New Training Method Achieves Sub-1bit Compression
BankApprehensive7612 · reddit · 2026-07-17
This post introduces the paper Requential Coding. The author claims researchers used a new tutorial-style training method to achieve sub-1 bit compression without obvious overfitting or memorization issues.
The core concept:
- The teacher model selects training samples from the student's own distribution.
- The student model trains itself by generating samples, forming a higher-density information encoding.
- The author believes this method improves generalization and allows existing neurons to be more fully utilized.
The poster adds their own take: this acts more like a "re-topologization" rather than mere compression, drawing parallels to Microsoft's Phi series attempts—training with a smaller vocabulary/simplified knowledge system before gradually expanding.
The post includes links to the paper and GitHub repo, suggesting this is a new direction ripe for reproduction and verification.
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