Alexander Toshev
Apple machine learning researcher; co-author of DataComp-LM, MobileCLIP2, and recent agent-training work
Alexander Toshev is a machine learning researcher at Apple, listed with Apple on papers through September 2026. Toshev's recent Apple work covers training agents, including RLTL;DR, a 2026 method in which an agent writes short feedback insights after failed attempts and conditions later attempts on them. Toshev is also a co-author of DataComp-LM, a testbed for controlled dataset experiments built around a standardized Common Crawl corpus, and of MobileCLIP2, which improves the training of low-latency image-text models.1234
Work
DataComp-LM: In search of the next generation of training sets for language models (external site: arxiv.org)Published research
Co-author, listed with Apple, of the 2024 DataComp-LM paper, which provides a standardized corpus, pretraining recipes, and downstream evaluations for dataset experiments at model scales from 412M to 7B parameters.3
RLTL;DR: Self-improvement by Internalizing Self-generated Feedback (external site: arxiv.org)Published research
Co-author of the 2026 Apple paper introducing RLTL;DR for self-improvement in reinforcement learning with verifiable rewards.1
MobileCLIP2: Improving Multi-Modal Reinforced Training (external site: arxiv.org)Published research
Co-author, listed with Apple, of the 2025 MobileCLIP2 paper on improved multi-modal reinforced training for low-latency image-text models.4
This profile covers public professional work only, from the sources below. It is not an endorsement or a ranking. To correct or remove it, use the correction form.