{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:6VHWR57YH5KQZILHI5MEKD4XMW","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":"046d1d20696b31d9b8a19ab6c75a418640cbb5353902f1c709fb0be6f05cfe00","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-10T09:59:16Z","title_canon_sha256":"2148644b931c69257bd8784437636d54343495a545244f0b843706b08b005c9c"},"schema_version":"1.0","source":{"id":"2501.05819","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.05819","created_at":"2026-07-05T09:59:28Z"},{"alias_kind":"arxiv_version","alias_value":"2501.05819v1","created_at":"2026-07-05T09:59:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.05819","created_at":"2026-07-05T09:59:28Z"},{"alias_kind":"pith_short_12","alias_value":"6VHWR57YH5KQ","created_at":"2026-07-05T09:59:28Z"},{"alias_kind":"pith_short_16","alias_value":"6VHWR57YH5KQZILH","created_at":"2026-07-05T09:59:28Z"},{"alias_kind":"pith_short_8","alias_value":"6VHWR57Y","created_at":"2026-07-05T09:59:28Z"}],"graph_snapshots":[{"event_id":"sha256:31e4c3641698ca9161c1d8fbade0bad27a68fa9a5ae3db2dfd457a4db2d1550e","target":"graph","created_at":"2026-07-05T09:59:28Z","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/2501.05819/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Unmanned Aerial Vehicles (UAVs) are increasingly adopted in modern communication networks. However, challenges in decision-making and digital modeling continue to impede their rapid advancement. Reinforcement Learning (RL) algorithms face limitations such as low sample efficiency and limited data versatility, further magnified in UAV communication scenarios. Moreover, Digital Twin (DT) modeling introduces substantial decision-making and data management complexities. RL models, often integrated into DT frameworks, require extensive training data to achieve accurate predictions. In contrast to t","authors_text":"Hao Zhou, Kai Li, Luis Almeida, Yousef Emami","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-10T09:59:16Z","title":"Diffusion Models for Smarter UAVs: Decision-Making and Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.05819","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:e93ac6318029de012a4ab10c0ac6252ee8832fbfccae4985624c075165e6a3e3","target":"record","created_at":"2026-07-05T09:59:28Z","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":"046d1d20696b31d9b8a19ab6c75a418640cbb5353902f1c709fb0be6f05cfe00","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-10T09:59:16Z","title_canon_sha256":"2148644b931c69257bd8784437636d54343495a545244f0b843706b08b005c9c"},"schema_version":"1.0","source":{"id":"2501.05819","kind":"arxiv","version":1}},"canonical_sha256":"f54f68f7f83f550ca1674758450f9765b0d0feba7a547bd211b9a07ddd814a55","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f54f68f7f83f550ca1674758450f9765b0d0feba7a547bd211b9a07ddd814a55","first_computed_at":"2026-07-05T09:59:28.989830Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:59:28.989830Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9jD/9aNc3/KYDlfBcMM5WnF0O6a7G/IRyxonzAVjoF+8/C3xsLyPP8haR6vHrO4w2FZGXrA2kzFAUjJP9uYNDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:59:28.990344Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.05819","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e93ac6318029de012a4ab10c0ac6252ee8832fbfccae4985624c075165e6a3e3","sha256:31e4c3641698ca9161c1d8fbade0bad27a68fa9a5ae3db2dfd457a4db2d1550e"],"state_sha256":"75505cc63be3fb6efbb5c08ed7188bbd272e4654ef6170ec1327d3a1ac4a51a6"}