RESEARCH · RESEARCH · #2466
Inheritance as an Admission Test for LLM Prompt Merge Operators (arXiv:2610.29023v1)
The paper proposes a statistical "admission test" for prompt-merge operators used when composing LLM agents: a merge is only accepted if the child moves measurably toward the donor beyond the operator's zero-dose effect and the lower confidence bound on that movement reaches half the requested dose. Experiments using gemini-3.1-flash-lite on a single negotiation task found tactic-append admitted, free-rewrite rejected, template-append undetermined on re-probe (but moved on initial probe), and constrained-rewrite admitted in the open loop; no fixed-oracle arm was run and results are reported on a single task.
KEY POINTS
- The paper proposes a statistical "admission test" for prompt-merge operators used when composing LLM agents: a merge is only accepted if the child moves measurably toward the donor beyond the operator's zero-dose effect and the lower confidence bound on that movement reaches half the requested dose.
- Experiments using gemini-3.1-flash-lite on a single negotiation task found tactic-append admitted, free-rewrite rejected, template-append undetermined on re-probe (but moved on initial probe), and constrained-rewrite admitted in the open loop; no fixed-oracle arm was run and results are reported on a single task.
- Provides a measurable, conservative criterion to decide when prompt-merge changes genuinely improve an LLM agent relative to baseline operator effects, which helps avoid false positives from population-elimination effects in iterative agent improvement.
WHY IT MATTERS
Provides a measurable, conservative criterion to decide when prompt-merge changes genuinely improve an LLM agent relative to baseline operator effects, which helps avoid false positives from population-elimination effects in iterative agent improvement.