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Word Embeddings

Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to vectors of real numbers.

Techniques for learning word embeddings can include Word2Vec, GloVe, and other neural network-based approaches that train on an NLP task such as language modeling or document classification.

( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )

Papers

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Showing 26–50 of 4002 papers

TitleStatusHype
Inducing Systematicity in Transformers by Attending to Structurally Quantized EmbeddingsCode1
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
Pre-training and Diagnosing Knowledge Base Completion ModelsCode1
Decoupled Textual Embeddings for Customized Image GenerationCode1
Quantifying the redundancy between prosody and textCode1
OFA: A Framework of Initializing Unseen Subword Embeddings for Efficient Large-scale Multilingual Continued PretrainingCode1
MLFMF: Data Sets for Machine Learning for Mathematical FormalizationCode1
Circumventing Concept Erasure Methods For Text-to-Image Generative ModelsCode1
The Looming Threat of Fake and LLM-generated LinkedIn Profiles: Challenges and Opportunities for Detection and PreventionCode1
Meta-Personalizing Vision-Language Models to Find Named Instances in VideoCode1
Towards Fair and Explainable AI using a Human-Centered AI ApproachCode1
Backpack Language ModelsCode1
Language Models Implement Simple Word2Vec-style Vector ArithmeticCode1
MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic SegmentationCode1
Word Embeddings Are Steers for Language ModelsCode1
PWESuite: Phonetic Word Embeddings and Tasks They FacilitateCode1
CTRAN: CNN-Transformer-based Network for Natural Language UnderstandingCode1
LANDMARK: Language-guided Representation Enhancement Framework for Scene Graph GenerationCode1
SanskritShala: A Neural Sanskrit NLP Toolkit with Web-Based Interface for Pedagogical and Annotation PurposesCode1
Efficient and Flexible Topic Modeling using Pretrained Embeddings and Bag of SentencesCode1
Effective Seed-Guided Topic Discovery by Integrating Multiple Types of ContextsCode1
Learning Object-Language Alignments for Open-Vocabulary Object DetectionCode1
ALIGN-MLM: Word Embedding Alignment is Crucial for Multilingual Pre-trainingCode1
Improving word mover's distance by leveraging self-attention matrixCode1
ADEPT: A DEbiasing PrompT FrameworkCode1
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