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  2. Paraphrasing (computational linguistics) - Wikipedia

    en.wikipedia.org/wiki/Paraphrasing...

    Applications of paraphrasing are varied including information retrieval, question answering, text summarization, and plagiarism detection. [1] Paraphrasing is also useful in the evaluation of machine translation, [2] as well as semantic parsing [3] and generation [4] of new samples to expand existing corpora. [5]

  3. Paraphrase - Wikipedia

    en.wikipedia.org/wiki/Paraphrase

    Machine learning models have been trained to generate paraphrases with specific properties, such as high semantic similarity and syntactic diversity, or to generate specific paraphrase types. [ 11 ] [ 12 ] Models that have high capacity in paraphrasing can be used for various applications.

  4. History of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/History_of_artificial...

    Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks.Their creation was inspired by biological neural circuitry. [1] [a] While some of the computational implementations ANNs relate to earlier discoveries in mathematics, the first implementation of ANNs was by psychologist Frank Rosenblatt, who developed the perceptron. [1]

  5. QuillBot - Wikipedia

    en.wikipedia.org/wiki/QuillBot

    Research from 2021 proposed that QuillBot could potentially be used for paraphrasing tasks, but indicated the importance of English language proficiency for using it properly. [ 7 ] [ 8 ] [ 9 ] See also

  6. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    Outline of machine learning; ... GPT-1 improved on previous best-performing models by 4.2% on semantic similarity (or paraphrase detection), ...

  7. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.

  8. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  9. Category:Machine learning - Wikipedia

    en.wikipedia.org/wiki/Category:Machine_learning

    Machine learning is a branch of statistics and computer science which studies algorithms and architectures that learn from observed facts. The main article for this category is Machine learning . Wikimedia Commons has media related to Machine learning .