{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:KN2B6XG2PCQMNH532R2PGDWPXT","short_pith_number":"pith:KN2B6XG2","schema_version":"1.0","canonical_sha256":"53741f5cda78a0c69fbbd474f30ecfbcd4105702475ff747470f3ab34d39d1b4","source":{"kind":"arxiv","id":"2511.18801","version":3},"attestation_state":"computed","paper":{"title":"PartDiffuser: Part-wise 3D Mesh Generation via Discrete Diffusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baochang Zhang, Guojun Lei, Haodong Zhu, Hong Li, Linin Yang, Sheng Xu, Yichen Yang","submitted_at":"2025-11-24T06:11:21Z","abstract_excerpt":"Existing autoregressive (AR) methods for generating artist-designed meshes struggle to balance global structural consistency with high-fidelity local details, and are susceptible to error accumulation. To address this, we propose PartDiffuser, a novel semi-autoregressive diffusion framework for point-cloud-to-mesh generation. The method first performs semantic segmentation on the mesh and then operates in a \"part-wise\" manner: it employs autoregression between parts to ensure global topology, while utilizing a parallel discrete diffusion process within each semantic part to precisely reconstru"},"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":"2511.18801","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-24T06:11:21Z","cross_cats_sorted":[],"title_canon_sha256":"496db59dca359cae980a708597d29415055bb45131a009c8292b3443b0e25bcc","abstract_canon_sha256":"b8e32e6eb36596ff4fd49a375fb65221c5cf92e470bd56488eae7c6129cce509"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:02:59.196096Z","signature_b64":"gwaQ7kYNMbAkw/5lrwdlljrgj5JGWQGWApxu9QRbFOH7o1/qglI/69DzAqVUbjHaoXjRP3yhfIo1Wp/CAvBfAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"53741f5cda78a0c69fbbd474f30ecfbcd4105702475ff747470f3ab34d39d1b4","last_reissued_at":"2026-05-20T00:02:59.195101Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:02:59.195101Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"PartDiffuser: Part-wise 3D Mesh Generation via Discrete Diffusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baochang Zhang, Guojun Lei, Haodong Zhu, Hong Li, Linin Yang, Sheng Xu, Yichen Yang","submitted_at":"2025-11-24T06:11:21Z","abstract_excerpt":"Existing autoregressive (AR) methods for generating artist-designed meshes struggle to balance global structural consistency with high-fidelity local details, and are susceptible to error accumulation. To address this, we propose PartDiffuser, a novel semi-autoregressive diffusion framework for point-cloud-to-mesh generation. The method first performs semantic segmentation on the mesh and then operates in a \"part-wise\" manner: it employs autoregression between parts to ensure global topology, while utilizing a parallel discrete diffusion process within each semantic part to precisely reconstru"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.18801","kind":"arxiv","version":3},"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/2511.18801/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":"2511.18801","created_at":"2026-05-20T00:02:59.195271+00:00"},{"alias_kind":"arxiv_version","alias_value":"2511.18801v3","created_at":"2026-05-20T00:02:59.195271+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.18801","created_at":"2026-05-20T00:02:59.195271+00:00"},{"alias_kind":"pith_short_12","alias_value":"KN2B6XG2PCQM","created_at":"2026-05-20T00:02:59.195271+00:00"},{"alias_kind":"pith_short_16","alias_value":"KN2B6XG2PCQMNH53","created_at":"2026-05-20T00:02:59.195271+00:00"},{"alias_kind":"pith_short_8","alias_value":"KN2B6XG2","created_at":"2026-05-20T00:02:59.195271+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/KN2B6XG2PCQMNH532R2PGDWPXT","json":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT.json","graph_json":"https://pith.science/api/pith-number/KN2B6XG2PCQMNH532R2PGDWPXT/graph.json","events_json":"https://pith.science/api/pith-number/KN2B6XG2PCQMNH532R2PGDWPXT/events.json","paper":"https://pith.science/paper/KN2B6XG2"},"agent_actions":{"view_html":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT","download_json":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT.json","view_paper":"https://pith.science/paper/KN2B6XG2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2511.18801&json=true","fetch_graph":"https://pith.science/api/pith-number/KN2B6XG2PCQMNH532R2PGDWPXT/graph.json","fetch_events":"https://pith.science/api/pith-number/KN2B6XG2PCQMNH532R2PGDWPXT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT/action/storage_attestation","attest_author":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT/action/author_attestation","sign_citation":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT/action/citation_signature","submit_replication":"https://pith.science/pith/KN2B6XG2PCQMNH532R2PGDWPXT/action/replication_record"}},"created_at":"2026-05-20T00:02:59.195271+00:00","updated_at":"2026-05-20T00:02:59.195271+00:00"}