Papers readers want explained next

Every requested paper, ranked by votes. Upvote what you want next, or add one. Paste an arXiv link and we pull the title straight from arXiv.

• 001
  An Image is Worth 16x16 Words (ViT)

  arXiv:2010.11929
  Vision
• 002
  Auto-Encoding Variational Bayes (VAE)

  arXiv:1312.6114
  Theory
• 003
  BERT: Pre-training of Deep Bidirectional Transformers

  arXiv:1810.04805
  LLMs
• 004
  Chain-of-Thought Prompting Elicits Reasoning

  arXiv:2201.11903
  LLMs
• 005
  Deep Residual Learning for Image Recognition (ResNet)

  arXiv:1512.03385
  Vision
• 006
  Exploring the Limits of Transfer Learning (T5)

  arXiv:1910.10683
  LLMs
• 007
  Generative Adversarial Networks

  arXiv:1406.2661
  Theory
• 008
  High-Resolution Image Synthesis with Latent Diffusion (Stable Diffusion)

  arXiv:2112.10752
  Diffusion
• 009
  LLaMA: Open and Efficient Foundation Language Models

  arXiv:2302.13971
  LLMs
• 010
  Mistral 7B

  arXiv:2310.06825
  LLMs
• 011
  Neural Ordinary Differential Equations

  arXiv:1806.07366
  Theory
• 012
  Proximal Policy Optimization (PPO)

  arXiv:1707.06347
  RL & alignment
• 013
  Retrieval-Augmented Generation (RAG)

  arXiv:2005.11401
  LLMs
• 014
  Robust Speech Recognition via Weak Supervision (Whisper)

  arXiv:2212.04356
  Multimodal
• 015
  Scaling Laws for Neural Language Models

  arXiv:2001.08361
  Training
• 016
  Segment Anything (SAM)

  arXiv:2304.02643
  Vision
• 017
  Training Language Models to Follow Instructions (InstructGPT)

  arXiv:2203.02155
  RL & alignment
• 018
  U-Net: Convolutional Networks for Biomedical Segmentation

  arXiv:1505.04597
  Vision