{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:EBW3HRH7EIQNRSFQUULWU3EEWF","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":"26bde296afed8474dee001fa35d8bb6c647bef5b500f84f98ef4f79a8da814c9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-20T17:00:45Z","title_canon_sha256":"de79dc706e1505135af931eddb7f917b0bf1efba791ba89b0ddb65ea8826e027"},"schema_version":"1.0","source":{"id":"2410.15449","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.15449","created_at":"2026-07-05T09:23:19Z"},{"alias_kind":"arxiv_version","alias_value":"2410.15449v1","created_at":"2026-07-05T09:23:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.15449","created_at":"2026-07-05T09:23:19Z"},{"alias_kind":"pith_short_12","alias_value":"EBW3HRH7EIQN","created_at":"2026-07-05T09:23:19Z"},{"alias_kind":"pith_short_16","alias_value":"EBW3HRH7EIQNRSFQ","created_at":"2026-07-05T09:23:19Z"},{"alias_kind":"pith_short_8","alias_value":"EBW3HRH7","created_at":"2026-07-05T09:23:19Z"}],"graph_snapshots":[{"event_id":"sha256:98e369ad1d19595ff47f6361556b64c077cc462736a878fe81e8fd5a28465b34","target":"graph","created_at":"2026-07-05T09:23:19Z","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/2410.15449/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spatial Crowdsourcing (SC) is gaining traction in both academia and industry, with tasks on SC platforms becoming increasingly complex and requiring collaboration among workers with diverse skills. Recent research works address complex tasks by dividing them into subtasks with dependencies and assigning them to suitable workers. However, the dependencies among subtasks and their heterogeneous skill requirements, as well as the need for efficient utilization of workers' limited work time in the multi-task allocation mode, pose challenges in achieving an optimal task allocation scheme. Therefore","authors_text":"Chen Gao, En Wang, Fei-Yue Wang, Jincai Huang, Yong Zhao, Zhengqiu Zhu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-20T17:00:45Z","title":"Heterogeneous Graph Reinforcement Learning for Dependency-aware Multi-task Allocation in Spatial Crowdsourcing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.15449","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:fd4da66cdf4733ae6047b3ae6b6e13abbaca6887bf84f9ab6eda57366ff1f859","target":"record","created_at":"2026-07-05T09:23:19Z","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":"26bde296afed8474dee001fa35d8bb6c647bef5b500f84f98ef4f79a8da814c9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-20T17:00:45Z","title_canon_sha256":"de79dc706e1505135af931eddb7f917b0bf1efba791ba89b0ddb65ea8826e027"},"schema_version":"1.0","source":{"id":"2410.15449","kind":"arxiv","version":1}},"canonical_sha256":"206db3c4ff2220d8c8b0a5176a6c84b14b6e554171b7bda50b827a9f02aab775","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"206db3c4ff2220d8c8b0a5176a6c84b14b6e554171b7bda50b827a9f02aab775","first_computed_at":"2026-07-05T09:23:19.808139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:23:19.808139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y3uB0IMz5xDDHgsq0YCtrgMl5QNedqcDE82swyxfhcXOgXLQWXlJoIeAWG0WgUhXB4htzIHOa1BM1Qesk4AtCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:23:19.808570Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.15449","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd4da66cdf4733ae6047b3ae6b6e13abbaca6887bf84f9ab6eda57366ff1f859","sha256:98e369ad1d19595ff47f6361556b64c077cc462736a878fe81e8fd5a28465b34"],"state_sha256":"fc706adf03464df82c15d2b379961efd6175258f802a9d229ba63f0945e63b52"}