{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:RUYIBIN2DJMQCMDCIGGTW5POCI","short_pith_number":"pith:RUYIBIN2","schema_version":"1.0","canonical_sha256":"8d3080a1ba1a59013062418d3b75ee12315ba8a7bda72bda39a8b3db24ed14c0","source":{"kind":"arxiv","id":"2608.13255","version":1},"attestation_state":"computed","paper":{"title":"GeoCache: Training-Free Acceleration of Multi-View Texture Diffusion via Geometric Delta Transport","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Bo Liu, Haotang Li, Huanrui Yang, Kebin Peng, Sen He, Shaohan Henry Wang, Yutong Zhao, Zhenyu Qi, Zi Wang","submitted_at":"2026-08-13T13:57:35Z","abstract_excerpt":"Geometry-conditioned multi-view diffusion enables high-quality 3D texture generation, but its repeated per-view denoiser evaluations introduce substantial computational cost. Existing training-free accelerators primarily exploit temporal redundancy by reusing computation across denoising steps. In multi-view texturing, however, skipping a step also removes the cross-view interaction that continually aligns different observations of the same surface, leading to rapidly degraded consistency and fidelity. Our analysis identifies a complementary source of redundancy: although intermediate features"},"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":"2608.13255","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-08-13T13:57:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a60c9d080d8b365e666f09cf7a0b81f00e4efad9fee4bcba32e6af0ccbca3460","abstract_canon_sha256":"78403083f8dc53b6084cba40daeed42513ece12a01e1ee6fcac337bed6612c3f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-14T01:00:46.742911Z","signature_b64":"BoM3cePwqP1J8TNxH6RhFzA3f63CMZWwRzdcKwQ9mkaPlhaqae0ODiyDnUkpCSeksClCAj6LItYaADieICIaBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8d3080a1ba1a59013062418d3b75ee12315ba8a7bda72bda39a8b3db24ed14c0","last_reissued_at":"2026-08-14T01:00:46.740879Z","signature_status":"signed_v1","first_computed_at":"2026-08-14T01:00:46.740879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GeoCache: Training-Free Acceleration of Multi-View Texture Diffusion via Geometric Delta Transport","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Bo Liu, Haotang Li, Huanrui Yang, Kebin Peng, Sen He, Shaohan Henry Wang, Yutong Zhao, Zhenyu Qi, Zi Wang","submitted_at":"2026-08-13T13:57:35Z","abstract_excerpt":"Geometry-conditioned multi-view diffusion enables high-quality 3D texture generation, but its repeated per-view denoiser evaluations introduce substantial computational cost. Existing training-free accelerators primarily exploit temporal redundancy by reusing computation across denoising steps. In multi-view texturing, however, skipping a step also removes the cross-view interaction that continually aligns different observations of the same surface, leading to rapidly degraded consistency and fidelity. Our analysis identifies a complementary source of redundancy: although intermediate features"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.13255","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/2608.13255/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":"2608.13255","created_at":"2026-08-14T01:00:46.741913+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.13255v1","created_at":"2026-08-14T01:00:46.741913+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.13255","created_at":"2026-08-14T01:00:46.741913+00:00"},{"alias_kind":"pith_short_12","alias_value":"RUYIBIN2DJMQ","created_at":"2026-08-14T01:00:46.741913+00:00"},{"alias_kind":"pith_short_16","alias_value":"RUYIBIN2DJMQCMDC","created_at":"2026-08-14T01:00:46.741913+00:00"},{"alias_kind":"pith_short_8","alias_value":"RUYIBIN2","created_at":"2026-08-14T01:00:46.741913+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI","json":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI.json","graph_json":"https://pith.science/api/pith-number/RUYIBIN2DJMQCMDCIGGTW5POCI/graph.json","events_json":"https://pith.science/api/pith-number/RUYIBIN2DJMQCMDCIGGTW5POCI/events.json","paper":"https://pith.science/paper/RUYIBIN2"},"agent_actions":{"view_html":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI","download_json":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI.json","view_paper":"https://pith.science/paper/RUYIBIN2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.13255&json=true","fetch_graph":"https://pith.science/api/pith-number/RUYIBIN2DJMQCMDCIGGTW5POCI/graph.json","fetch_events":"https://pith.science/api/pith-number/RUYIBIN2DJMQCMDCIGGTW5POCI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI/action/storage_attestation","attest_author":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI/action/author_attestation","sign_citation":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI/action/citation_signature","submit_replication":"https://pith.science/pith/RUYIBIN2DJMQCMDCIGGTW5POCI/action/replication_record"}},"created_at":"2026-08-14T01:00:46.741913+00:00","updated_at":"2026-08-14T01:00:46.741913+00:00"}