{
  "id": 17972,
  "url": "https://arxiv.org/abs/2608.09819",
  "title": "Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA",
  "summary": "Macaron-V1 is an open agent-model family for experiential intelligence: learning from experience in real environments and continuing to learn after deployment. It is organized around two system goals. Adaptation is pursued through recursive improvement of versioned model-harness pairs, where experience from one configuration is evaluated under an external contract and used to construct its successor. Collaboration is pursued via the Mixture-of-LoRA (MoL) architecture that freezes a base model, c",
  "authors": "Mind Lab, Vin Bo, Asher Cai, Jingwei Cao, Song Cao, Vic Cao",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-09T20:00:00.000Z",
  "fetched_at": "2026-08-11T05:10:37.351Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/17972",
  "original_url": "https://arxiv.org/abs/2608.09819",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}