On the Rejection Criterion for Proxy-based Test-time Alignment
Recent works proposed test-time alignment methods that rely on a small aligned model as a proxy that guides the generation of a larger base (unaligned) model. The implicit reward approach skews the large model distribution, whereas the nudging approach defers the generation of the next token to the small aligned model when the large base one is unconfident about its outcome. In this work, we first show that both approaches can be reduced to sampling from similar graphical models, where they differ only in the definition of a rejection criterion (or distribution). Moreover, we argue that the confidence criterion is ill-motivated due to linguistic phenomena like ambiguous phrasing. We propo...
| Authors | Ayoub Hammal, Pierre Zweigenbaum, Caio Corro |
|---|---|
| Primary category | cs.CL |
| Published | 17 April 2026 |
| Last updated at source | 20 April 2026 |
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