{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7PYCRJD54A2OAQ7EA27TNI7ROM","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":"5c3eac62ddae9b7e33ae05c3005ea45f12296a7ddb488379b011e0c70e7c9790","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-27T13:45:22Z","title_canon_sha256":"e57b64253bc74b2148503cfd6831806d55f1e26d5da1129c892d8ca11d338551"},"schema_version":"1.0","source":{"id":"2607.24436","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.24436","created_at":"2026-07-28T02:24:03Z"},{"alias_kind":"arxiv_version","alias_value":"2607.24436v1","created_at":"2026-07-28T02:24:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.24436","created_at":"2026-07-28T02:24:03Z"},{"alias_kind":"pith_short_12","alias_value":"7PYCRJD54A2O","created_at":"2026-07-28T02:24:03Z"},{"alias_kind":"pith_short_16","alias_value":"7PYCRJD54A2OAQ7E","created_at":"2026-07-28T02:24:03Z"},{"alias_kind":"pith_short_8","alias_value":"7PYCRJD5","created_at":"2026-07-28T02:24:03Z"}],"graph_snapshots":[{"event_id":"sha256:783bb20ef07837a3c1d88f0245fdb917fe5190f2221c338c1c961b75bc44f05a","target":"graph","created_at":"2026-07-28T02:24:03Z","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/2607.24436/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"High-fidelity 3D generative modeling increasingly relies on the latent diffusion paradigm, where the reconstruction quality of the underlying 3D VAE becomes a primary bottleneck. Existing approaches largely follow two paradigms: sparse voxel-based representations achieve strong reconstruction quality but incur significant memory and computational overhead, while set-based representations are compact and continuous yet typically lag in fidelity due to latent sparsity and excessive global smoothness. We propose MSVS-VAE, a hierarchical set-based VAE that closes this fidelity gap without sacrific","authors_text":"Dehao Hao, Dongyu Yan, Kaiyi Zhang, Lingting Zhu, Li Yuan, Long Quan, Runze Zhang, Tanghui Jia, Weikai Chen, Xiangjun Gao, Xin Wang, Yingda Yin, Zeyu Hu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-27T13:45:22Z","title":"MSVS-VAE: Multi-Scale Anchored VecSet for High-Fidelity 3D Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.24436","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":"sha256:82e089bea4b6ce7e169b16afcfa778a08cd4cf8c3f7860dc5037a82079becad6","target":"record","created_at":"2026-07-28T02:24:03Z","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":"5c3eac62ddae9b7e33ae05c3005ea45f12296a7ddb488379b011e0c70e7c9790","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-27T13:45:22Z","title_canon_sha256":"e57b64253bc74b2148503cfd6831806d55f1e26d5da1129c892d8ca11d338551"},"schema_version":"1.0","source":{"id":"2607.24436","kind":"arxiv","version":1}},"canonical_sha256":"fbf028a47de034e043e406bf36a3f17303acecc2558fca93bb3a460aab97e49b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fbf028a47de034e043e406bf36a3f17303acecc2558fca93bb3a460aab97e49b","first_computed_at":"2026-07-28T02:24:03.299308Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-28T02:24:03.299308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IfWtDbcMi2LcsYMPzGVyiNfgc/ZFskCTCo8cbmkha/Px109D0Y0Jekx9Bq+pSmsdBu8sFvaNsLn/+rv7mHhHCw==","signature_status":"signed_v1","signed_at":"2026-07-28T02:24:03.300164Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.24436","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82e089bea4b6ce7e169b16afcfa778a08cd4cf8c3f7860dc5037a82079becad6","sha256:783bb20ef07837a3c1d88f0245fdb917fe5190f2221c338c1c961b75bc44f05a"],"state_sha256":"900aa4b99994c711f0ec942bb2ab2fcddb3b17693b725be1f29ae52de947d8cb"}