Search: “apple-ml-research”

Generative models are often deployed to make decisions on behalf of users, such as vision-language models (VLMs) identifying which person in a room is a doctor to help visually impaired individuals. Y

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29 Apr 2026

LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning

DGX agent

Large Language Models (LLMs) demonstrate their reasoning ability through chain-of-thought (CoT) generation. However, LLM’s autoregressive decoding may limit the ability to revisit and refine earlier t

researchapple-ml-research

28 Apr 2026

Tutorials

Local Mechanisms of Compositional Generalization in Conditional Diffusion

tutorialsapple-ml-research

Conditional diffusion models appear capable of compositional generalization, i.e., generating convincing samples for out-of-distribution combinations of conditioners, but the mechanisms underlying thi

28 Apr 2026

StereoFoley: Object-Aware Stereo Audio Generation from Video

We present StereoFoley, a video-to-audio generation framework that produces semantically aligned, temporally synchronized, and spatially accurate stereo sound at 48 kHz. While recent generative video-

28 Apr 2026

Learning Long-Term Motion Embeddings for Efficient Kinematics Generation

Understanding and predicting motion is a fundamental component of visual intelligence. Although modern video models exhibit strong comprehension of scene dynamics, exploring multiple possible futures

24 Apr 2026

ParaRNN: Large-Scale Nonlinear RNNs, Trainable in Parallel

Recurrent Neural Networks (RNNs) are naturally suited to efficient inference, requiring far less memory and compute than attention-based architectures, but the sequential nature of their computation h

23 Apr 2026

Apple Machine Learning Research at ICLR 2026

Apple is advancing AI and ML with fundamental research, much of which is shared through publications and engagement at conferences in order to accelerate progress in this important field and support t

22 Apr 2026

Model Releases

Can Large Language Models Understand Context?

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Understanding context is key to understanding human language, an ability which Large Language Models (LLMs) have been increasingly seen to demonstrate to an impressive extent. However, though the eval

21 Apr 2026

International Conference on Learning Representations (ICLR) 2026

ICLR 2026 is a major international conference on machine learning and deep learning where Apple's research team will present their latest work and innovations in representation learning. The conferenc

17 Apr 2026

MixAtlas: Uncertainty-aware Data Mixture Optimization for Multimodal LLM Midtraining

This paper was accepted at the Workshop on Navigating and Addressing Data Problems for Foundation Models (NADPFM) at ICLR 2026. Principled domain reweighting can substantially improve sample efficienc

16 Apr 2026

ACM Human-Computer Interaction Conference (CHI) 2026

Apple is presenting new research at the ACM CHI Conference on Human Factors in Computing Systems, held in person in Barcelona, Spain, from April 13–17, 2026, and is a sponsor of the event. Research...

10 Apr 2026

A Theoretical Framework for Acoustic Neighbor Embeddings

This paper provides a theoretical framework for interpreting acoustic neighbor embeddings, which are representations of the phonetic content of variable-width audio or text in a fixed-dimensional embe

9 Apr 2026

Model Releases

LaCy: What Small Language Models Can and Should Learn is Not Just a Question of Loss

model-releasesapple-ml-research

This paper was accepted at the Workshop on Memory for LLM-Based Agentic Systems at ICLR. Language models have consistently grown to compress more world knowledge into their parameters, but the knowled

9 Apr 2026

Safety

Governance-Aware Agent Telemetry for Closed-Loop Enforcement in Multi-Agent AI Systems