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X-Tree trains agents on reusable hierarchies mined from action traces

huggingface.co by Sitao Cheng et al. Editor score 8/10

X-Tree merges reusable action spans into a skill hierarchy and applies it to offline RL, online RLVR, and self-distillation; the excerpt reports gains across three benchmarks. The method aims to make agents generalize from trajectories rather than rely on retrieved, in-context skills.

What

X-Tree mines reusable hierarchies from action data and uses them to train multi-step agents, without LLM calls to write skills.

Method

It scores action spans for reusability, merges canonicalized actions into a tree, and integrates that structure into offline RL, online RLVR, and on-policy self-distillation.

Why it matters

Training on reusable sub-procedures can make better use of scarce trajectories and improve agent generalization across tasks.

Read on huggingface.co → Code · 2 stars

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