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Keyword: tomas-mikolov

Article:Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean18 Sept 2026
Distributed Representations of Words and Phrases and their Compositionality
The authors present extensions to the continuous Skip-gram model to improve vector quality and training speed. The work introduces subsampling of frequent words, negative sampling as an alternative to hierarchical softmax, and a technique for learning distributed representations of idiomatic phrases.
From Video: Building an LLM from Scratch: Neural Networks, Tokenization, and Transformers
AI & LLMs· Research
Article:Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean18 Sept 2026
Efficient Estimation of Word Representations in Vector Space
A research team led by Tomas Mikolov introduces two novel model architectures designed to compute continuous vector representations of words from massive datasets. The approach delivers higher accuracy with substantially lower computational requirements than prior neural network methods.
From Video: Building an LLM from Scratch: Neural Networks, Tokenization, and Transformers
AI & LLMs· Research

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Distributed Representations of Words and Phrases and their Compositionality

Efficient Estimation of Word Representations in Vector Space

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