BEYOND SCALAR BUDGETS: AUDITING RESOURCE SUFFICIENCY DECISIONS IN PEFT

Parameter-efficient fine-tuning (PEFT) seeks lower-resource configurations that meet a specified quality tolerance. We study whether simple resource rules preserve the sufficiency decisions obtained from directly trained configurations. Specifically, we audit rank thresholds, composition of separately tested parameter and data reductions, and interchangeability at equal parameter count. Across the tested settings, all three rules can disagree with measured decisions: passing ranks need not admit a threshold, separately passing reductions can fail jointly, and equal-count configurations can receive different all-seed labels. We formulate a finite decision-validity audit that compares rule-implied decisions with same-seed paired measurements and quantifies departures from monotonicity on complete rank–data grids. Offline replays translate these violations into concrete selection errors: missed lower-resource passing configurations and false-sufficient predictions. On prospectively frozen GSM8K grids, Qwen 1.5B and 7B configurations incur worst-seed losses below 1 pp relative to their rank-eight/full-pool references while using one eighth of the adapter parameters and 3.85-fold or 1.93-fold fewer distinct examples visited. These results support validating resource rules against measured configurations rather than assuming that scalar budgets preserve sufficiency.