{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XOX5HXUY7GEK5NDS4SFCUTNB22","short_pith_number":"pith:XOX5HXUY","schema_version":"1.0","canonical_sha256":"bbafd3de98f988aeb472e48a2a4da1d6950750f402e2e9660d4cb01a9862c8b9","source":{"kind":"arxiv","id":"2606.26985","version":1},"attestation_state":"computed","paper":{"title":"Vis4GS: A Visual Analytic Tool for 3D Gaussian Splatting Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Aryabima Mandala Putra, Jui-Chi Lee, Kai-Yuan Lin, Shih-Hsuan Hung","submitted_at":"2026-06-25T12:59:02Z","abstract_excerpt":"3D Gaussian Splatting (3DGS) supports fast training and real-time rendering, but its optimization process remains difficult to interpret. Existing viewers mainly expose the final reconstructed scene and offer limited support for explaining how Gaussian properties contribute to visible artifacts or evolve during training. We present Vis4GS, a multi-view visual analytics tool for primitive-level diagnosis of 3DGS reconstruction artifacts. Built on the original 3DGS viewer and training framework, Vis4GS links rendered artifacts to Gaussian properties, View Coverage, training progress, and Gaussia"},"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":"2606.26985","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2026-06-25T12:59:02Z","cross_cats_sorted":[],"title_canon_sha256":"a2892ee924eacd412abbbfbcb4c88d58ca9cadced76a9640c9e0cc98d654a5ec","abstract_canon_sha256":"d500f4ee7e72439f63f04b58612c12c7a914d31296de030432af7171ea3f4f12"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-26T01:16:05.947532Z","signature_b64":"/o74mpeoFiUMUpJJZtwQFHgbGg39WMGsfJFqX6KWBbZkCTOV4vTl1av6yWiKQtye3ZhXpWeBDcwcda0sj7uvAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bbafd3de98f988aeb472e48a2a4da1d6950750f402e2e9660d4cb01a9862c8b9","last_reissued_at":"2026-06-26T01:16:05.947180Z","signature_status":"signed_v1","first_computed_at":"2026-06-26T01:16:05.947180Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Vis4GS: A Visual Analytic Tool for 3D Gaussian Splatting Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Aryabima Mandala Putra, Jui-Chi Lee, Kai-Yuan Lin, Shih-Hsuan Hung","submitted_at":"2026-06-25T12:59:02Z","abstract_excerpt":"3D Gaussian Splatting (3DGS) supports fast training and real-time rendering, but its optimization process remains difficult to interpret. Existing viewers mainly expose the final reconstructed scene and offer limited support for explaining how Gaussian properties contribute to visible artifacts or evolve during training. We present Vis4GS, a multi-view visual analytics tool for primitive-level diagnosis of 3DGS reconstruction artifacts. Built on the original 3DGS viewer and training framework, Vis4GS links rendered artifacts to Gaussian properties, View Coverage, training progress, and Gaussia"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.26985","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/2606.26985/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":"2606.26985","created_at":"2026-06-26T01:16:05.947235+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.26985v1","created_at":"2026-06-26T01:16:05.947235+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.26985","created_at":"2026-06-26T01:16:05.947235+00:00"},{"alias_kind":"pith_short_12","alias_value":"XOX5HXUY7GEK","created_at":"2026-06-26T01:16:05.947235+00:00"},{"alias_kind":"pith_short_16","alias_value":"XOX5HXUY7GEK5NDS","created_at":"2026-06-26T01:16:05.947235+00:00"},{"alias_kind":"pith_short_8","alias_value":"XOX5HXUY","created_at":"2026-06-26T01:16:05.947235+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/XOX5HXUY7GEK5NDS4SFCUTNB22","json":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22.json","graph_json":"https://pith.science/api/pith-number/XOX5HXUY7GEK5NDS4SFCUTNB22/graph.json","events_json":"https://pith.science/api/pith-number/XOX5HXUY7GEK5NDS4SFCUTNB22/events.json","paper":"https://pith.science/paper/XOX5HXUY"},"agent_actions":{"view_html":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22","download_json":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22.json","view_paper":"https://pith.science/paper/XOX5HXUY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.26985&json=true","fetch_graph":"https://pith.science/api/pith-number/XOX5HXUY7GEK5NDS4SFCUTNB22/graph.json","fetch_events":"https://pith.science/api/pith-number/XOX5HXUY7GEK5NDS4SFCUTNB22/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22/action/storage_attestation","attest_author":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22/action/author_attestation","sign_citation":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22/action/citation_signature","submit_replication":"https://pith.science/pith/XOX5HXUY7GEK5NDS4SFCUTNB22/action/replication_record"}},"created_at":"2026-06-26T01:16:05.947235+00:00","updated_at":"2026-06-26T01:16:05.947235+00:00"}