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Methods/fastText

fastText

Natural Language ProcessingIntroduced 2000240 papers

Description

fastText embeddings exploit subword information to construct word embeddings. Representations are learnt of character $n$ -grams, and words represented as the sum of the $n$ -gram vectors. This extends the word2vec type models with subword information. This helps the embeddings understand suffixes and prefixes. Once a word is represented using character $n$ -grams, a skipgram model is trained to learn the embeddings.

Papers Using This Method

Speak2Sign3D: A Multi-modal Pipeline for English Speech to American Sign Language Animation2025-07-09 Guarded Query Routing for Large Language Models2025-05-20 Ultra-FineWeb: Efficient Data Filtering and Verification for High-Quality LLM Training Data2025-05-08 myNER: Contextualized Burmese Named Entity Recognition with Bidirectional LSTM and fastText Embeddings via Joint Training with POS Tagging2025-04-05 A Data-driven Investigation of Euphemistic Language: Comparing the usage of "slave" and "servant" in 19th century US newspapers2025-03-19 Text classification using machine learning methods2025-02-27 Poster: Long PHP webshell files detection based on sliding window attention2025-02-26 A Multi-tiered Solution for Personalized Baggage Item Recommendations using FastText and Association Rule Mining2025-01-16 Sentiment Analysis in Twitter Social Network Centered on Cryptocurrencies Using Machine Learning2025-01-16 Research on Violent Text Detection System Based on BERT-fasttext Model2024-12-21 UnMA-CapSumT: Unified and Multi-Head Attention-driven Caption Summarization Transformer2024-12-16 On Importance of Code-Mixed Embeddings for Hate Speech Identification2024-11-27 BERT or FastText? A Comparative Analysis of Contextual as well as Non-Contextual Embeddings2024-11-26 From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models2024-11-06 Generic Embedding-Based Lexicons for Transparent and Reproducible Text Scoring2024-11-01 LightFusionRec: Lightweight Transformers-Based Cross-Domain Recommendation Model2024-10-21 Stress Detection on Code-Mixed Texts in Dravidian Languages using Machine Learning2024-10-08 Beyond Film Subtitles: Is YouTube the Best Approximation of Spoken Vocabulary?2024-10-04 Individuation in Neural Models with and without Visual Grounding2024-09-27 An Evaluation of Sindhi Word Embedding in Semantic Analogies and Downstream Tasks2024-08-28