{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CPZWJQ7C3V4XJDNWXKPQRYS5XJ","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":"44e225e5729feb434a48f221257072517d0a08d8923afcdfdb2816909bb79f20","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.DS","submitted_at":"2025-07-18T12:53:58Z","title_canon_sha256":"d4969e4809f0bd0c3e3b054f031b3a93641ca6fb34abf6bb1fb7635f6b92fd74"},"schema_version":"1.0","source":{"id":"2507.14261","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.14261","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"arxiv_version","alias_value":"2507.14261v1","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.14261","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"pith_short_12","alias_value":"CPZWJQ7C3V4X","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"pith_short_16","alias_value":"CPZWJQ7C3V4XJDNW","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"pith_short_8","alias_value":"CPZWJQ7C","created_at":"2026-07-05T11:40:02Z"}],"graph_snapshots":[{"event_id":"sha256:58942098e98ba8805c2629dc42e4d915166414258bd2b1eaed858e2afb7a6df2","target":"graph","created_at":"2026-07-05T11:40:02Z","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/2507.14261/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present Fast Approximate Minimum Spanning Tree (FAMST), a novel algorithm that addresses the computational challenges of constructing Minimum Spanning Trees (MSTs) for large-scale and high-dimensional datasets. FAMST utilizes a three-phase approach: Approximate Nearest Neighbor (ANN) graph construction, ANN inter-component connection, and iterative edge refinement. For a dataset of $n$ points in a $d$-dimensional space, FAMST achieves $\\mathcal{O}(dn \\log n)$ time complexity and $\\mathcal{O}(dn + kn)$ space complexity when $k$ nearest neighbors are considered, which is a significant improve","authors_text":"Mahmood K. M. Almansoori, Miklos Telek","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.DS","submitted_at":"2025-07-18T12:53:58Z","title":"FAMST: Fast Approximate Minimum Spanning Tree Construction for Large-Scale and High-Dimensional Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.14261","kind":"arxiv","version":1},"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":"sha256:452109c4889e6ecfe23326495aa63fbeabb4fd60ba82869d8bb48b9b90733cf5","target":"record","created_at":"2026-07-05T11:40:02Z","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":"44e225e5729feb434a48f221257072517d0a08d8923afcdfdb2816909bb79f20","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.DS","submitted_at":"2025-07-18T12:53:58Z","title_canon_sha256":"d4969e4809f0bd0c3e3b054f031b3a93641ca6fb34abf6bb1fb7635f6b92fd74"},"schema_version":"1.0","source":{"id":"2507.14261","kind":"arxiv","version":1}},"canonical_sha256":"13f364c3e2dd79748db6ba9f08e25dba49aa9273d2f33a1f5a1f1409f5917fae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"13f364c3e2dd79748db6ba9f08e25dba49aa9273d2f33a1f5a1f1409f5917fae","first_computed_at":"2026-07-05T11:40:02.943920Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:40:02.943920Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yy7WwiuhOgiL2RiB7Yq6MCa+Y8K63CNlbiYeaag9V2l9L64X7r3ArhLiCDKaq3jG70C6eODqnm6dP3/6c+ClBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:40:02.944400Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.14261","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:452109c4889e6ecfe23326495aa63fbeabb4fd60ba82869d8bb48b9b90733cf5","sha256:58942098e98ba8805c2629dc42e4d915166414258bd2b1eaed858e2afb7a6df2"],"state_sha256":"6ea9662aa1bd04730ef2072a4d6700a003c7315bfd3f620f50b06afc7b7b138e"}