{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:57ZK2NFOXGSQT4ORPTCBBYOS3P","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":"beeb602b4997a1c71d07a33a9bb39dbea70c7ad63c48dfac81f4b856694c4ba5","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-25T03:01:26Z","title_canon_sha256":"674ee7a620f3ee133385b614712c6c8f3206df6afd0d77f4dad076cadafb64b7"},"schema_version":"1.0","source":{"id":"2501.15045","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15045","created_at":"2026-07-05T10:06:47Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15045v2","created_at":"2026-07-05T10:06:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15045","created_at":"2026-07-05T10:06:47Z"},{"alias_kind":"pith_short_12","alias_value":"57ZK2NFOXGSQ","created_at":"2026-07-05T10:06:47Z"},{"alias_kind":"pith_short_16","alias_value":"57ZK2NFOXGSQT4OR","created_at":"2026-07-05T10:06:47Z"},{"alias_kind":"pith_short_8","alias_value":"57ZK2NFO","created_at":"2026-07-05T10:06:47Z"}],"graph_snapshots":[{"event_id":"sha256:506dda8cf3e30ba86521a62c9f7ab998369bc16db45ab302969c8d01c0659806","target":"graph","created_at":"2026-07-05T10:06:47Z","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/2501.15045/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Robustly predicting attention regions of interest for self-driving systems is crucial for driving safety but presents significant challenges due to the labor-intensive nature of obtaining large-scale attention labels and the domain gap between self-driving scenarios and natural scenes. These challenges are further exacerbated by complex traffic environments, including camera corruption under adverse weather, noise interferences, and central bias from long-tail distributions. To address these issues, we propose a robust unsupervised attention prediction method. An Uncertainty Mining Branch refi","authors_text":"Huadong Ma, Mengshi Qi, Pengfei Zhu, Xiaoyang Bi","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-25T03:01:26Z","title":"Towards Robust Unsupervised Attention Prediction in Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15045","kind":"arxiv","version":2},"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":"sha256:16cd670bf89d61aeb89cae278f2aef62cc902b6cda9b383a4005a5c36034f7f5","target":"record","created_at":"2026-07-05T10:06:47Z","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":"beeb602b4997a1c71d07a33a9bb39dbea70c7ad63c48dfac81f4b856694c4ba5","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-25T03:01:26Z","title_canon_sha256":"674ee7a620f3ee133385b614712c6c8f3206df6afd0d77f4dad076cadafb64b7"},"schema_version":"1.0","source":{"id":"2501.15045","kind":"arxiv","version":2}},"canonical_sha256":"eff2ad34aeb9a509f1d17cc410e1d2dbf6c4a59cd7c3a84758f6e7767caa671d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eff2ad34aeb9a509f1d17cc410e1d2dbf6c4a59cd7c3a84758f6e7767caa671d","first_computed_at":"2026-07-05T10:06:47.677463Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:06:47.677463Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yKtuTUn6QZcT6pR7oqS6Jap5mrct12xKKm67PqrrpsDhYdepMuqynBRNFp9ffbg52prHSHv7K/kO7krp+cINDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:06:47.677999Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.15045","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16cd670bf89d61aeb89cae278f2aef62cc902b6cda9b383a4005a5c36034f7f5","sha256:506dda8cf3e30ba86521a62c9f7ab998369bc16db45ab302969c8d01c0659806"],"state_sha256":"23288e27d691ebc7a861a4a4112322c2839a05be84452adb3d6e485addf321f1"}