In a groundbreaking development, researchers from MIT have introduced a novel training method that significantly enhances vision-language models’ ability to locate personalized objects in new scenes. This advancement addresses a critical limitation in generative AI, where models like GPT-5 excel at recognizing general objects but struggle with identifying specific items, such as a pet among many others. By leveraging carefully curated video-tracking data, the new approach allows these models to learn from context rather than relying solely on pre-existing knowledge.