DEFT extends its Core–Slack split across layers to keep transfer learning stable
TheGradient · x · 2026-07-24
Layer-to-layer routing
This installment explains how DEFT propagates the Core/Slack split across layers. Core neurons connect to Core neurons, Slack to Slack, while cross-links are severed at time step zero for the forbidden directions.
The intended effect
By preserving only the allowed routes, the method tries to keep foundational features stable while letting new learning accumulate in the plastic branch. In the thread’s framing, this is what makes the system usable for continual learning and transfer learning rather than just compression.
Related event: DEFT Introduces Core-Slack Architecture to Prevent Catastrophic Forgetting(3 posts)→
More from Research
- 3D ResNet Paper Crosses 3,000 Citations Eight Years After CVPR 2018 — HirokatuKataoka · 2026-09-11
- Jeff Heaton's Intro to the Math of Neural Networks eBook Is Free to Download — blaizedsouza · 2026-09-11
- Mathematician Daniel Litt Launches Problem Repo to Track Human vs AI Progress: 15 Problems, 1 Solved — littmath · 2026-09-11
- Open ECDSA.fail challenge uses AI agents to shrink Shor's-algorithm quantum circuits for Bitcoin keys — StefanoGogioso · 2026-09-11
- Alex Townsend posts 200 open problems in numerical linear algebra for humans and AI agents — IgorCarron · 2026-09-11
- Navier-Stokes, Riemann, P vs NP: what this week's math buzzwords mean for you — koltregaskes · 2026-09-11