word Alignment
In this paper, we propose methods for discovering semantic differences in words appearing in two corpora based on the norms of contextualized word vectors. The key idea is that the coverage of meanings is reflected in th…
Word AlignmentLow-resource Bilingual Dialect Lexicon Induction with Large Language Models
Bilingual word lexicons are crucial tools for multilingual natural language understanding and machine translation tasks, as they facilitate the mapping of words in one language to their synonyms in another language. To a…
Bilingual Lexicon InductionMachine TranslationNatural Language UnderstandingSemantic Similarity+3Investigating the Role of Attribute Context in Vision-Language Models for Object Recognition and Detection
Vision-language alignment learned from image-caption pairs has been shown to benefit tasks like object recognition and detection. Methods are mostly evaluated in terms of how well object class names are learned, but capt…
AttributeContrastive LearningObjectobject-detection+7Meeting the Needs of Low-Resource Languages: The Value of Automatic Alignments via Pretrained Models
Large multilingual models have inspired a new class of word alignment methods, which work well for the model's pretraining languages. However, the languages most in need of automatic alignment are low-resource and, thus,…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Part-Of-Speech Tagging+1Multilingual Sentence Transformer as A Multilingual Word Aligner
Multilingual pretrained language models (mPLMs) have shown their effectiveness in multilingual word alignment induction. However, these methods usually start from mBERT or XLM-R. In this paper, we investigate whether mul…
SentenceWord AlignmentXLM-RNoisy Parallel Data Alignment
An ongoing challenge in current natural language processing is how its major advancements tend to disproportionately favor resource-rich languages, leaving a significant number of under-resourced languages behind. Due to…
Optical Character RecognitionOptical Character Recognition (OCR)Word AlignmentLearning Trajectory-Word Alignments for Video-Language Tasks
In a video, an object usually appears as the trajectory, i.e., it spans over a few spatial but longer temporal patches, that contains abundant spatiotemporal contexts. However, modern Video-Language BERTs (VDL-BERTs) neg…
Question AnsweringRetrievalText to Video RetrievalVideo Question Answering+2Learning To Generate Language-Supervised and Open-Vocabulary Scene Graph Using Pre-Trained Visual-Semantic Space
Scene graph generation (SGG) aims to abstract an image into a graph structure, by representing objects as graph nodes and their relations as labeled edges. However, two knotty obstacles limit the practicability of cu…
Graph Generationobject-detectionObject DetectionOpen-vocabulary object detection+3Word Alignment in the Era of Deep Learning: A Tutorial
The word alignment task, despite its prominence in the era of statistical machine translation (SMT), is niche and under-explored today. In this two-part tutorial, we argue for the continued relevance for word alignment. …
Deep LearningMachine TranslationNMTTranslation+1Frustratingly Easy Label Projection for Cross-lingual Transfer
Translating training data into many languages has emerged as a practical solution for improving cross-lingual transfer. For tasks that involve span-level annotations, such as information extraction or question answering,…
Cross-Lingual NERCross-Lingual TransferEvent ExtractionNER+4Third-Party Aligner for Neural Word Alignments
Word alignment is to find translationally equivalent words between source and target sentences. Previous work has demonstrated that self-training can achieve competitive word alignment results. In this paper, we propose …
Language ModelingLanguage ModellingWord AlignmentImproving Bilingual Lexicon Induction with Cross-Encoder Reranking
Bilingual lexicon induction (BLI) with limited bilingual supervision is a crucial yet challenging task in multilingual NLP. Current state-of-the-art BLI methods rely on the induction of cross-lingual word embeddings (CLW…
Bilingual Lexicon InductionCross Encoder RerankingCross-Lingual Word EmbeddingsMachine Translation+9EntityCS: Improving Zero-Shot Cross-lingual Transfer with Entity-Centric Code Switching
Accurate alignment between languages is fundamental for improving cross-lingual pre-trained language models (XLMs). Motivated by the natural phenomenon of code-switching (CS) in multilingual speakers, CS has been used as…
Cross-Lingual TransferData AugmentationRetrievalSentence+2SilverAlign: MT-Based Silver Data Algorithm For Evaluating Word Alignment
Word alignments are essential for a variety of NLP tasks. Therefore, choosing the best approaches for their creation is crucial. However, the scarce availability of gold evaluation data makes the choice difficult. We pro…
Machine TranslationTranslationvalidWord Alignment