{"id":"5bbcf7e2-e56f-49f2-b804-1822dddb3ae6","arxiv_id":"2505.14001","paper_version":1,"verdict":"REJECT","confidence":"HIGH","novelty_score":7.0,"correctness_risk":"high","formal_verification":"none","parameter_count":0,"one_line_summary":"VeRecycle shows the maximum reusable safety probability after a localized change is min(original threshold, 1 minus 1 divided by the certificate's infimum on the changed region).","lead":"VeRecycle reuses a probabilistic neural safety certificate after a change in a known part of the state space, by lowering the certified success probability instead of retraining the controller. This matters because full re-certification of neural controllers is expensive, and the paper gives a formula and algorithm for deciding when older guarantees can still be trusted.","discovery_kind":"new_method","skeptic_critique":null,"referee_report":null,"author_rebuttal":null,"desk_editor":null,"rs_alignment":null,"lean_confirmation":null,"pith_extraction":null,"created_at":"2026-08-07T15:44:16.746996+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":null,"supporting_citations":[],"review_version":1}