Hackathon Winners Present: Do Multilingual Vision-Language Models Abstain under Cross-Modal Conflict in Low-Resource Languages?

​A model sees a red car. The caption says blue. Which does it trust?

​In English, it sometimes catches the conflict. In Hindi and Telugu, that safety check breaks down.

​Anvesh Reddy Lankala, Vicky Feliren, and Akansh Jain built a benchmark across English, Hindi, and Telugu and tested 9 vision-language models. Qwen2.5-VL-7B looked safe on standard metrics — but overrode correct visual evidence 81% of the time when text disagreed.

​Winners, Asia-Pacific track, Apart Research's Global South AI Safety Hackathon.

​Hosted by AI Safety India, Weekly Discussion Series.

​Format:
- Research presentation
- Q&A, open floor
- AI Safety Mixer

​Speakers
Anvesh Reddy Lankala
Vicky Feliren
Akansh Jain

​Full submission: https://apartresearch.com/project/do-multilingual-visionlanguage-models-abstain-under-crossmodal-conflict-in-lowresource-languages-hcsp?utm_source=luma