Uploaded November 2025 | Updated September 2026, 2 hours ago
What if your vision language model isn’t actually seeing… but mostly guessing from text? 👀
Letitia Parcalabescu explains it perfectly: when VLMs rely too heavily on text, they start hallucinating answers based on the most common phrasing in their training data instead of what’s in the image. Ask “How many cats are there?” and even if the image shows five, the model might say two simply because “two” appears more often in similar prompts.
This is the hidden trap behind text-driven hallucinations. And unless we explicitly measure grounding, these models will keep sounding confident while being wrong.
I love this kind of research because it shows exactly where our tools break and where we need to push next, especially in high-stakes domains like medicine or robotics.
#visionlanguagemodels #VLM #AIresearch
What if your vision language model isn’t actually seeing… but mostly guessing from text? 👀
Letitia Parcalabescu explains it perfectly: when VLMs rely too heavily on text, they start hallucinating answers based on the most common phrasing in their training data instead of what’s in the image. Ask “How many cats are there?” and even if the image shows five, the model might say two simply because “two” appears more often in similar prompts.
This is the hidden trap behind text-driven hallucinations. And unless we explicitly measure grounding, these models will keep sounding confident while being wrong.
I love this kind of research because it shows exactly where our tools break and where we need to push next, especially in high-stakes domains like medicine or robotics.
#visionlanguagemodels #VLM #AIresearch
