The Effects of Visual Priming on Cooperative Behavior in Vision-Language Models
arXiv cs.AI / 5/1/2026
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Key Points
- The paper studies how visual priming affects vision-language models’ cooperative behavior in the Iterated Prisoner’s Dilemma (IPD) testbed.
- It tests whether images representing kindness/helpfulness versus aggressiveness/selfishness, as well as color-coded reward matrices, change the models’ decision patterns.
- Experiments across multiple state-of-the-art VLMs show that both image content and color cues can shift behavior, but with model-dependent susceptibility.
- The authors evaluate mitigation approaches—prompt modifications, Chain-of-Thought prompting, and visual token reduction—and find they vary in effectiveness across different VLMs.
- The work argues that VLM deployment in visually rich and safety-critical settings requires more robust evaluation frameworks to account for these behavioral influences.
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