kalomaze: You don't need an analytic transfer theory, just a learnable transfer-extrapolation function
kalomaze · x · 2026-09-12
Continuing the RLVR generalization discussion, kalomaze argues you don't necessarily need a strong mechanistic theory of transfer (which may not exist in closed form) before training. What you need instead is a strong learned function of transfer extrapolation for a given policy — something he says is constructible, replacing crude heuristics like domain similarity.
More from Research
- Two fruit-fly connectome models (138,639 neurons each) play Gomoku locally on an M3 Pro — chrisalbon · 2026-09-12
- Liquid AI × Insilico Medicine drug discovery foundation model accepted at EMNLP 2026 — JosephJacks_ · 2026-09-12
- Hameroff revisits 1990 microtubule automata simulations, clashing with MIT's Miller Lab — JosephJacks_ · 2026-09-12
- 25 Fields Medalists sign open letter blasting AI firms for treating solved problems as benchmarks — 智东西 · 2026-09-12
- 100 LLM Agents Run a Town Economy for 26 Weeks — and Money Stops Moving — omarsar0 · 2026-09-12
- Simons Institute holds workshop on AI's rapid acceleration of mathematics and theoretical CS — jasondeanlee · 2026-09-12