Publications (6)
Apple Intelligence Foundation Language Models: Tech Report 2025
Ethan Li, Anders Boesen Lindbo Larsen, Chen Zhang +395
We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: i a 3B-parameter on-device model opti…
Probabilistic Attention for Interactive Segmentation
Prasad Gabbur, Manjot Bilkhu, Javier Movellan
We provide a probabilistic interpretation of attention and show that the standard dot-product attention in transformers is a special case of Maximum A Posteriori (MAP) inference. T…
MixAtlas: Uncertainty-aware Data Mixture Optimization for Multimodal LLM Midtraining
Bingbing Wen, Sirajul Salekin, Feiyang Kang +4
Domain reweighting can improve sample efficiency and downstream generalization, but data-mixture optimization for multimodal midtraining remains largely unexplored. Current multimo…
RubiCap: Rubric-Guided Reinforcement Learning for Dense Image Captioning
Tzu-Heng Huang, Sirajul Salekin, Javier Movellan +2
Dense image captioning is critical for cross-modal alignment in vision-language pretraining and text-to-image generation, but scaling expert-quality annotations is prohibitively ex…
Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights
Tzu-Heng Huang, Manjot Bilkhu, John Cooper +2
Large-scale web-crawled datasets contain noise, bias, and irrelevant information, necessitating data selection techniques. Existing methods depend on hand-crafted heuristics, downs…
Discriminately Decreasing Discriminability with Learned Image Filters
Jacob Whitehill, Javier Movellan
In machine learning and computer vision, input images are often filtered to increase data discriminability. In some situations, however, one may wish to purposely decrease discrimi…