KAN author's 'meta model' framing: models that predict and design models
ZimingLiu11 · x · 2026-10-31
Ziming Liu (KAN first author) continues his thread on the "meta model" concept: it's not tied to any specific architecture — an LLM, TabPFN, or KAN can all serve. What matters is the framing: a model that predicts other models' performance and ultimately designs models. He adds that KANs boost TabPFN's performance and yield interpretable insights into where residual errors come from.
More from Research
- LLM judges are strongly biased toward position, researcher warns to randomize everything — antoine_chaffin · 2026-10-31
- The kernel trick explained: how lifting one feature makes rings linearly separable — techNmak · 2026-10-31
- 15-year-old builds sliding window attention from scratch: 4.16x speedup, 21% less VRAM — vankownlaw · 2026-10-31
- Overfitting explained with two students and two exams — cneuralnetwork · 2026-10-31
- Betelgeuse runs 68GB Qwen MoE bit-exact at 22 tok/s on RTX 3060 + 16GB RAM — zyxciss · 2026-10-31
- EdgeRock-4B open-sourced with fixed 72MiB KV cache, 99.1% less memory than base — testingcatalog · 2026-10-31