arXiv Machine Learning August 12, 2026 By Ying Yuan

Detecting an Effect Is Not Learning to Act on It: A Reward-SNR Floor for LLM Acquisition Agents

Read the original on arXiv Machine Learning →

arXiv:2608. 10441v1 Announce Type: new Abstract: Many pipelines can pay a per-example cost to acquire an auxiliary, model-derived observation -- an LLM's structured reasoning, a slow oracle, an expensive measurement -- and then must decide when the acquired signal is worth using.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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