Paper

Structure-Induced Information for Rerooting Levin Tree Search

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arXiv:2605. 30664v1 Announce Type: new Abstract: Subgoal-based policy tree search, which uses a policy to guide search, is effective for complex single-agent deterministic problems but often relies on explicit subgoal generation that can incur substantial overhead and hinders scalability.

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Authors: Jake Tuero, Michael Buro, Laurent Orseau, Levi H. S. Lelis
Released: 2026-06-01 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Structure-Induced Information for Rerooting Levin Tree Search overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, soft, line, rate, test. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2605.30664

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