Source record

Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.25215.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Systematic ablation on a production agentic platform evaluated tradeoffs in protein characterization workflows across federation topology, RL versus LLM-driven harnesses, model choice, and prompt expertise. Model choice dominated prediction quality (Opus 92-94% vs o4-mini 40-50%). A PPO policy matched accuracy at zero token cost; federation imposed negligible penalty.

Concretely quantifies when to deploy a cheap deterministic policy versus a costly reasoning LLM in a production scientific agent stack, with hard numbers on accuracy, latency, and reproducibility.

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