Phantasia: Context-Adaptive Backdoors in Vision Language Models

Abstract

Recent advances in Vision-Language Models (VLMs) have greatly enhanced the integration of visual perception and linguistic reasoning, driving rapid progress in multimodal understanding. Despite these achievements, the security of VLMs, particularly their vulnerability to backdoor attacks, remains significantly underexplored. Existing backdoor attacks on VLMs are still in an early stage of development, with most current methods relying on generating poisoned responses that contain fixed, easily i

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@misc{tran2026phantasia,
  title = {{Phantasia: Context-Adaptive Backdoors in Vision Language Models}},
  author = {Nam Duong Tran and Phi Le Nguyen},
  year = {2026},
  month = apr,
  eprint = {2604.08395},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.08395}
}