When Good Verifiers Go Bad: Silent Negative Transfer in Verifier-Guided VLM Training
Verifier reliability is not portable across tasks. A verifier-guided self-DPO pipeline with genuine held-out gains on MathVista (+9.6 points on self-training data, +8.0 held out) can be harmful on MMMU. The failure is invisible from the target-task self-training signal: over six learner-verifier configurations, MMMU self-training performance still improves by +3.52 points while held-out performance drops by 1.42 points. We call this silent negative transfer: a verifier validated as useful before can still show signatures of successful self-training after its induced update stops transferring to unseen data. Downstream failure alone cannot diagnose this: poor generalization may mean the ve...
| Authors | Jianzhe Lin |
|---|---|
| Primary category | cs.CR |
| Published | 12 June 2026 |
| Last updated at source | 25 September 2026 |
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