{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:QQP37CH5UIK3RJALQRQGO3U4KO","short_pith_number":"pith:QQP37CH5","canonical_record":{"source":{"id":"2605.16363","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-09T16:26:16Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"76d2b916b863b7e91b6b6ab997fda4cff6fedd9893452ca9c22e943af70ddcad","abstract_canon_sha256":"da3d514872299d74e1eae073e3fbd85df31a74d9f730b25b778d334618c2e0f2"},"schema_version":"1.0"},"canonical_sha256":"841fbf88fda215b8a40b8460676e9c53a7f1f7f2085c3a9d373c3699532338c0","source":{"kind":"arxiv","id":"2605.16363","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16363","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16363v1","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16363","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"pith_short_12","alias_value":"QQP37CH5UIK3","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"pith_short_16","alias_value":"QQP37CH5UIK3RJAL","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"pith_short_8","alias_value":"QQP37CH5","created_at":"2026-05-20T00:02:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:QQP37CH5UIK3RJALQRQGO3U4KO","target":"record","payload":{"canonical_record":{"source":{"id":"2605.16363","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-09T16:26:16Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"76d2b916b863b7e91b6b6ab997fda4cff6fedd9893452ca9c22e943af70ddcad","abstract_canon_sha256":"da3d514872299d74e1eae073e3fbd85df31a74d9f730b25b778d334618c2e0f2"},"schema_version":"1.0"},"canonical_sha256":"841fbf88fda215b8a40b8460676e9c53a7f1f7f2085c3a9d373c3699532338c0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:02:18.472659Z","signature_b64":"wxSdWmONHqaLC1ObY1W/HkGEGO1Cukf/z9/RuHnbDiN/p6wMARLoWH5if1ObCcd4kDjTmTwqWPmzQSS2DtqEDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"841fbf88fda215b8a40b8460676e9c53a7f1f7f2085c3a9d373c3699532338c0","last_reissued_at":"2026-05-20T00:02:18.472034Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:02:18.472034Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.16363","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":"2026-05-20T00:02:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I+Xe8IhGfhqqJ1kkkVxu6pQMV+ghOiof/KASstMMmaS5wZO0+930bkNFHmeFiz1Rtm/wP2JU77tU8V6DnLiPCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T00:07:21.396753Z"},"content_sha256":"b81eeaa4d0a7e2b94158697dd190f39e076460251e05e2ddd11b48c16b14e276","schema_version":"1.0","event_id":"sha256:b81eeaa4d0a7e2b94158697dd190f39e076460251e05e2ddd11b48c16b14e276"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:QQP37CH5UIK3RJALQRQGO3U4KO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.LG","authors_text":"Fei Shen, Gang Xu, Huiping Zhuang, Ming Li, Songbai Tan, Wenbo Gao, Xiaofeng Zhu, Yunyun Yang, Zhongan Wang","submitted_at":"2026-05-09T16:26:16Z","abstract_excerpt":"Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective intervention thus requires anticipating scams before the intent becomes explicit. This is inherently challenging, as decisions must rely on partial trajectories with temporally distributed evidence. In this paper, we propose \\textbf{ORACLE} Online Reasoning for Anticipating Cross-temporal Latent thrEats, the first agentic framework for early scam anticipation from \\textit{streaming app-usage} trajectories. To support this setting, we curate a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16363","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/2605.16363/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T20:38:45.707171Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"4e1e56f849152674e5fda7ac40ae5ab1682347f87bb3024cb72de9b6804c75ee"},"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":"2026-05-20T00:02:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PGqufzVMMoD9G+1bkZQqX7YK3zelGK4mPTMIzpB1n2n8i5BXCFZPAAGwU9Np06i4bwGdojwcD30Veq7b9gNFDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T00:07:21.397156Z"},"content_sha256":"69a200eb7727f547a6aa5020254b1609c37416394b106ccb250c52bd758a9a8b","schema_version":"1.0","event_id":"sha256:69a200eb7727f547a6aa5020254b1609c37416394b106ccb250c52bd758a9a8b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QQP37CH5UIK3RJALQRQGO3U4KO/bundle.json","state_url":"https://pith.science/pith/QQP37CH5UIK3RJALQRQGO3U4KO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QQP37CH5UIK3RJALQRQGO3U4KO/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":"2026-05-22T00:07:21Z","links":{"resolver":"https://pith.science/pith/QQP37CH5UIK3RJALQRQGO3U4KO","bundle":"https://pith.science/pith/QQP37CH5UIK3RJALQRQGO3U4KO/bundle.json","state":"https://pith.science/pith/QQP37CH5UIK3RJALQRQGO3U4KO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QQP37CH5UIK3RJALQRQGO3U4KO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QQP37CH5UIK3RJALQRQGO3U4KO","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":"da3d514872299d74e1eae073e3fbd85df31a74d9f730b25b778d334618c2e0f2","cross_cats_sorted":["cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-09T16:26:16Z","title_canon_sha256":"76d2b916b863b7e91b6b6ab997fda4cff6fedd9893452ca9c22e943af70ddcad"},"schema_version":"1.0","source":{"id":"2605.16363","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16363","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16363v1","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16363","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"pith_short_12","alias_value":"QQP37CH5UIK3","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"pith_short_16","alias_value":"QQP37CH5UIK3RJAL","created_at":"2026-05-20T00:02:18Z"},{"alias_kind":"pith_short_8","alias_value":"QQP37CH5","created_at":"2026-05-20T00:02:18Z"}],"graph_snapshots":[{"event_id":"sha256:69a200eb7727f547a6aa5020254b1609c37416394b106ccb250c52bd758a9a8b","target":"graph","created_at":"2026-05-20T00:02:18Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T20:38:45.707171Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.16363/integrity.json","findings":[],"snapshot_sha256":"4e1e56f849152674e5fda7ac40ae5ab1682347f87bb3024cb72de9b6804c75ee","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective intervention thus requires anticipating scams before the intent becomes explicit. This is inherently challenging, as decisions must rely on partial trajectories with temporally distributed evidence. In this paper, we propose \\textbf{ORACLE} Online Reasoning for Anticipating Cross-temporal Latent thrEats, the first agentic framework for early scam anticipation from \\textit{streaming app-usage} trajectories. To support this setting, we curate a ","authors_text":"Fei Shen, Gang Xu, Huiping Zhuang, Ming Li, Songbai Tan, Wenbo Gao, Xiaofeng Zhu, Yunyun Yang, Zhongan Wang","cross_cats":["cs.CY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-09T16:26:16Z","title":"ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16363","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:b81eeaa4d0a7e2b94158697dd190f39e076460251e05e2ddd11b48c16b14e276","target":"record","created_at":"2026-05-20T00:02:18Z","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":"da3d514872299d74e1eae073e3fbd85df31a74d9f730b25b778d334618c2e0f2","cross_cats_sorted":["cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-09T16:26:16Z","title_canon_sha256":"76d2b916b863b7e91b6b6ab997fda4cff6fedd9893452ca9c22e943af70ddcad"},"schema_version":"1.0","source":{"id":"2605.16363","kind":"arxiv","version":1}},"canonical_sha256":"841fbf88fda215b8a40b8460676e9c53a7f1f7f2085c3a9d373c3699532338c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"841fbf88fda215b8a40b8460676e9c53a7f1f7f2085c3a9d373c3699532338c0","first_computed_at":"2026-05-20T00:02:18.472034Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:18.472034Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wxSdWmONHqaLC1ObY1W/HkGEGO1Cukf/z9/RuHnbDiN/p6wMARLoWH5if1ObCcd4kDjTmTwqWPmzQSS2DtqEDA==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:18.472659Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.16363","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b81eeaa4d0a7e2b94158697dd190f39e076460251e05e2ddd11b48c16b14e276","sha256:69a200eb7727f547a6aa5020254b1609c37416394b106ccb250c52bd758a9a8b"],"state_sha256":"649380fff3bab8397d747851643cfe0a7ca164c8d51752cb429e31f31ae0c888"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bwVf4Ucvj5gT4mDf3zOHiKUG052oAK8PyNMEZ+F4+ZkJTNhJG7USw6tKqfe59Zp8q85Ibw/b2ChDafgB/gcFBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T00:07:21.399613Z","bundle_sha256":"e64218f48409c48d9e518fd2f1549e7be938b79540d084b9d144d020fa66f79a"}}