BEAGLE's HIGH and LOW performer profiles differentiate by SRL strategy: HIGH performers allocate 72% of steps to PLANNING and MONITORING while LOW performers spend 50.8% trapped in ENACTING¶

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Simulated HIGH and LOW profiles reproduce the wheel-spinning pattern: HIGH performers spend 72% of steps planning and monitoring; LOW performers spend 50.8% in ENACTING. → Hanchen David Wang 2026

Evidence¶

Hanchen David Wang 2026¶

Hanchen David Wang, Clayton Cohn, Zifan Xu, Siyuan Guo, Gautam Biswas, Meiyi Ma. (2026). BEAGLE: Behavior-Enforced Agent for Grounded Learner Emulation. Preprint. https://arxiv.org/abs/2602.13280 doi:10.48550/arxiv.2602.13280

q2 · i? · design · r2

Performance-differentiation analysis in the RQ1 behavioral-fidelity evaluation, comparing BEAGLE runs configured with HIGH versus LOW behavioral profiles. The paper reports profile-driven solve-rate gaps that scale with backbone capability (e.g., +40% on Gemini 2.5 Flash), whereas vanilla LLMs show no profile sensitivity (+0%).

"HIGHperformers allocate 72% of steps to PLANNING and MONITORING , while LOWperformers spend 50.8% trapped in ENACTING (Fig. 6), reproducing the "wheel-spinning" pattern documented in SRL literature [3]."

Discussion¶

Related Claims¶

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