Notes

Study of papers that are of personal interest

• Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
  Slides / Paper
• T-MARS: Improving Visual Representations by Circumventing Text Feature Learning
  Slides / Paper
• What Do We Learn from Inverting CLIP Models?
  Slides / Paper
• GLIGEN: Open-Set Grounded Text-to-Image Generation
  Slides / Paper
• SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
  Slides / Paper
• Tree of Thoughts: Deliberate Problem Solving with Large Language Models
  Slides / Paper
• Visual Instruction Tuning
  Slides / Paper
• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
  Slides / Paper
• LoRA: Low-Rank Adaptation of Large Language Models
  Slides / Paper
• Visual Prompting via Image Inpainting
  Slides / Paper
• Trainig Data Attribution for Diffusion Models
  Slides / Paper
• Optimizing DDPM Sampling with Shortcut Fine-Tuning
  Slides / Paper
• Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models
  Slides / Paper
• SELF-REFINE: Iterative Refinement with Self-Feedback
  Slides / Paper
• Generative Agents: Interactive Simulacra of Human Behavior
  Slides / Paper
• Consistency Models
  Slides / Paper
• Image as Set of Points
  Slides / Paper
• Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs
  Slides / Paper
• Git Re-Basin: Merging Models modulo Permutation Symmetries
  Slides / Paper