بعد أكاديمية كاوست
Mohammed is an Information Systems graduate of King Saud University and completed the KAUST Academy AI summer program at the University of Oxford in 2026. Mohammed was also one of 20 Saudi students chosen for the Mawhiba and Huawei AI program in China.
المشروع الصيفي
تخصص الذكاء الاصطناعي · دفعة 2026
Generative Late-Interaction Embeddings For Visual Document Retrieval
Late-interaction models such as ColPali achieve strong visual document retrieval performance but require storing many token embeddings per page. We propose compact generative codes that capture each page’s low-dimensional token manifold. The project has two central components: efficient retrieval and on-demand vector generation. The codes can be scored directly using standard MaxSim for first-stage retrieval, then used to generate richer token representations on demand for more accurate reranking—without permanently storing those vectors. Anchored by cluster centroids and refined using the complete token set, the codes are trained through knowledge distillation from a frozen retrieval encoder.
مع أكاديمية كاوست
- دفعة 2026
جامعة أكسفورد · المدرسة الصيفية للذكاء الاصطناعي
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