{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HRDP2CCTSH5GN7ZPXW4M2Q4DKP","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":"062ca78ce6ec9da0a6478b9ddbf6ea96288427361713aa2795f6eb57e8bd6e3b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-07T14:49:00Z","title_canon_sha256":"f56cb768e58a4588924ab502d8d005906b5bb0f9176c81f5879dbf4e27424253"},"schema_version":"1.0","source":{"id":"2406.04983","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04983","created_at":"2026-07-05T08:28:51Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04983v1","created_at":"2026-07-05T08:28:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04983","created_at":"2026-07-05T08:28:51Z"},{"alias_kind":"pith_short_12","alias_value":"HRDP2CCTSH5G","created_at":"2026-07-05T08:28:51Z"},{"alias_kind":"pith_short_16","alias_value":"HRDP2CCTSH5GN7ZP","created_at":"2026-07-05T08:28:51Z"},{"alias_kind":"pith_short_8","alias_value":"HRDP2CCT","created_at":"2026-07-05T08:28:51Z"}],"graph_snapshots":[{"event_id":"sha256:d3e297fc1c78d544e71fd3eed2f87db0730f30f1c698e660aecdbc9f24df4204","target":"graph","created_at":"2026-07-05T08:28:51Z","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/2406.04983/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"City scene generation has gained significant attention in autonomous driving, smart city development, and traffic simulation. It helps enhance infrastructure planning and monitoring solutions. Existing methods have employed a two-stage process involving city layout generation, typically using Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), or Transformers, followed by neural rendering. These techniques often exhibit limited diversity and noticeable artifacts in the rendered city scenes. The rendered scenes lack variety, resembling the training images, resulting in mono","authors_text":"Gaoang Wang, Jenq-Neng Hwang, Jianshu Guo, Jie Deng, Junsheng Huang, Mingyan Gao, Qixuan Huang, Shengyu Hao, Wenhao Chai, Wenhao Hu, Xi Li, Zhonghan Zhao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-07T14:49:00Z","title":"CityCraft: A Real Crafter for 3D City Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04983","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":"sha256:0894fe821a16f2dd09e456706f0983ce15574a99e6286d7af9c17b49e3c8e938","target":"record","created_at":"2026-07-05T08:28:51Z","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":"062ca78ce6ec9da0a6478b9ddbf6ea96288427361713aa2795f6eb57e8bd6e3b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-07T14:49:00Z","title_canon_sha256":"f56cb768e58a4588924ab502d8d005906b5bb0f9176c81f5879dbf4e27424253"},"schema_version":"1.0","source":{"id":"2406.04983","kind":"arxiv","version":1}},"canonical_sha256":"3c46fd085391fa66ff2fbdb8cd438353e7eb8a558edb3da8871bb4d248eb0e4e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3c46fd085391fa66ff2fbdb8cd438353e7eb8a558edb3da8871bb4d248eb0e4e","first_computed_at":"2026-07-05T08:28:51.877049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:28:51.877049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"d2truBJ2HrIHU/4hLi8zGEEOC37REjVbWjbTROQ2CM+g2pzjGbWRe03MExSNlyk3gsBChcWPCUfKaysB82RUDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:28:51.877543Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.04983","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0894fe821a16f2dd09e456706f0983ce15574a99e6286d7af9c17b49e3c8e938","sha256:d3e297fc1c78d544e71fd3eed2f87db0730f30f1c698e660aecdbc9f24df4204"],"state_sha256":"fb3498bb708addf56dd28146dd661d672258449b943ac56ecd4050f1cc719050"}