Joint Self-Supervised Compression Method for ARC-AGI Problem Solving

Joint Self-Supervised Compression Method for ARC-AGI Problem Solving

Yacine Mahdid via YouTube Direct link

- does the method work with ARC AGI v2?:

11 of 24

11 of 24

- does the method work with ARC AGI v2?:

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Joint Self-Supervised Compression Method for ARC-AGI Problem Solving

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  1. 1 - Intro:
  2. 2 - overview of the method:
  3. 3 - related works HRM/TRM/CompressARC:
  4. 4 - method overview:
  5. 5 - interview with author:
  6. 6 - background of mithil:
  7. 7 - overview of the intuition:
  8. 8 - training flow of the method:
  9. 9 - data augmentation is bad:
  10. 10 - why are you so interested by ARC?:
  11. 11 - does the method work with ARC AGI v2?:
  12. 12 - why so few compression method?:
  13. 13 - what is joint self supervised learning?
  14. 14 - explicit vs implicit mdl:
  15. 15 - connection between mdl and TRM?:
  16. 16 - is this method a general problem solver?:
  17. 17 - is compression enough for this benchmark?:
  18. 18 - architecture choices:
  19. 19 - how much does the 3D RoPE helps?:
  20. 20 - how to scale this?:
  21. 21 - dumbest idea ever:
  22. 22 - how to remove data augmentation?:
  23. 23 - about test time training:
  24. 24 - Conclusion:

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