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Apple Machine Learning Research AI news
The latest from Apple Machine Learning Research, listed as it is published. Headlines link to the original on machinelearning.apple.com.
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Evaluating the Evaluators: Investigating LLM Judges for Personalized Writing Style Assessment
This paper was accepted at the Can We Trust AI Evaluation? Workshop at NeurIPS 2026. We evaluate how good large language model (LLM) judges are for personalized writing tasks. This is important when a user’s preferred writing style is…
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On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models
State Space Models (SSMs) have emerged as a compelling alternative to Transformers, enabling sequence modeling with constant memory and linear compute. Although SSMs exhibit reasonable performance and favorable computational…
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Weighted State Souping for Efficient Long-Context Retrieval
This paper was accepted at the Workshop on Personalized, Aligned, Long-term Memory for AI Systems (PALM) at NeurIPS 2026. State space models (SSMs) combine fast inference and fixed state size with competitive language-modeling performance…
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Faster Retrieval for Better, More Efficient RAG
Maximum inner product search (MIPS) sits at the core of recommendation systems, search, and retrieval-augmented generation (RAG). Given a query vector, MIPS systems search within a database of millions of candidate key vectors for the one…
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Attention to Mamba: A Recipe for Cross-Architecture Distillation
State Space Models (SSMs) such as Mamba have become a popular alternative to Transformer models, due to their reduced memory consumption and higher throughput at generation compared to their Attention-based counterparts. On the other hand…
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GHARP: Real-Time Gaussian Head Animation from Large-Scale Reconstruction Prior
We present GHARP (Real-time Gaussian Head Animation from Large-scale Reconstruction Prior), a method that animates 3D human heads in real time from a few input images of a subject and a driving expression signal. We decouple the problem…