{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:CGGCZBXVTWTTRFSF7MAAI6FTX2","short_pith_number":"pith:CGGCZBXV","schema_version":"1.0","canonical_sha256":"118c2c86f59da7389645fb000478b3be937defaefb57b8a9f48758bb73044e9c","source":{"kind":"arxiv","id":"2605.19065","version":1},"attestation_state":"computed","paper":{"title":"A Geometric Algebra-Informed 3D Gaussian Splatting Framework for Wireless Scene Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Jingzhou Shen, Tianya Zhao, Xuyu Wang","submitted_at":"2026-05-18T19:47:27Z","abstract_excerpt":"In this paper, we introduce Geometric Algebra-Informed 3D Gaussian Splatting (GAI-GS), a framework for wireless modeling that couples 3D Gaussian splatting with a geometric algebra-based attention mechanism to explicitly model ray-object interactions in complex propagation environments. GAI-GS encodes joint spatial-electromagnetic (EM) relations into token representations, enabling scene-level aggregation within a unified, end-to-end neural architecture. This design grounds wireless ray propagation in electromagnetic principles, allowing token interactions to model key effects such as multipat"},"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":"2605.19065","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2026-05-18T19:47:27Z","cross_cats_sorted":[],"title_canon_sha256":"75ba465732fca1ad35e32ba1e2886a61136723b4312ee06941d3bc849a45488d","abstract_canon_sha256":"fb8cdbc9252bac94b7e0f06031628da72c639e30788f23635ea7a2f70d445937"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:05:25.727977Z","signature_b64":"X1l+Wxpc88p9VJJnNMvN55V8ntpHTMo7p9EQd7KIcO1mrEIupx8nxh2W7MNd2AfWDi5OVXj+h4ozMqNVeloOCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"118c2c86f59da7389645fb000478b3be937defaefb57b8a9f48758bb73044e9c","last_reissued_at":"2026-05-20T01:05:25.727419Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:05:25.727419Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Geometric Algebra-Informed 3D Gaussian Splatting Framework for Wireless Scene Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Jingzhou Shen, Tianya Zhao, Xuyu Wang","submitted_at":"2026-05-18T19:47:27Z","abstract_excerpt":"In this paper, we introduce Geometric Algebra-Informed 3D Gaussian Splatting (GAI-GS), a framework for wireless modeling that couples 3D Gaussian splatting with a geometric algebra-based attention mechanism to explicitly model ray-object interactions in complex propagation environments. GAI-GS encodes joint spatial-electromagnetic (EM) relations into token representations, enabling scene-level aggregation within a unified, end-to-end neural architecture. This design grounds wireless ray propagation in electromagnetic principles, allowing token interactions to model key effects such as multipat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19065","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/2605.19065/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":"2605.19065","created_at":"2026-05-20T01:05:25.727511+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.19065v1","created_at":"2026-05-20T01:05:25.727511+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19065","created_at":"2026-05-20T01:05:25.727511+00:00"},{"alias_kind":"pith_short_12","alias_value":"CGGCZBXVTWTT","created_at":"2026-05-20T01:05:25.727511+00:00"},{"alias_kind":"pith_short_16","alias_value":"CGGCZBXVTWTTRFSF","created_at":"2026-05-20T01:05:25.727511+00:00"},{"alias_kind":"pith_short_8","alias_value":"CGGCZBXV","created_at":"2026-05-20T01:05:25.727511+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/CGGCZBXVTWTTRFSF7MAAI6FTX2","json":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2.json","graph_json":"https://pith.science/api/pith-number/CGGCZBXVTWTTRFSF7MAAI6FTX2/graph.json","events_json":"https://pith.science/api/pith-number/CGGCZBXVTWTTRFSF7MAAI6FTX2/events.json","paper":"https://pith.science/paper/CGGCZBXV"},"agent_actions":{"view_html":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2","download_json":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2.json","view_paper":"https://pith.science/paper/CGGCZBXV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.19065&json=true","fetch_graph":"https://pith.science/api/pith-number/CGGCZBXVTWTTRFSF7MAAI6FTX2/graph.json","fetch_events":"https://pith.science/api/pith-number/CGGCZBXVTWTTRFSF7MAAI6FTX2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2/action/storage_attestation","attest_author":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2/action/author_attestation","sign_citation":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2/action/citation_signature","submit_replication":"https://pith.science/pith/CGGCZBXVTWTTRFSF7MAAI6FTX2/action/replication_record"}},"created_at":"2026-05-20T01:05:25.727511+00:00","updated_at":"2026-05-20T01:05:25.727511+00:00"}