Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA

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

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ethics.ai (9 August 2026), “Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA,” evidence record 17972, https://ethics.ai/record/17972 (originally published by HuggingFace Daily Papers).

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