SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 4002 papers

TitleStatusHype
Personalized Video Summarization using Text-Based Queries and Conditional Modeling—0
Triplètoile: Extraction of Knowledge from Microblogging Text—0
BERT's Conceptual Cartography: Mapping the Landscapes of Meaning—0
Quantum Algorithms for Compositional Text Processing—0
Semantics or spelling? Probing contextual word embeddings with orthographic noiseCode0
Local Topology Measures of Contextual Language Model Latent Spaces With Applications to Dialogue Term Extraction—0
Strong and weak alignment of large language models with human valuesCode0
Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages—0
ML-EAT: A Multilevel Embedding Association Test for Interpretable and Transparent Social ScienceCode0
Representation Bias of Adolescents in AI: A Bilingual, Bicultural StudyCode0
Misinforming LLMs: vulnerabilities, challenges and opportunities—0
Ontological Relations from Word Embeddings—0
You shall know a piece by the company it keeps. Chess plays as a data for word2vec models—0
Appformer: A Novel Framework for Mobile App Usage Prediction Leveraging Progressive Multi-Modal Data Fusion and Feature Extraction—0
The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European LanguagesCode0
On Initializing Transformers with Pre-trained Embeddings—0
R-SFLLM: Jamming Resilient Framework for Split Federated Learning with Large Language Models—0
WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question AnsweringCode2
Cross-Lingual Word Alignment for ASEAN Languages with Contrastive Learning—0
Investigating the Contextualised Word Embedding Dimensions Specified for Contextual and Temporal Semantic ChangesCode0
Deep Image-to-Recipe TranslationCode0
Spiking Convolutional Neural Networks for Text ClassificationCode1
MT2ST: Adaptive Multi-Task to Single-Task LearningCode1
CLIP-Decoder : ZeroShot Multilabel Classification using Multimodal CLIP Aligned RepresentationCode0
Evaluating Contextualized Representations of (Spanish) Ambiguous Words: A New Lexical Resource and Empirical Analysis—0
Show:102550
← PrevPage 5 of 161Next →

No leaderboard results yet.