Foundation models in changing environments can encounter unfamiliar domain knowledge that their original training did not cover. However, new domains rarely provide large amounts of expert-created tra
Recursa is a self-improving foundation model system that adapts to new domains by recursively learning from its own experience, storing skills and reflections in a knowledge repository, and validating improvements without human supervision or stronger teachers.
Foundation models in changing environments can encounter unfamiliar domain knowledge that their original training did not cover. However, new domains rarely provide large amounts of expert-created training data or reliable supervisory signals for further training. We introduce Recursa, a foundation model system that adapts to new domains by learning from its own experience without human experts or a stronger teacher model. Recursa uses a knowledge repository to store what it learns: domain-specific skills and instructions on when to apply them, along with memories of past task experiences and reflections on what to improve. Recursa bootstraps the repository from domain materials and then…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Recursa: Toward Recursively Self-Improving Foundation Model Systems was first seen on Hugging Face · Daily papers on Nov 4, 2026. Since then it has appeared in 11 checks on 2 different days. Its best position was #16 of 30, reached on Nov 4, 05:28 UTC. It dropped off the list after Nov 5, 01:28 UTC.
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#16 on Hugging Face · Daily papers, on Nov 4, 05:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 4, 2026 and has been on the list on 2 days (11 checks) since.