{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:BCTRE2CSLCB6DFYY6TVKWFLAYD","short_pith_number":"pith:BCTRE2CS","schema_version":"1.0","canonical_sha256":"08a71268525883e19718f4eaab1560c0c31dbd132563ccdc45634a633c1f4b7e","source":{"kind":"arxiv","id":"2606.04464","version":1},"attestation_state":"computed","paper":{"title":"Homology-Preserving Dimensionality Reduction via Adaptive Mapper and Landmark Isomap","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CG","authors_text":"Bei Wang, Ilia Jahanshahi, Lin Yan, Shakiba Khourashahi","submitted_at":"2026-06-03T05:20:21Z","abstract_excerpt":"As data becomes increasingly central across engineering and scientific disciplines, effective visualization is essential for interpreting complex, high-dimensional structures. Dimensionality reduction techniques project high-dimensional data into lower dimensions while aiming to preserve structural properties such as pairwise distances and local neighborhoods. In this paper, we focus on improving homological preservation, that is, the retention of topological features such as connected components and loops, which is critical for maintaining global shape and continuity. We first introduce AdaMa"},"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":"2606.04464","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CG","submitted_at":"2026-06-03T05:20:21Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"4cbfdbe4e97c908628507e858a20b7b9394d966d7e15b63952b5f23cac3864a3","abstract_canon_sha256":"ed6e043d733bc688ff79ce5db825b1132d8a32ca82ec0d25220c3935113497c5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T01:09:09.215266Z","signature_b64":"2Rx02YLwHeSLVRyWynfQAOD/Jnq5Ul4tABWYgrZKwC8xFY9aY9HBvaFb+GVBooUtkgpG+zcgKhj1JxqFfrNxDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08a71268525883e19718f4eaab1560c0c31dbd132563ccdc45634a633c1f4b7e","last_reissued_at":"2026-06-04T01:09:09.214513Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T01:09:09.214513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Homology-Preserving Dimensionality Reduction via Adaptive Mapper and Landmark Isomap","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CG","authors_text":"Bei Wang, Ilia Jahanshahi, Lin Yan, Shakiba Khourashahi","submitted_at":"2026-06-03T05:20:21Z","abstract_excerpt":"As data becomes increasingly central across engineering and scientific disciplines, effective visualization is essential for interpreting complex, high-dimensional structures. Dimensionality reduction techniques project high-dimensional data into lower dimensions while aiming to preserve structural properties such as pairwise distances and local neighborhoods. In this paper, we focus on improving homological preservation, that is, the retention of topological features such as connected components and loops, which is critical for maintaining global shape and continuity. We first introduce AdaMa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.04464","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/2606.04464/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":"2606.04464","created_at":"2026-06-04T01:09:09.214638+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.04464v1","created_at":"2026-06-04T01:09:09.214638+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.04464","created_at":"2026-06-04T01:09:09.214638+00:00"},{"alias_kind":"pith_short_12","alias_value":"BCTRE2CSLCB6","created_at":"2026-06-04T01:09:09.214638+00:00"},{"alias_kind":"pith_short_16","alias_value":"BCTRE2CSLCB6DFYY","created_at":"2026-06-04T01:09:09.214638+00:00"},{"alias_kind":"pith_short_8","alias_value":"BCTRE2CS","created_at":"2026-06-04T01:09:09.214638+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/BCTRE2CSLCB6DFYY6TVKWFLAYD","json":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD.json","graph_json":"https://pith.science/api/pith-number/BCTRE2CSLCB6DFYY6TVKWFLAYD/graph.json","events_json":"https://pith.science/api/pith-number/BCTRE2CSLCB6DFYY6TVKWFLAYD/events.json","paper":"https://pith.science/paper/BCTRE2CS"},"agent_actions":{"view_html":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD","download_json":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD.json","view_paper":"https://pith.science/paper/BCTRE2CS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.04464&json=true","fetch_graph":"https://pith.science/api/pith-number/BCTRE2CSLCB6DFYY6TVKWFLAYD/graph.json","fetch_events":"https://pith.science/api/pith-number/BCTRE2CSLCB6DFYY6TVKWFLAYD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD/action/storage_attestation","attest_author":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD/action/author_attestation","sign_citation":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD/action/citation_signature","submit_replication":"https://pith.science/pith/BCTRE2CSLCB6DFYY6TVKWFLAYD/action/replication_record"}},"created_at":"2026-06-04T01:09:09.214638+00:00","updated_at":"2026-06-04T01:09:09.214638+00:00"}