[Eval Request] Kai-30B-Instruct (ADS Framework)
Model Link: NoesisLab/Kai-30B-Instruct
Methodology: Adaptive Dual-Search (ADS) Type: Reasoning / Intelligence / Instruction-Following
Description:
I would like to request an evaluation for Kai-30B-Instruct. This model is a 34B parameter reasoning engine developed using our ADS (Adaptive Dual-Search) framework.
Unlike traditional "Self-Talk" or "CoT" models that rely on verbose step-by-step reasoning to "think," Kai-30B-Instruct focuses on Logical Crystallization. By enforcing a log-barrier penalty on the Shannon entropy of the output distribution during SFT, we induced an $O(1)$ inference manifold.
Key Features for UGI:
- Direct Reasoning: It delivers high-precision answers directly, bypassing the need for "thought" tags or verbose chain-of-thought.
- Crystallized Logic: It maintains a ~80% token accuracy on complex reasoning tasks while keeping a near-zero entropy state (Crystallization).
- Zero-Shot Robustness: Specifically designed to collapse the search space into a simplex vertex, making it extremely fast and decisive for hard logic/math problems.
We believe Kai-30B-Instruct will offer a unique perspective on the "Intelligence" axis of the UGI Leaderboard, showcasing that true reasoning doesn't always need millions of "thinking" tokens.