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Apple Machine Learning Research

Multilingual Knowledge Transfer under Data Constraints via Lexical Interventions Scaling Laws for Mixture Pretraining Under Data Constraints Examining Human-Like Behaviors in LLMs: A Multi-Dimensional Analysis of Model Behaviors, User Factors, and System Prompts The P-Completeness of Inverted Index Traversal: On the Complexity of Evaluating Boolean Query DAGs GRPO Beyond English: A Large-Scale Study of GRPO in Non-English and Multilingual Settings MVICAD2: Multi-View Independent Component Analysis with Delays and Dilations A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport When Unlearning Is Free: Leveraging Low Influence Points to Reduce Computational Costs Scaling Categorical Flow Maps Beyond Next-Token Prediction: A Performance Characterization of Diffusion versus Autoregressive Language Models Arbitrage: Efficient Reasoning via Advantage-Aware Speculation Locking Pretrained Weights via Deep Low-Rank Residual Distillation DeepAmbigQA: Ambiguous Multi-hop Questions for Benchmarking LLM Answer Completeness Taming Outlier Tokens in Diffusion Transformers Understanding Alignment in Multimodal LLMs: A Comprehensive Study Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph MoMo: Dial Motion Mode in Robot Manipulation with Spatiotemporal Action Tokenization Memory Efficient Audio Synthesis with Decoupled Temporal Depth Diffusion Transformers GH-ESD: Grounded Hypothesis-Driven Error Slice Discovery for Instance-Level Vision Tasks LEAD: Breaking the No-Recovery Bottleneck in Long-Horizon Reasoning Environment-free Synthetic Data Generation for API-Calling Agents Accelerating Text-to-Video Generation with Calibrated Sparse Attention RayRoPE: Projective Ray Positional Encoding for Multi-View Attention LVSum: A Benchmark for Timestamp-Aware Long Video Summarization Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling When Unlearning Is Free: Leveraging Low Influence Points to Reduce Computational Costs Show Me Examples: Inferring Visual Concepts from Image Sets Location-Invariant Properties of Functions Versus Properties of Distributions: United in Testing but Separated in Verification Interactive Proofs for General Distribution Properties Doubly Sub-linear Interactive Proofs of Proximity
What Matters in Practical Learned Image Compression
2026-05-07 · via Apple Machine Learning Research
One of the major differentiators unlocked by learned codecs relative to their hard-coded traditional counterp…