Near-Duplicate Image Selection Transfers Preferences in Vision-Language Models
Subliminal learning is the phenomenon in which a model transmits its preferences to another model through data that do not explicitly express them. As models increasingly curate training data for other models, we ask whether this transfer can arise from choosing among near-duplicate images while keeping the source photographs and human-written captions fixed. For each photograph, a curator selects one of eight near-duplicate variants by caption likelihood, without target-specific prompts. Students trained on target-preferring curators' selections show higher mean target-versus-alternatives log-likelihood ratios in an image-free readout than students trained on neutral selections. Under a ...
| Authors | Jaeyoung Kim, Eunseok Kim, Dongsuk Jang et al. |
|---|---|
| Primary category | cs.LG |
| Published | 20 October 2026 |
| Last updated at source | 20 October 2026 |
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