{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:AFUCHZCGGSH2GA3GXM4FH4OHMM","short_pith_number":"pith:AFUCHZCG","schema_version":"1.0","canonical_sha256":"016823e446348fa30366bb3853f1c76315f91a94e34e897c485d861a058fc9dd","source":{"kind":"arxiv","id":"2506.10342","version":2},"attestation_state":"computed","paper":{"title":"UrbanSense:A Framework for Quantitative Analysis of Urban Streetscapes leveraging Vision Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Jing Zhong, Jun Yin, Miao Zhang, Peilin Li, Pengyu Zeng, Ruolin Pan, Shuai Lu","submitted_at":"2025-06-12T04:35:39Z","abstract_excerpt":"Urban cultures and architectural styles vary significantly across cities due to geographical, chronological, historical, and socio-political factors. Understanding these differences is essential for anticipating how cities may evolve in the future. As representative cases of historical continuity and modern innovation in China, Beijing and Shenzhen offer valuable perspectives for exploring the transformation of urban streetscapes. However, conventional approaches to urban cultural studies often rely on expert interpretation and historical documentation, which are difficult to standardize acros"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.10342","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-12T04:35:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"808e80bee2d0f37fea6539bbb23fddab82e5e72bc9e6d326590d6ef39e4b4658","abstract_canon_sha256":"131081994f3f23ff59ffe60e828a7e2b158b681ccddf92b497b4390e35f47598"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:48:04.578853Z","signature_b64":"fS+a+c2CHGLivA8s2XsdfwZXm8O9vNlGDiSbp7C1KidBu5VskmghPntNlSmCa6vypiNNCHP+n0v0Z59Kg0/PAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"016823e446348fa30366bb3853f1c76315f91a94e34e897c485d861a058fc9dd","last_reissued_at":"2026-07-05T11:48:04.578273Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:48:04.578273Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"UrbanSense:A Framework for Quantitative Analysis of Urban Streetscapes leveraging Vision Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Jing Zhong, Jun Yin, Miao Zhang, Peilin Li, Pengyu Zeng, Ruolin Pan, Shuai Lu","submitted_at":"2025-06-12T04:35:39Z","abstract_excerpt":"Urban cultures and architectural styles vary significantly across cities due to geographical, chronological, historical, and socio-political factors. Understanding these differences is essential for anticipating how cities may evolve in the future. As representative cases of historical continuity and modern innovation in China, Beijing and Shenzhen offer valuable perspectives for exploring the transformation of urban streetscapes. However, conventional approaches to urban cultural studies often rely on expert interpretation and historical documentation, which are difficult to standardize acros"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.10342","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/2506.10342/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.10342","created_at":"2026-07-05T11:48:04.578368+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.10342v2","created_at":"2026-07-05T11:48:04.578368+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.10342","created_at":"2026-07-05T11:48:04.578368+00:00"},{"alias_kind":"pith_short_12","alias_value":"AFUCHZCGGSH2","created_at":"2026-07-05T11:48:04.578368+00:00"},{"alias_kind":"pith_short_16","alias_value":"AFUCHZCGGSH2GA3G","created_at":"2026-07-05T11:48:04.578368+00:00"},{"alias_kind":"pith_short_8","alias_value":"AFUCHZCG","created_at":"2026-07-05T11:48:04.578368+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2506.21562","citing_title":"FloorPlan-DeepSeek (FPDS): A multimodal approach to floorplan generation using vector-based next room prediction","ref_index":834,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM","json":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM.json","graph_json":"https://pith.science/api/pith-number/AFUCHZCGGSH2GA3GXM4FH4OHMM/graph.json","events_json":"https://pith.science/api/pith-number/AFUCHZCGGSH2GA3GXM4FH4OHMM/events.json","paper":"https://pith.science/paper/AFUCHZCG"},"agent_actions":{"view_html":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM","download_json":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM.json","view_paper":"https://pith.science/paper/AFUCHZCG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.10342&json=true","fetch_graph":"https://pith.science/api/pith-number/AFUCHZCGGSH2GA3GXM4FH4OHMM/graph.json","fetch_events":"https://pith.science/api/pith-number/AFUCHZCGGSH2GA3GXM4FH4OHMM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM/action/storage_attestation","attest_author":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM/action/author_attestation","sign_citation":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM/action/citation_signature","submit_replication":"https://pith.science/pith/AFUCHZCGGSH2GA3GXM4FH4OHMM/action/replication_record"}},"created_at":"2026-07-05T11:48:04.578368+00:00","updated_at":"2026-07-05T11:48:04.578368+00:00"}