Agent Step Value: Auditing Evaluation-Channel Sensitivity in Black-Box Agent Traces
Reusing evaluator-derived step rewards across evaluation channels raises a measurement question: does the assigned direction remain stable? We define Agent Step Value (ASV) as a channel-indexed before/after target-margin gain and identify the state-by-channel interaction from a matched 2x2 design. Across frozen PubMed question-answering transitions, cross-channel gain signs disagree on 48.3% of comparisons, compared with 0.3% for same-channel retries. Transition interactions are nearly balanced in sign (median +0.014; 10% trimmed mean -0.033), but asymmetric negative magnitudes produce a positive direct mean and a negative generated-view mean under the empirical target mixture. Equal-targ...
| Authors | Andrew Zhang, Chengzhan Li |
|---|---|
| Primary category | cs.AI |
| Published | 5 July 2026 |
| Last updated at source | 9 October 2026 |
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