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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 1–50 of 4002 papers

TitleStatusHype
Fine-mixing: Mitigating Backdoors in Fine-tuned Language ModelsCode8
CharacterFactory: Sampling Consistent Characters with GANs for Diffusion ModelsCode3
WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question AnsweringCode2
FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic ModelCode2
VNLP: Turkish NLP PackageCode2
Generative Adversarial Training for Text-to-Speech Synthesis Based on Raw Phonetic Input and Explicit Prosody ModellingCode2
RETVec: Resilient and Efficient Text VectorizerCode2
Contextual Semantic Embeddings for Ontology Subsumption PredictionCode2
Train Short, Test Long: Attention with Linear Biases Enables Input Length ExtrapolationCode2
A Pilot Study for Chinese SQL Semantic ParsingCode2
ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational KnowledgeCode2
ConceptNet 5.5: An Open Multilingual Graph of General KnowledgeCode2
An Ensemble Method to Produce High-Quality Word Embeddings (2016)Code2
Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot LearningCode1
HJ-Ky-0.1: an Evaluation Dataset for Kyrgyz Word EmbeddingsCode1
Fine-Tuning CLIP's Last Visual Projector: A Few-Shot CornucopiaCode1
Enhancing High-order Interaction Awareness in LLM-based Recommender ModelCode1
GrEmLIn: A Repository of Green Baseline Embeddings for 87 Low-Resource Languages Injected with Multilingual Graph KnowledgeCode1
DiffEditor: Enhancing Speech Editing with Semantic Enrichment and Acoustic ConsistencyCode1
Spiking Convolutional Neural Networks for Text ClassificationCode1
MT2ST: Adaptive Multi-Task to Single-Task LearningCode1
Statistical Uncertainty in Word Embeddings: GloVe-VCode1
A Comprehensive Analysis of Static Word Embeddings for TurkishCode1
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language ModelsCode1
DiLM: Distilling Dataset into Language Model for Text-level Dataset DistillationCode1
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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