{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:3FIA2YHY7TJOHAUHSLQKUBLFWH","short_pith_number":"pith:3FIA2YHY","canonical_record":{"source":{"id":"2606.09086","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T06:32:49Z","cross_cats_sorted":[],"title_canon_sha256":"169c5afd2ab580ab64558afac0d69de6bcfd2469cfd85519e2b8af5dd8dad5e2","abstract_canon_sha256":"8a0f5d63d46709081c16784b2c904efdceacba56f10ee9326449ab6daae759f3"},"schema_version":"1.0"},"canonical_sha256":"d9500d60f8fcd2e3828792e0aa0565b1e8b0dd99fe34ed7b357e290232c8777f","source":{"kind":"arxiv","id":"2606.09086","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09086","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09086v1","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09086","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_12","alias_value":"3FIA2YHY7TJO","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_16","alias_value":"3FIA2YHY7TJOHAUH","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_8","alias_value":"3FIA2YHY","created_at":"2026-06-09T02:07:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:3FIA2YHY7TJOHAUHSLQKUBLFWH","target":"record","payload":{"canonical_record":{"source":{"id":"2606.09086","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T06:32:49Z","cross_cats_sorted":[],"title_canon_sha256":"169c5afd2ab580ab64558afac0d69de6bcfd2469cfd85519e2b8af5dd8dad5e2","abstract_canon_sha256":"8a0f5d63d46709081c16784b2c904efdceacba56f10ee9326449ab6daae759f3"},"schema_version":"1.0"},"canonical_sha256":"d9500d60f8fcd2e3828792e0aa0565b1e8b0dd99fe34ed7b357e290232c8777f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T02:07:58.179387Z","signature_b64":"+rpGpQV5eGUKaYvgLeORGqA0coNYVCICx19ZpT45v26vookGtNlKXY5AN7CW8vxxZTI0fu2daFAKcDALEwFWBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d9500d60f8fcd2e3828792e0aa0565b1e8b0dd99fe34ed7b357e290232c8777f","last_reissued_at":"2026-06-09T02:07:58.178556Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T02:07:58.178556Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.09086","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":"2026-06-09T02:07:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VmLBCvxeljr82cZFdqyCOHlUou8Mt7dSql4PKpKZHmIEmPC/9ppffoD6HUgzrt7fbAoDgwQIxTUMyxl6IzQlCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T04:58:56.475431Z"},"content_sha256":"43aa407dcb416d13d9e4192c83d8b10600e982127bb62d81d50193ccc8eb0d30","schema_version":"1.0","event_id":"sha256:43aa407dcb416d13d9e4192c83d8b10600e982127bb62d81d50193ccc8eb0d30"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:3FIA2YHY7TJOHAUHSLQKUBLFWH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DynaOD: Dynamic Origin-Destination Flow Generation with Discrete-to-Continuous Temporal Semantic Modeling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Huandong Wang, Jie Feng, Jie Zhao, Xianqi Dai, Yong Li","submitted_at":"2026-06-08T06:32:49Z","abstract_excerpt":"Dynamic origin-destination (OD) flow generation seeks to synthesize realistic mobility dynamics from temporal context alone, without relying on historical OD observations. A key challenge is to translate semantic temporal signals into temporally coherent OD patterns while preserving the inherent spatial heterogeneity of urban regions. We propose DynaOD, a semantic-driven framework that models temporal dynamics through two complementary perspectives: discrete directional trends that characterize qualitative shifts in urban activity patterns, and continuous temporal evolution that captures how s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09086","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/2606.09086/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":"2026-06-09T02:07:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p1nTmoLc214UxD7j6A4AG4n8lxxzYKntR9OfZEqfaz45arHUQiNTsmgCfx580TnmI+BKkUmKrAXIlipIh/AbDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T04:58:56.476176Z"},"content_sha256":"737366628a0c94754e0467439b8c2bc0c1addb335e9b6c3a848a8d6d0e6ff58c","schema_version":"1.0","event_id":"sha256:737366628a0c94754e0467439b8c2bc0c1addb335e9b6c3a848a8d6d0e6ff58c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3FIA2YHY7TJOHAUHSLQKUBLFWH/bundle.json","state_url":"https://pith.science/pith/3FIA2YHY7TJOHAUHSLQKUBLFWH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3FIA2YHY7TJOHAUHSLQKUBLFWH/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":"2026-06-11T04:58:56Z","links":{"resolver":"https://pith.science/pith/3FIA2YHY7TJOHAUHSLQKUBLFWH","bundle":"https://pith.science/pith/3FIA2YHY7TJOHAUHSLQKUBLFWH/bundle.json","state":"https://pith.science/pith/3FIA2YHY7TJOHAUHSLQKUBLFWH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3FIA2YHY7TJOHAUHSLQKUBLFWH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3FIA2YHY7TJOHAUHSLQKUBLFWH","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":"8a0f5d63d46709081c16784b2c904efdceacba56f10ee9326449ab6daae759f3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T06:32:49Z","title_canon_sha256":"169c5afd2ab580ab64558afac0d69de6bcfd2469cfd85519e2b8af5dd8dad5e2"},"schema_version":"1.0","source":{"id":"2606.09086","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09086","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09086v1","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09086","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_12","alias_value":"3FIA2YHY7TJO","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_16","alias_value":"3FIA2YHY7TJOHAUH","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_8","alias_value":"3FIA2YHY","created_at":"2026-06-09T02:07:58Z"}],"graph_snapshots":[{"event_id":"sha256:737366628a0c94754e0467439b8c2bc0c1addb335e9b6c3a848a8d6d0e6ff58c","target":"graph","created_at":"2026-06-09T02:07:58Z","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/2606.09086/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Dynamic origin-destination (OD) flow generation seeks to synthesize realistic mobility dynamics from temporal context alone, without relying on historical OD observations. A key challenge is to translate semantic temporal signals into temporally coherent OD patterns while preserving the inherent spatial heterogeneity of urban regions. We propose DynaOD, a semantic-driven framework that models temporal dynamics through two complementary perspectives: discrete directional trends that characterize qualitative shifts in urban activity patterns, and continuous temporal evolution that captures how s","authors_text":"Huandong Wang, Jie Feng, Jie Zhao, Xianqi Dai, Yong Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T06:32:49Z","title":"DynaOD: Dynamic Origin-Destination Flow Generation with Discrete-to-Continuous Temporal Semantic Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09086","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":"sha256:43aa407dcb416d13d9e4192c83d8b10600e982127bb62d81d50193ccc8eb0d30","target":"record","created_at":"2026-06-09T02:07:58Z","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":"8a0f5d63d46709081c16784b2c904efdceacba56f10ee9326449ab6daae759f3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T06:32:49Z","title_canon_sha256":"169c5afd2ab580ab64558afac0d69de6bcfd2469cfd85519e2b8af5dd8dad5e2"},"schema_version":"1.0","source":{"id":"2606.09086","kind":"arxiv","version":1}},"canonical_sha256":"d9500d60f8fcd2e3828792e0aa0565b1e8b0dd99fe34ed7b357e290232c8777f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d9500d60f8fcd2e3828792e0aa0565b1e8b0dd99fe34ed7b357e290232c8777f","first_computed_at":"2026-06-09T02:07:58.178556Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T02:07:58.178556Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+rpGpQV5eGUKaYvgLeORGqA0coNYVCICx19ZpT45v26vookGtNlKXY5AN7CW8vxxZTI0fu2daFAKcDALEwFWBQ==","signature_status":"signed_v1","signed_at":"2026-06-09T02:07:58.179387Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.09086","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:43aa407dcb416d13d9e4192c83d8b10600e982127bb62d81d50193ccc8eb0d30","sha256:737366628a0c94754e0467439b8c2bc0c1addb335e9b6c3a848a8d6d0e6ff58c"],"state_sha256":"7f50c22a325d4c31b8bebe7c29594832a635f0b99b7d2c52d019048ea2be15c0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a5AKxnGcHHFz6ww0w32Z2+9m8doiBbtDzTVa8ztcwzkRrBaOqr3iZFIGQ0a5MzJPRhUdzHj9Tf/d2AwFQ0q2Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T04:58:56.480873Z","bundle_sha256":"1b370eeffd6a207c5260730c3ab9ec943ff6031c2595aa70e0859a5eb68ecd5e"}}