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Model Atlas

Papers

Published paper pages that break one report or publication into its main claims, linked entities, and supporting sources.

  • Attention Is All You Need

    The 2017 paper that introduced the transformer, using self-attention as the main way tokens mix information in encoder-decoder sequence models.

  • BERT Paper

    The paper that introduced deep bidirectional transformer encoders trained with masked language modeling and fine-tuned for language understanding tasks.

  • DeepSeek-V4

    A technical report that bundles DeepSeek-V4 architecture, long-context attention, post-training methods, and serving systems into one connected release.

  • GPT-2 Report

    A technical report that introduced GPT-2 as a large decoder-only language model trained with broad next-token pretraining and byte-level BPE tokenization.

  • Latent Diffusion Models

    The research paper behind Stable Diffusion-style image generation: compress images into a latent space, denoise there instead of in pixel space, then decode the result.

  • Learning Transferable Visual Models From Natural Language Supervision

    The CLIP paper introduced contrastive language-image pretraining with separate image and text encoders that map paired captions and images into one shared embedding space.