Beyond Update Counts: A Control Map for Evaluating Test-Time Model Updates

arXiv:2610.36109v1 Announce Type: new Abstract: Test-time updating lets a language model change persistent state after training---such as model weights, adapter parameters, or a memory module---before or while answering queries. Existing evaluations often compare systems using update count or frequency and performance measured immediately afterward. These summaries omit what is updated, where, when, and in what order. The same total can therefore hide an important difference: one system may answer after one update while another answers after two.