{"id":"fc2f7ae3-5035-492f-b1b7-15f79b0aca3d","arxiv_id":"2504.11990","paper_version":1,"verdict":"CONDITIONAL","confidence":"MODERATE","novelty_score":6.0,"correctness_risk":"medium","formal_verification":"none","parameter_count":9,"one_line_summary":"T-Core, a bootstrapping defense that sifts clean data and filters trusted encoder channels, reduces backdoor attack success rates below 10% across encoder and dataset poisoning threats in transfer learning.","lead":"The paper proposes T-Core, a defense that identifies trusted clean samples and encoder neurons before training, to block backdoor attacks in transfer learning. It targets resource-limited users who fine-tune pre-trained encoders, a setting where prior defenses often fail.","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":"2026-08-16T12:40:45.008418+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":null,"supporting_citations":[],"review_version":1}