{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WIMLQNM5EMJZOAVRCZAZWQHC26","short_pith_number":"pith:WIMLQNM5","canonical_record":{"source":{"id":"2601.13632","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-20T06:06:35Z","cross_cats_sorted":[],"title_canon_sha256":"ce87a2d24bcf3c5594862f5385f92525f065ad84537f2d605fad50c8fa6d1e96","abstract_canon_sha256":"566ae0235f82b226b144ccc159f8aa9bec8367c822c9c8749cc819c10864fc61"},"schema_version":"1.0"},"canonical_sha256":"b218b8359d23139702b116419b40e2d794278deae347972f63d85907b1290f66","source":{"kind":"arxiv","id":"2601.13632","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.13632","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"arxiv_version","alias_value":"2601.13632v2","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.13632","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"pith_short_12","alias_value":"WIMLQNM5EMJZ","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"pith_short_16","alias_value":"WIMLQNM5EMJZOAVR","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"pith_short_8","alias_value":"WIMLQNM5","created_at":"2026-06-26T01:15:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WIMLQNM5EMJZOAVRCZAZWQHC26","target":"record","payload":{"canonical_record":{"source":{"id":"2601.13632","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-20T06:06:35Z","cross_cats_sorted":[],"title_canon_sha256":"ce87a2d24bcf3c5594862f5385f92525f065ad84537f2d605fad50c8fa6d1e96","abstract_canon_sha256":"566ae0235f82b226b144ccc159f8aa9bec8367c822c9c8749cc819c10864fc61"},"schema_version":"1.0"},"canonical_sha256":"b218b8359d23139702b116419b40e2d794278deae347972f63d85907b1290f66","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-26T01:15:17.046676Z","signature_b64":"2FxUXRqaJJyJed7GjFqND282EXo7klUIZB917l/j9V/eVyrbzmA/EP/rJR/wOFxIa0M0xpds1VmtmYzLZybwBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b218b8359d23139702b116419b40e2d794278deae347972f63d85907b1290f66","last_reissued_at":"2026-06-26T01:15:17.046183Z","signature_status":"signed_v1","first_computed_at":"2026-06-26T01:15:17.046183Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2601.13632","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-26T01:15:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pOlCDGrxpg2neIbcWdlpmGsCwHovfceaOhYKnvADeNyVz7OpMX8BoQQP2UwcgTNOM017xWUryVXzqvWR7vlfCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T14:42:38.889892Z"},"content_sha256":"adecb1db22084a7777aa765a8674ea5fb4695698a229a054bb68ddf6b5e79f0f","schema_version":"1.0","event_id":"sha256:adecb1db22084a7777aa765a8674ea5fb4695698a229a054bb68ddf6b5e79f0f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WIMLQNM5EMJZOAVRCZAZWQHC26","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Resilient Routing: Risk-Aware Dynamic Routing in Smart Logistics via Spatiotemporal Graph Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Sichen Zhao, Xianling Zeng, Yalun Qi, Zhiming Xue, Zihan Yu","submitted_at":"2026-01-20T06:06:35Z","abstract_excerpt":"With the rapid development of the e-commerce industry, the logistics network is experiencing unprecedented pressure. The traditional static routing strategy most time cannot tolerate the traffic congestion and fluctuating retail demand. In this paper, we propose a Risk-Aware Dynamic Routing(RADR) framework which integrates Spatiotemporal Graph Neural Networks (ST-GNN) with combinatorial optimization. We first construct a logistics topology graph by using the discrete GPS data using spatial clustering methods. Subsequently, a hybrid deep learning model combining Graph Convolutional Network (GCN"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.13632","kind":"arxiv","version":2},"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/2601.13632/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":"2026-06-26T01:15:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UUN7qBlahzW66lJrIRJ0QecEdwUZN8Gt0ivrYNMiOpJgSkJ9hryMNNjqR9godDsYLT3FHed1TkpPzyLvIgFbCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T14:42:38.890264Z"},"content_sha256":"127ef8677b773b7a01a3ea8472109f29f775c1d3dc9fd8bec1afeb9f16b61eeb","schema_version":"1.0","event_id":"sha256:127ef8677b773b7a01a3ea8472109f29f775c1d3dc9fd8bec1afeb9f16b61eeb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WIMLQNM5EMJZOAVRCZAZWQHC26/bundle.json","state_url":"https://pith.science/pith/WIMLQNM5EMJZOAVRCZAZWQHC26/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WIMLQNM5EMJZOAVRCZAZWQHC26/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":"2026-07-02T14:42:38Z","links":{"resolver":"https://pith.science/pith/WIMLQNM5EMJZOAVRCZAZWQHC26","bundle":"https://pith.science/pith/WIMLQNM5EMJZOAVRCZAZWQHC26/bundle.json","state":"https://pith.science/pith/WIMLQNM5EMJZOAVRCZAZWQHC26/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WIMLQNM5EMJZOAVRCZAZWQHC26/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WIMLQNM5EMJZOAVRCZAZWQHC26","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":"566ae0235f82b226b144ccc159f8aa9bec8367c822c9c8749cc819c10864fc61","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-20T06:06:35Z","title_canon_sha256":"ce87a2d24bcf3c5594862f5385f92525f065ad84537f2d605fad50c8fa6d1e96"},"schema_version":"1.0","source":{"id":"2601.13632","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.13632","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"arxiv_version","alias_value":"2601.13632v2","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.13632","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"pith_short_12","alias_value":"WIMLQNM5EMJZ","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"pith_short_16","alias_value":"WIMLQNM5EMJZOAVR","created_at":"2026-06-26T01:15:17Z"},{"alias_kind":"pith_short_8","alias_value":"WIMLQNM5","created_at":"2026-06-26T01:15:17Z"}],"graph_snapshots":[{"event_id":"sha256:127ef8677b773b7a01a3ea8472109f29f775c1d3dc9fd8bec1afeb9f16b61eeb","target":"graph","created_at":"2026-06-26T01:15:17Z","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/2601.13632/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the rapid development of the e-commerce industry, the logistics network is experiencing unprecedented pressure. The traditional static routing strategy most time cannot tolerate the traffic congestion and fluctuating retail demand. In this paper, we propose a Risk-Aware Dynamic Routing(RADR) framework which integrates Spatiotemporal Graph Neural Networks (ST-GNN) with combinatorial optimization. We first construct a logistics topology graph by using the discrete GPS data using spatial clustering methods. Subsequently, a hybrid deep learning model combining Graph Convolutional Network (GCN","authors_text":"Sichen Zhao, Xianling Zeng, Yalun Qi, Zhiming Xue, Zihan Yu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-20T06:06:35Z","title":"Resilient Routing: Risk-Aware Dynamic Routing in Smart Logistics via Spatiotemporal Graph Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.13632","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:adecb1db22084a7777aa765a8674ea5fb4695698a229a054bb68ddf6b5e79f0f","target":"record","created_at":"2026-06-26T01:15:17Z","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":"566ae0235f82b226b144ccc159f8aa9bec8367c822c9c8749cc819c10864fc61","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-20T06:06:35Z","title_canon_sha256":"ce87a2d24bcf3c5594862f5385f92525f065ad84537f2d605fad50c8fa6d1e96"},"schema_version":"1.0","source":{"id":"2601.13632","kind":"arxiv","version":2}},"canonical_sha256":"b218b8359d23139702b116419b40e2d794278deae347972f63d85907b1290f66","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b218b8359d23139702b116419b40e2d794278deae347972f63d85907b1290f66","first_computed_at":"2026-06-26T01:15:17.046183Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-26T01:15:17.046183Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2FxUXRqaJJyJed7GjFqND282EXo7klUIZB917l/j9V/eVyrbzmA/EP/rJR/wOFxIa0M0xpds1VmtmYzLZybwBQ==","signature_status":"signed_v1","signed_at":"2026-06-26T01:15:17.046676Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.13632","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:adecb1db22084a7777aa765a8674ea5fb4695698a229a054bb68ddf6b5e79f0f","sha256:127ef8677b773b7a01a3ea8472109f29f775c1d3dc9fd8bec1afeb9f16b61eeb"],"state_sha256":"ea876ad565386df6a440c4014e3ed5e0868c2ea85e347952a30d36bb39460881"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B0lNxld2q0OnhkCW+/Ej+DIoXPB6v8st5XnWaoLHiITfOceP3cg0dCN1adDSBZJoCQpU5FXGZdjX5JkRjQ2sCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-02T14:42:38.892347Z","bundle_sha256":"3e57f25f4f5b82c8811078e195331f8394fd70b7c7972f93d2d92e2cd94d5ddc"}}