CHERRY: Compressed Hierarchical Experts with Recurrent Representational Yield
Frontier language capability is usually bought with frontier compute; CHERRY shows a different trade. It is a sovereign Korean model family built on one principle: supervise the tokens that decide the answer, and let shared weights carry the rest. Under matched compute this exposes a sharp, reproducible dissociation---selected-token supervision preserves held-out discrimination yet collapses free generation, and a full-sequence anchor recovers only part of the gap. The same signal drives a heal-after-merge recurrent-representational-yield loop that collapses 48 layers to 6 unique blocks at near-dense parity (227M at loss 2.934 vs a 566M dense model at 2.926) and composes them by MoEE fusi...
| Authors | Dohyeon Kwon, Youngjin Park |
|---|---|
| Primary category | cs.CL |
| Published | 30 June 2026 |
| Last updated at source | 23 July 2026 |
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