AI at Meta· X：AI at Meta (@AIatMeta)·· 3 小时前AI 评分31
Meta 对比 Muse 模型分布外任务表现
AI 导读
Meta 对比了 Muse 系列模型在分布外任务上的表现：两个模型在分布外任务上的提升幅度相近，但在相同分布内得分下，Muse Wonder Full 在陌生任务上的表现优于 Muse Spark 1.3 的趋势预测。Meta 将这一上移归因于更强的基座模型，能把后训练收益更有效地迁移到未预期的任务上。
正文
To quantify how the models handle unfamiliar tasks, we compared test-time compute scaling on tasks trained on during post-training against other tasks.
Both models improve similarly out-of-distribution, but given the same in-distribution score, Muse Wonder Full performs better on unfamiliar tasks than the Muse Spark 1.3 trend predicts. We attribute this upward shift to a stronger base model, which carries post-training gains over more effectively to tasks we didn't anticipate.
来源：AI at Meta · x.com