Apple is presenting new research at the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), taking place October 24–29 in Budapest, Hungary. EMNLP focuses on research ...

MLX on Mac with Apple silicon lets AI researchers and developers experiment locally with the latest models and methods in a private environment. The open-source array framework leverages the unified ...

Supervised fine-tuning on teacher-generated trajectories is the standard first stage for distilling tool-calling capabilities into deployable models. Post-training pipelines that drive shipped ...

Diffusion (Large) Language Models (dLLMs) now match the downstream performance of their autoregressive counterparts on many tasks, while holding the promise of being more efficient during inference.

Our next generation of Apple Intelligence is centered around our users, integrated deeply into our operating systems, and powered by a bold new architecture with privacy at its core. At the heart of ...

Serving transformer language models with high throughput requires caching Key-Values (KVs) to avoid redundant computation during autoregressive generation. The memory footprint of KV caching is ...

Apple is presenting new research at the annual International Conference on Learning Representations (ICLR), which takes place in person in Rio de Janeiro, Brazil, from April 23 to 27. We are proud to ...

Agentic LLM systems that generate code through multi-turn tool use face a fundamental context problem: each session starts from zero, discarding the configuration choices, domain constraints, data ...

Mac with Apple silicon is increasingly popular among AI developers and researchers interested in using their Mac to experiment with the latest models and techniques. With MLX, users can explore and ...

The Apple AIML Residency is a one-year program for graduates with advanced degrees, designed to spur interdisciplinary collaboration and apply it to ML-based solutions to solve new complex problems.

3D Scene understanding has been an active area of machine learning (ML) research for more than a decade. More recently the release of LiDAR sensor functionality in Apple iPhone and iPad has begun a ...

This paper introduces a framework that integrates reinforcement learning (RL) with autonomous agents to enable continuous improvement in the automated process of software test cases authoring from ...