@lucazapp.bsky.social
🚀 We're hiring a Research Scientist, Machine Learning Research (MLR), Barcelona ☀️ 👉 Apply here: jobs.apple.com/en-us/detail... #MachineLearning #MLResearch #AI #Hiring #Apple #Barcelona #ResearchScientist #DeepLearning
AIML - Machine Learning Researcher - MLR - Jobs - Careers at Apple
Apply for a AIML - Machine Learning Researcher - MLR job at Apple. Read about the role and find out if it’s right for you.
jobs.apple.com
Check out our new work on conditioning pre-trained generative models via activation steering. LineAS has been accepted at NeurIPS 2025. Code and paper are online: 💻 github.com/apple/ml-lin... 📄 arxiv.org/abs/2503.10679
GitHub - apple/ml-lineas
Contribute to apple/ml-lineas development by creating an account on GitHub.
github.com
Pau Rodriguez@paurodriguez.bsky.social · 11mo ago🚀 Excited to share LinEAS, our new activation steering method accepted at NeurIPS 2025! It approximates optimal transport maps e2e to precisely guide 🧭 activations achieving finer control 🎚️ with ✨ less than 32 ✨ prompts! 💻https://github.com/apple/ml-lineas 📄https://arxiv.org/abs/2503.10679
New blog post that explains our work on Controlling Diffusion and LLMs using steering and optimal transport: machinelearning.apple.com/research/tra... This work will be presented at ICLR2025 in Singapore. See you there!
Controlling Language and Diffusion Models by Transporting Activations
Large generative models are becoming increasingly capable and more widely deployed to power production applications, but getting these…
machinelearning.apple.com
Pau Rodriguez@paurodriguez.bsky.social · 2y agoThrilled to share the latest work from our team at @Apple where we achieve interpretable and fine-grained control of LLMs and Diffusion models via Activation Transport 🔥 📄 arxiv.org/abs/2410.23054 🛠️ github.com/apple/ml-act 0/9 🧵
Thrilled to share the latest work from our team at @Apple where we achieve interpretable and fine-grained control of LLMs and Diffusion models via Activation Transport 🔥 📄 arxiv.org/abs/2410.23054 🛠️ github.com/apple/ml-act 0/9 🧵
Paper🧵 (cross-posted at X): When does composition of diffusion models "work"? Intuitively, the reason dog+hat works and dog+horse doesn’t has something to do with independence between the concepts being composed. The tricky part is to formalize exactly what this means. 1/
Preetum Nakkiran@preetumnakkiran.bsky.social · 2y agofinally managed to sneak my dog into a paper: arxiv.org/abs/2502.04549
🚨 One question that has always intrigued me is the role of different ways to increase a model's capacity: parameters, parallelizable compute, or sequential compute? We explored this through the lens of MoEs:
The Apple Machine Learning Research (MLR) team in Paris has openings for both FTE roles and a short-term post-doc position to contribute to our team's research agenda. Researchers at Apple's MLR (led by Samy Bengio) target impactful publications in top-tier ML venues and OSS.