{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LBEUIZTJMSFLV6LVKXIPJDTDV4","short_pith_number":"pith:LBEUIZTJ","canonical_record":{"source":{"id":"2502.02187","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T10:02:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f548c24f839e8ffc3f04f1e67a860b107681b54e170c1f86c8b8b4c07a05262f","abstract_canon_sha256":"660f1aa4ac01396d32d2443dda61edd9fd0c5143dfc06e8d98fce9b430a8a302"},"schema_version":"1.0"},"canonical_sha256":"5849446669648abaf97555d0f48e63af2491d64496bfed6b645ff554672fd928","source":{"kind":"arxiv","id":"2502.02187","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02187","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02187v2","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02187","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"pith_short_12","alias_value":"LBEUIZTJMSFL","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"pith_short_16","alias_value":"LBEUIZTJMSFLV6LV","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"pith_short_8","alias_value":"LBEUIZTJ","created_at":"2026-07-05T10:32:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LBEUIZTJMSFLV6LVKXIPJDTDV4","target":"record","payload":{"canonical_record":{"source":{"id":"2502.02187","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T10:02:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f548c24f839e8ffc3f04f1e67a860b107681b54e170c1f86c8b8b4c07a05262f","abstract_canon_sha256":"660f1aa4ac01396d32d2443dda61edd9fd0c5143dfc06e8d98fce9b430a8a302"},"schema_version":"1.0"},"canonical_sha256":"5849446669648abaf97555d0f48e63af2491d64496bfed6b645ff554672fd928","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:32:38.916028Z","signature_b64":"Onch38NAmCT6V3u0cQUjILW09kVpUYIWoGJtq3S9XRUYgskj2vP26UmL2f2dd+uKa5tCg/qQAHh3Y3O7NSIeAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5849446669648abaf97555d0f48e63af2491d64496bfed6b645ff554672fd928","last_reissued_at":"2026-07-05T10:32:38.915348Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:32:38.915348Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.02187","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:32:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZSYwtIyszmTksDhhYAO1zk9DIg7V2k5OCarYJK24fK5PHHnkTjE3Pyj+5V+h7j2m97AL/UTZV/xGdgLFJoxPAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:32:32.403696Z"},"content_sha256":"4d6538d23edb3fb2585648fcf19683503a2603e20924107384ff36c1686ef134","schema_version":"1.0","event_id":"sha256:4d6538d23edb3fb2585648fcf19683503a2603e20924107384ff36c1686ef134"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LBEUIZTJMSFLV6LVKXIPJDTDV4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Mathieu Desbrun, Matthew Fisher, Nissim Maruani, Pierre Alliez, Wang Yifan","submitted_at":"2025-02-04T10:02:40Z","abstract_excerpt":"This paper proposes ShapeShifter, a new 3D generative model that learns to synthesize shape variations based on a single reference model. While generative methods for 3D objects have recently attracted much attention, current techniques often lack geometric details and/or require long training times and large resources. Our approach remedies these issues by combining sparse voxel grids and point, normal, and color sampling within a multiscale neural architecture that can be trained efficiently and in parallel. We show that our resulting variations better capture the fine details of their origi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02187","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/2502.02187/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:32:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nea74UDbaHsLvOFxknRVD/D0LNmlKUf3gYG7QSwSIAoHY+59GNYhE+OeOfZfXLjAyg/Xq9UoPuyB6DMfmorRAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:32:32.404218Z"},"content_sha256":"ddab6decdb2d2edb749cd62cce49694237d741b86fa9a417070dfd6ea2a76b64","schema_version":"1.0","event_id":"sha256:ddab6decdb2d2edb749cd62cce49694237d741b86fa9a417070dfd6ea2a76b64"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LBEUIZTJMSFLV6LVKXIPJDTDV4/bundle.json","state_url":"https://pith.science/pith/LBEUIZTJMSFLV6LVKXIPJDTDV4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LBEUIZTJMSFLV6LVKXIPJDTDV4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T10:32:32Z","links":{"resolver":"https://pith.science/pith/LBEUIZTJMSFLV6LVKXIPJDTDV4","bundle":"https://pith.science/pith/LBEUIZTJMSFLV6LVKXIPJDTDV4/bundle.json","state":"https://pith.science/pith/LBEUIZTJMSFLV6LVKXIPJDTDV4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LBEUIZTJMSFLV6LVKXIPJDTDV4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LBEUIZTJMSFLV6LVKXIPJDTDV4","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":"660f1aa4ac01396d32d2443dda61edd9fd0c5143dfc06e8d98fce9b430a8a302","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T10:02:40Z","title_canon_sha256":"f548c24f839e8ffc3f04f1e67a860b107681b54e170c1f86c8b8b4c07a05262f"},"schema_version":"1.0","source":{"id":"2502.02187","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02187","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02187v2","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02187","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"pith_short_12","alias_value":"LBEUIZTJMSFL","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"pith_short_16","alias_value":"LBEUIZTJMSFLV6LV","created_at":"2026-07-05T10:32:38Z"},{"alias_kind":"pith_short_8","alias_value":"LBEUIZTJ","created_at":"2026-07-05T10:32:38Z"}],"graph_snapshots":[{"event_id":"sha256:ddab6decdb2d2edb749cd62cce49694237d741b86fa9a417070dfd6ea2a76b64","target":"graph","created_at":"2026-07-05T10:32:38Z","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/2502.02187/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper proposes ShapeShifter, a new 3D generative model that learns to synthesize shape variations based on a single reference model. While generative methods for 3D objects have recently attracted much attention, current techniques often lack geometric details and/or require long training times and large resources. Our approach remedies these issues by combining sparse voxel grids and point, normal, and color sampling within a multiscale neural architecture that can be trained efficiently and in parallel. We show that our resulting variations better capture the fine details of their origi","authors_text":"Mathieu Desbrun, Matthew Fisher, Nissim Maruani, Pierre Alliez, Wang Yifan","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T10:02:40Z","title":"ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02187","kind":"arxiv","version":2},"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":"sha256:4d6538d23edb3fb2585648fcf19683503a2603e20924107384ff36c1686ef134","target":"record","created_at":"2026-07-05T10:32:38Z","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":"660f1aa4ac01396d32d2443dda61edd9fd0c5143dfc06e8d98fce9b430a8a302","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T10:02:40Z","title_canon_sha256":"f548c24f839e8ffc3f04f1e67a860b107681b54e170c1f86c8b8b4c07a05262f"},"schema_version":"1.0","source":{"id":"2502.02187","kind":"arxiv","version":2}},"canonical_sha256":"5849446669648abaf97555d0f48e63af2491d64496bfed6b645ff554672fd928","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5849446669648abaf97555d0f48e63af2491d64496bfed6b645ff554672fd928","first_computed_at":"2026-07-05T10:32:38.915348Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:32:38.915348Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Onch38NAmCT6V3u0cQUjILW09kVpUYIWoGJtq3S9XRUYgskj2vP26UmL2f2dd+uKa5tCg/qQAHh3Y3O7NSIeAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:32:38.916028Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.02187","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4d6538d23edb3fb2585648fcf19683503a2603e20924107384ff36c1686ef134","sha256:ddab6decdb2d2edb749cd62cce49694237d741b86fa9a417070dfd6ea2a76b64"],"state_sha256":"d09ab753b017abb3c85dba16c0c86deee7893faa2e5ed5c46b33c64308d5d7cc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f4rmcWod2RFttRXOkFqFhUctd5BxMEU8UJqa6NpgmitsGJaLcSrwG1E4U8xrDo6JKbOJZKX9xpjYhjk/6lSgBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T10:32:32.408104Z","bundle_sha256":"4444e2e2d56ba235509bd11433dc67fe128952c4d5c1c00ce024037277f8a2a0"}}