Please confirm you are human
This browser or connection looks automated. Press and continuously hold the control for 3 seconds to enable Google-hosted web results and, when separately allowed, AI-assisted answers.
A successful check enables 100 search requests. Interactive access does not authorize scraping, systematic collection, or reuse of search output.
News
Scaling Laws for Mixture Pretraining Under Data Constraints - Apple Machine Learning Research
4+ hour, 15+ min ago (42+ words) Scaling Laws for Optimal Data Mixtures Scaling Laws for Forgetting During Finetuning with Pretraining Data Injection June 20, 2025research area Methods and Algorithmsconference ICML Our research in machine learning breaks new ground every day. Scaling Laws for Mixture Pretraining Under Data Constraints...
Scaling Categorical Flow Maps
1+ week, 6+ day ago (315+ words) Apple Machine Learning Research Scaling Categorical Flow Maps Continuous diffusion and flow matching models could represent a powerful alternative to autoregressive approaches for language modelling (LM), as they unlock a host of advantages currently reserved for continuous modalities, including accelerated sampling…...
When Unlearning Is Free: Leveraging Low Influence Points to Reduce Computational Costs
1+ mon, 3+ day ago (253+ words) Apple Machine Learning Research When Unlearning Is Free: Leveraging Low Influence Points to Reduce Computational Costs As concerns around data privacy in machine learning grow, the ability to unlearn—or remove—specific data points from trained models becomes increasingly important....
Learning Structured Reasoning via Tractable Trajectory Control
1+ mon, 2+ week ago (309+ words) Apple Machine Learning Research Learning Structured Reasoning via Tractable Trajectory Control Large language models can exhibit emergent reasoning behaviors, often manifested as recurring lexical patterns (e.g., “wait,” indicating verification). However, complex reasoning trajectories remain sparse in unconstrained sampling, and standard RL…...
LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning
3+ mon, 3+ week ago (134+ words) AuthorsHaoqiang Kang†, Yizhe Zhang, Nikki Lijing Kuang†, Nicklas Majamaki†, Navdeep Jaitly, Yi-An Ma†, Lianhui Qin† Thinking into the Future: Latent Lookahead Training for Transformers March 25, 2026research area Methods and AlgorithmsWorkshop at ICLR This paper was accepted at the Workshop on Latent…...
ParaRNN: Large-Scale Nonlinear RNNs, Trainable in Parallel
3+ mon, 3+ week ago (757+ words) To accelerate research in efficient sequence modeling and enable researchers and practitioners to explore new nonlinear RNN models at scale, the ParaRNN codebase has been released as an open-source framework for automatic training-parallelization of nonlinear RNNs. The computational cost of…...
A Theoretical Framework for Acoustic Neighbor Embeddings
4+ mon, 1+ week ago (250+ words) Apple Machine Learning Research 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 embedding space. A…...
Google News
4+ mon, 2+ week ago (12+ words) Personalized Group Relative Policy Optimization for Heterogenous Preference Alignment Apple Machine Learning Research...
Entropy-Preserving Reinforcement Learning
4+ mon, 3+ week ago (284+ words) machinelearning.apple.com Policy gradient algorithms have driven many recent advancements in language model reasoning. An appealing property is their ability to learn from exploration on their own trajectories, a process crucial for fostering diverse and creative solutions. As we…...