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  2. Zero-shot learning - Wikipedia

    en.wikipedia.org/wiki/Zero-shot_learning

    The first paper on zero-shot learning in computer vision appeared at the same conference, under the name zero-data learning. [4] The term zero-shot learning itself first appeared in the literature in a 2009 paper from Palatucci, Hinton, Pomerleau, and Mitchell at NIPS’09. [5] This terminology was repeated later in another computer vision ...

  3. T5 (language model) - Wikipedia

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

    blog.research.google /2020 /02 /exploring-transfer-learning-with-t5.html 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 ...

  4. One-shot learning (computer vision) - Wikipedia

    en.wikipedia.org/wiki/One-shot_learning...

    One-shot learning is an object categorization problem, found mostly in computer vision. Whereas most machine learning -based object categorization algorithms require training on hundreds or thousands of examples, one-shot learning aims to classify objects from one, or only a few, examples.

  5. Chinchilla (language model) - Wikipedia

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

    It is named "chinchilla" because it is a further development over a previous model family named Gopher.Both model families were trained in order to investigate the scaling laws of large language models.

  6. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  7. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    In-context learning, refers to a model's ability to temporarily learn from prompts.For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning.

  8. DeepSeek - Wikipedia

    en.wikipedia.org/wiki/DeepSeek

    DeepSeek (Chinese: 深度求索; pinyin: Shēndù Qiúsuǒ) is a Chinese artificial intelligence company that develops open-source large language models (LLMs). Based in Hangzhou, Zhejiang, it is owned and funded by Chinese hedge fund High-Flyer, whose co-founder, Liang Wenfeng, established the company in 2023 and serves as its CEO.

  9. Few-shot learning - Wikipedia

    en.wikipedia.org/wiki/Few-shot_learning

    One-shot learning (computer vision) Topics referred to by the same term This disambiguation page lists articles associated with the title Few-shot learning .

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