{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:KK5MPKCGFJKN33XTVIBQGALPYN","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"414f356bf6e3a31a890c5baa985e7a86885d9c3d3296e8f874ffbdd25c6035a8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-17T09:44:28Z","title_canon_sha256":"3b70794512790e1af4064c1c3289152d3f66cee462e118f0e6544c1292c9c4ee"},"schema_version":"1.0","source":{"id":"2606.18864","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.18864","created_at":"2026-06-19T16:11:49Z"},{"alias_kind":"arxiv_version","alias_value":"2606.18864v1","created_at":"2026-06-19T16:11:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.18864","created_at":"2026-06-19T16:11:49Z"},{"alias_kind":"pith_short_12","alias_value":"KK5MPKCGFJKN","created_at":"2026-06-19T16:11:49Z"},{"alias_kind":"pith_short_16","alias_value":"KK5MPKCGFJKN33XT","created_at":"2026-06-19T16:11:49Z"},{"alias_kind":"pith_short_8","alias_value":"KK5MPKCG","created_at":"2026-06-19T16:11:49Z"}],"graph_snapshots":[{"event_id":"sha256:c95e5bfcd606146b30231435e888fab170d05c67b0279aec5ce577424bcc102e","target":"graph","created_at":"2026-06-19T16:11:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.18864/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper studies how to scale learning-based automatic emergency braking (AEB) with massive unlabeled fleet data under production constraints. Our approach is based on meta-feedback semi-supervised learning (MF-SSL), where a teacher generates pseudo labels for unlabeled driving data and is updated using a small labeled anchor set as safety-critical feedback. In production, anchor ambiguity and labeled-unlabeled mismatch can amplify systematic pseudo-label errors, leading to spurious triggers. We propose a stabilized MF-SSL framework with (i) Noise-Aware Decoupling, which removes ambiguity-pr","authors_text":"Chuanchuan Zhong, Junjie Zhang, Mengxiang Hao, Xiangyu Wang, Xin Jiang, Yang Zhan, Yansong Jia, Ying Wang, Yu Han, Yulun Song, Zhen Cao, Zhitao Xu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-17T09:44:28Z","title":"Scaling Learning-based AEB with Massive Unlabeled Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.18864","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:3cc6ae143820b2e86905693790b87124aa502723c278ec3329b7a8223858a5c2","target":"record","created_at":"2026-06-19T16:11:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"414f356bf6e3a31a890c5baa985e7a86885d9c3d3296e8f874ffbdd25c6035a8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-17T09:44:28Z","title_canon_sha256":"3b70794512790e1af4064c1c3289152d3f66cee462e118f0e6544c1292c9c4ee"},"schema_version":"1.0","source":{"id":"2606.18864","kind":"arxiv","version":1}},"canonical_sha256":"52bac7a8462a54ddeef3aa0303016fc340ee993b37521ff0f4c6c40b6a8276c7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"52bac7a8462a54ddeef3aa0303016fc340ee993b37521ff0f4c6c40b6a8276c7","first_computed_at":"2026-06-19T16:11:49.956049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:11:49.956049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2KUGn0OwUHu6R6+rL+QvsEdv7E7PX/9Xz7VfqoESDBuHT9Ls+bj8QRV+BAZXP3KN676G5S+C1VrvXKFWmQtXBA==","signature_status":"signed_v1","signed_at":"2026-06-19T16:11:49.956424Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.18864","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3cc6ae143820b2e86905693790b87124aa502723c278ec3329b7a8223858a5c2","sha256:c95e5bfcd606146b30231435e888fab170d05c67b0279aec5ce577424bcc102e"],"state_sha256":"78bd2d76dfb44fab33b65856f039630fe0abf2955bbcc70a16dc1b7eae0a1c97"}