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E-Reverance

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  1. Video Generation Models Are General-Purpose Vision Learners (genception.github.io)
    1 points 0
  2. Universal Learning of Nonlinear Dynamics (arxiv.org)
    1 points 0
  3. Learning-to-Optimize via Deep Unfolded Flows (mit-realm.github.io)
    1 points 0
  4. A Theory of Contrastive Learning with Natural Images (arxiv.org)
    2 points 0
  5. Lingbot Vision (technology.robbyant.com)
    1 points 0
  6. Zero-Flow Encoders (arxiv.org)
    1 points 0
  7. Dispersion loss counteracts embedding condensation in small language models (chenliu-1996.github.io)
    1 points 8
  8. Simplified Sparse Attention via Gist Tokens (arxiv.org)
    4 points 0
  9. Continuity-Enhancing Degree Elevation and Splits (graphics.cs.utah.edu)
    2 points 0
  10. Forward Self Models (jagilley.github.io)
    2 points 0
  11. Tapered Language Models (arxiv.org)
    3 points 0
  12. Everything is logarithms (alexkritchevsky.com)
    313 points 21
  13. Explaining Attention with Program Synthesis (arxiv.org)
    2 points 0
  14. Sparsely gated tiny linear experts (arxiv.org)
    3 points 0
  15. Training-Free Single-Image Diffusion Models (haojunqiu.github.io)
    6 points 0
  16. Simple input–output dependencies explain neuronal activity (nature.com)
    4 points 0
  17. Self Teaching Autoencoder (the-puzzler.github.io)
    2 points 0
  18. Distance Marching for Generative Modeling (arxiv.org)
    1 points 0
  19. A Theory of Generalization in Deep Learning (arxiv.org)
    4 points 0
  20. Neural similarity predicts whether strangers become friends (nature.com)
    4 points 0
  21. Generation Is Required for Data-Efficient Perception (arxiv.org)
    1 points 0
  22. Flow Map Learning via Nongradient Vector Flow [pdf] (openreview.net)
    26 points 1
  23. How to Generate Text in One Step (one-step-lm.github.io)
    3 points 0
  24. Neural Particle Automata: Learning Self-Organizing Particle Dynamics (arxiv.org)
    1 points 0
  25. Open AI's competition spammed by AI slop (github.com)
    5 points 0