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  2. Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Contrastive_Language-Image...

    Contrastive Language-Image Pre-training (CLIP) is a technique for training a pair of neural network models, one for image understanding and one for text understanding, using a contrastive objective. [1]

  3. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    DALL-E was developed and announced to the public in conjunction with CLIP (Contrastive Language-Image Pre-training). [23] CLIP is a separate model based on contrastive learning that was trained on 400 million pairs of images with text captions scraped from the Internet. Its role is to "understand and rank" DALL-E's output by predicting which ...

  4. Self-supervised learning - Wikipedia

    en.wikipedia.org/wiki/Self-supervised_learning

    Contrastive Language-Image Pre-training (CLIP) allows joint pretraining of a text encoder and an image encoder, such that a matching image-text pair have image encoding vector and text encoding vector that span a small angle (having a large cosine similarity).

  5. OpenAI - Wikipedia

    en.wikipedia.org/wiki/OpenAI

    First described in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to GPT-2. [ 187 ] [ 188 ] [ 189 ] OpenAI stated that the full version of GPT-3 contained 175 billion parameters , [ 189 ] two orders of magnitude larger than the 1.5 billion [ 190 ] in the full version of ...

  6. Talk:Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Talk:Contrastive_Language...

    Talk: Contrastive Language-Image Pre-training. Add languages. Page contents not supported in other languages. Article; Talk; ... Download QR code; Print/export

  7. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    That development led to the emergence of large language models such as BERT (2018) [28] which was a pre-trained transformer (PT) but not designed to be generative (BERT was an "encoder-only" model). Also in 2018, OpenAI published Improving Language Understanding by Generative Pre-Training, which introduced GPT-1, the first in its GPT series. [29]

  8. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    The model has two possible training schemes to produce word vector representations, one generative and one contrastive. [27] The first is word prediction given each of the neighboring words as an input. [28] The second is training on the representation similarity for neighboring words and representation dissimilarity for random pairs of words. [10]

  9. Contrastive linguistics - Wikipedia

    en.wikipedia.org/wiki/Contrastive_linguistics

    Contrastive linguistics is a practice-oriented linguistic approach that seeks to describe the differences and similarities between a pair of languages (hence it is occasionally called "differential linguistics").