arXiv Computation and Language October 16, 2026 By Tianxiang Fei, Jiazheng Kang, Mao Zheng, Xingyan He, Xiang Yu

Hy-Memory-30B-A3B: Attributed Reinforcement Learning for Long-Term Memory Writing

Read the original on arXiv Computation and Language →

Hy‑Memory‑30B‑A3B is a compact long‑term‑memory writer that learns to write to external memory across multiple frameworks (Mem0, MemOS, and Hy‑Memory). It uses Memory On‑Policy Distillation to teach framework‑specific write protocols and Memory RL to optimize answerability with dense per‑chunk probes, attributed cross‑chunk rewards, and chunk‑level GRPO. On a 20% benchmark subsample, it outperforms other models, achieving a 55.49% macro average versus 54.62% for Claude Opus 5.

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