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Word Embeddings
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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.
<span style="color:grey; opacity: 0.6">( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
"Hunt Takes Hare": Theming Games Through Game-Word Vector Translation
Exploring Public Attention in the Circular Economy through Topic Modelling with Twin Hyperparameter Optimisation
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
LGDE: Local Graph-based Dictionary Expansion
A Comprehensive Analysis of Static Word Embeddings for Turkish
Span-Aggregatable, Contextualized Word Embeddings for Effective Phrase Mining
Word-specific tonal realizations in Mandarin
Enhancing Scalability of Metric Differential Privacy via Secret Dataset Partitioning and Benders Decomposition
DALLMi: Domain Adaption for LLM-based Multi-label Classifier
1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy
CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models
Bridging Vision and Language Spaces with Assignment Prediction
WordDecipher: Enhancing Digital Workspace Communication with Explainable AI for Non-native English Speakers
Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval
IITK at SemEval-2024 Task 1: Contrastive Learning and Autoencoders for Semantic Textual Relatedness in Multilingual Texts
BanglaAutoKG: Automatic Bangla Knowledge Graph Construction with Semantic Neural Graph Filtering
Robust Concept Erasure Using Task Vectors
PejorativITy: Disambiguating Pejorative Epithets to Improve Misogyny Detection in Italian Tweets
Breaking the Silence Detecting and Mitigating Gendered Abuse in Hindi, Tamil, and Indian English Online Spaces
DiLM: Distilling Dataset into Language Model for Text-level Dataset Distillation
The Shape of Word Embeddings: Quantifying Non-Isometry With Topological Data Analysis
Quantum Natural Language Processing
SemRoDe: Macro Adversarial Training to Learn Representations That are Robust to Word-Level Attacks
Debiasing Sentence Embedders through Contrastive Word Pairs
Fusion approaches for emotion recognition from speech using acoustic and text-based features
Projective Methods for Mitigating Gender Bias in Pre-trained Language Models
Introducing Syllable Tokenization for Low-resource Languages: A Case Study with Swahili
A comparative analysis of embedding models for patent similarity
Advancing Fake News Detection: Hybrid DeepLearning with FastText and Explainable AI
An efficient domain-independent approach for supervised keyphrase extraction and ranking
Empowering Segmentation Ability to Multi-modal Large Language Models
Leveraging Linguistically Enhanced Embeddings for Open Information Extraction
Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representations
Identifying and interpreting non-aligned human conceptual representations using language modeling
VNLP: Turkish NLP Package
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