{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VCCRAIBGLWZWT4FAS7FWAZBTWD","short_pith_number":"pith:VCCRAIBG","canonical_record":{"source":{"id":"2501.01733","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T09:51:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f1c1ef62f3a29f9c5feb64ce1cbb5a84c81af995ff50c086c5ecdb67940432e8","abstract_canon_sha256":"ca8c876b0760293086f86537568bab41b29497d31df7d6dfdbc0ce46a616390a"},"schema_version":"1.0"},"canonical_sha256":"a8851020265db369f0a097cb606433b0d8921d6a9dd8bc8d045cfcef9ad45322","source":{"kind":"arxiv","id":"2501.01733","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.01733","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"arxiv_version","alias_value":"2501.01733v1","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01733","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"pith_short_12","alias_value":"VCCRAIBGLWZW","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"pith_short_16","alias_value":"VCCRAIBGLWZWT4FA","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"pith_short_8","alias_value":"VCCRAIBG","created_at":"2026-07-05T09:56:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VCCRAIBGLWZWT4FAS7FWAZBTWD","target":"record","payload":{"canonical_record":{"source":{"id":"2501.01733","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T09:51:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f1c1ef62f3a29f9c5feb64ce1cbb5a84c81af995ff50c086c5ecdb67940432e8","abstract_canon_sha256":"ca8c876b0760293086f86537568bab41b29497d31df7d6dfdbc0ce46a616390a"},"schema_version":"1.0"},"canonical_sha256":"a8851020265db369f0a097cb606433b0d8921d6a9dd8bc8d045cfcef9ad45322","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:56:40.098275Z","signature_b64":"8nohjpkTP6fWNe8xbbaWLlc3Zb8Tq5g4bP3DFCCFGh3h5ILOfoky4DuQc3u+to9x6TN/leT3nL+M5FHmPQ3TDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a8851020265db369f0a097cb606433b0d8921d6a9dd8bc8d045cfcef9ad45322","last_reissued_at":"2026-07-05T09:56:40.097764Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:56:40.097764Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.01733","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:56:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Iu8ACJlpebSbHB5MUwgcouxpSmjLGMqsP6eZApec2xnagh3W0Y8lG9hmCcwFTFSiXhr60700Kkc0dxwpvqhHDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T05:14:21.308440Z"},"content_sha256":"0d7ef7c513ed17ddef9cfba8e41235bb30b5ce34596020d43254cf3bc4a83e1a","schema_version":"1.0","event_id":"sha256:0d7ef7c513ed17ddef9cfba8e41235bb30b5ce34596020d43254cf3bc4a83e1a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VCCRAIBGLWZWT4FAS7FWAZBTWD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Hanzi Wang, Jing-Hao Xue, Ruikang Chen, Yang Lu, Yan Yan","submitted_at":"2025-01-03T09:51:51Z","abstract_excerpt":"Automatic X-ray prohibited item detection is vital for public safety. Existing deep learning-based methods all assume that the annotations of training X-ray images are correct. However, obtaining correct annotations is extremely hard if not impossible for large-scale X-ray images, where item overlapping is ubiquitous.As a result, X-ray images are easily contaminated with noisy annotations, leading to performance deterioration of existing methods.In this paper, we address the challenging problem of training a robust prohibited item detector under noisy annotations (including both category noise"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01733","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2501.01733/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:56:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fTWIGoECEd9er71Sr2lUnUA/iblB3HnaaPBOrz14iOek9tSgGthuS8B3IWfPjBHe7+O2yUGccaI8bnXX6y/ICg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T05:14:21.308962Z"},"content_sha256":"748d9b5c78829b1e791d1dd3b27cf02a00d585d1205c6021dc1f445acdb6f6fe","schema_version":"1.0","event_id":"sha256:748d9b5c78829b1e791d1dd3b27cf02a00d585d1205c6021dc1f445acdb6f6fe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VCCRAIBGLWZWT4FAS7FWAZBTWD/bundle.json","state_url":"https://pith.science/pith/VCCRAIBGLWZWT4FAS7FWAZBTWD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VCCRAIBGLWZWT4FAS7FWAZBTWD/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-13T05:14:21Z","links":{"resolver":"https://pith.science/pith/VCCRAIBGLWZWT4FAS7FWAZBTWD","bundle":"https://pith.science/pith/VCCRAIBGLWZWT4FAS7FWAZBTWD/bundle.json","state":"https://pith.science/pith/VCCRAIBGLWZWT4FAS7FWAZBTWD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VCCRAIBGLWZWT4FAS7FWAZBTWD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VCCRAIBGLWZWT4FAS7FWAZBTWD","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":"ca8c876b0760293086f86537568bab41b29497d31df7d6dfdbc0ce46a616390a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T09:51:51Z","title_canon_sha256":"f1c1ef62f3a29f9c5feb64ce1cbb5a84c81af995ff50c086c5ecdb67940432e8"},"schema_version":"1.0","source":{"id":"2501.01733","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.01733","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"arxiv_version","alias_value":"2501.01733v1","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01733","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"pith_short_12","alias_value":"VCCRAIBGLWZW","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"pith_short_16","alias_value":"VCCRAIBGLWZWT4FA","created_at":"2026-07-05T09:56:40Z"},{"alias_kind":"pith_short_8","alias_value":"VCCRAIBG","created_at":"2026-07-05T09:56:40Z"}],"graph_snapshots":[{"event_id":"sha256:748d9b5c78829b1e791d1dd3b27cf02a00d585d1205c6021dc1f445acdb6f6fe","target":"graph","created_at":"2026-07-05T09:56:40Z","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/2501.01733/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic X-ray prohibited item detection is vital for public safety. Existing deep learning-based methods all assume that the annotations of training X-ray images are correct. However, obtaining correct annotations is extremely hard if not impossible for large-scale X-ray images, where item overlapping is ubiquitous.As a result, X-ray images are easily contaminated with noisy annotations, leading to performance deterioration of existing methods.In this paper, we address the challenging problem of training a robust prohibited item detector under noisy annotations (including both category noise","authors_text":"Hanzi Wang, Jing-Hao Xue, Ruikang Chen, Yang Lu, Yan Yan","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T09:51:51Z","title":"Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01733","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":"sha256:0d7ef7c513ed17ddef9cfba8e41235bb30b5ce34596020d43254cf3bc4a83e1a","target":"record","created_at":"2026-07-05T09:56:40Z","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":"ca8c876b0760293086f86537568bab41b29497d31df7d6dfdbc0ce46a616390a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-03T09:51:51Z","title_canon_sha256":"f1c1ef62f3a29f9c5feb64ce1cbb5a84c81af995ff50c086c5ecdb67940432e8"},"schema_version":"1.0","source":{"id":"2501.01733","kind":"arxiv","version":1}},"canonical_sha256":"a8851020265db369f0a097cb606433b0d8921d6a9dd8bc8d045cfcef9ad45322","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a8851020265db369f0a097cb606433b0d8921d6a9dd8bc8d045cfcef9ad45322","first_computed_at":"2026-07-05T09:56:40.097764Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:56:40.097764Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8nohjpkTP6fWNe8xbbaWLlc3Zb8Tq5g4bP3DFCCFGh3h5ILOfoky4DuQc3u+to9x6TN/leT3nL+M5FHmPQ3TDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:56:40.098275Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.01733","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0d7ef7c513ed17ddef9cfba8e41235bb30b5ce34596020d43254cf3bc4a83e1a","sha256:748d9b5c78829b1e791d1dd3b27cf02a00d585d1205c6021dc1f445acdb6f6fe"],"state_sha256":"9c09310f6f030d8dc8c28554fcaa2cff2eb52a96840f5a91de3606c5938035b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H2j4zQit56YCzNA/jupQDNSyV1Aoy2p3C+CpClhS65H77D2JOEgZeV8HYi8l6orwuvDVGuw3Tz29v9gpbvAxBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T05:14:21.314930Z","bundle_sha256":"424a822f67a19788912e802dfed8201df811d2e9a4d8f7e02499fbf5714eb9e1"}}