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

Published
Source
arXiv
Paper number
861
Field
Machine Learning
arXiv ID
2608.09819

Key points

  • The system uses a Mixture-of-LoRA structure that keeps the base model frozen and selects expert adapters for chat, agent, coding, or GenUI on each turn.
  • It proposes a framework for continual learning after deployment through joint model and harness design plus a recursive self-improvement loop.
  • It releases Venti, a 744B model based on GLM-5.2, and Tall, a 50B model based on Qwen3.6.
  • It also develops UI4A, a component-native GenUI harness, and MindForge, an agent RL framework.
  • It shows competitive performance with frontier models on Personal Intelligence, GenUI, and general capability benchmarks.

Paper links

External research summaries. These are not HDATF publications or measured product results.

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