{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:H7WY3YHDINATEH4NPP6ODMWM3V","short_pith_number":"pith:H7WY3YHD","canonical_record":{"source":{"id":"2501.13442","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-23T07:47:00Z","cross_cats_sorted":["cs.DB","cs.DC","cs.LG"],"title_canon_sha256":"a9c140d09c8aa043f1976c5f795719f420c310ea3ab4bd4217e69e9453d74a04","abstract_canon_sha256":"f266caf86a7873bec61cfdf6a23438ed8dd32d0fbce3ba01eb5016bbe5100932"},"schema_version":"1.0"},"canonical_sha256":"3fed8de0e34341321f8d7bfce1b2ccdd42e548081778c877a1253f69e6c7ad64","source":{"kind":"arxiv","id":"2501.13442","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.13442","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"arxiv_version","alias_value":"2501.13442v1","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.13442","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"pith_short_12","alias_value":"H7WY3YHDINAT","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"pith_short_16","alias_value":"H7WY3YHDINATEH4N","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"pith_short_8","alias_value":"H7WY3YHD","created_at":"2026-07-05T10:04:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:H7WY3YHDINATEH4NPP6ODMWM3V","target":"record","payload":{"canonical_record":{"source":{"id":"2501.13442","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-23T07:47:00Z","cross_cats_sorted":["cs.DB","cs.DC","cs.LG"],"title_canon_sha256":"a9c140d09c8aa043f1976c5f795719f420c310ea3ab4bd4217e69e9453d74a04","abstract_canon_sha256":"f266caf86a7873bec61cfdf6a23438ed8dd32d0fbce3ba01eb5016bbe5100932"},"schema_version":"1.0"},"canonical_sha256":"3fed8de0e34341321f8d7bfce1b2ccdd42e548081778c877a1253f69e6c7ad64","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:04:28.681545Z","signature_b64":"VidhSeKC+Rc9P8sibAEjJJ+lk36BaIoMA0QyorfFnseBIePxNLWe+TF7/onj0UE2zsDJ0d5+Ix1IrI17SKe6DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3fed8de0e34341321f8d7bfce1b2ccdd42e548081778c877a1253f69e6c7ad64","last_reissued_at":"2026-07-05T10:04:28.681001Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:04:28.681001Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.13442","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:04:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"owrrn7uJJWtLWWpmr63rgt66aoDxZtWHWAw8WDaT1FZPg2h4wam3A2S1DXBVH+L7CFOVSTdrty+gt1kLkVl9Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:16:02.544923Z"},"content_sha256":"a8f49a4939ae0dcc4ed934eb15064bdf44e5f7c0ee9d3f7a0d88160011fe16e7","schema_version":"1.0","event_id":"sha256:a8f49a4939ae0dcc4ed934eb15064bdf44e5f7c0ee9d3f7a0d88160011fe16e7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:H7WY3YHDINATEH4NPP6ODMWM3V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Billion-scale Similarity Search Using a Hybrid Indexing Approach with Advanced Filtering","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.DB","cs.DC","cs.LG"],"primary_cat":"cs.IR","authors_text":"Aleksandar Dimov, Simeon Emanuilov","submitted_at":"2025-01-23T07:47:00Z","abstract_excerpt":"This paper presents a novel approach for similarity search with complex filtering capabilities on billion-scale datasets, optimized for CPU inference. Our method extends the classical IVF-Flat index structure to integrate multi-dimensional filters. The proposed algorithm combines dense embeddings with discrete filtering attributes, enabling fast retrieval in high-dimensional spaces. Designed specifically for CPU-based systems, our disk-based approach offers a cost-effective solution for large-scale similarity search. We demonstrate the effectiveness of our method through a case study, showcasi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.13442","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/2501.13442/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":"2026-07-05T10:04:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cc4balXMiYJsbtl+Crt2ByMWYCmP+bdYfgoUtLvoz+sq9BgX4ycCovkt21yVSs+x/y38eNQX/g4bTLiCePQEBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:16:02.545437Z"},"content_sha256":"424041596dd45075be339d3ba702ebbade8cbf5b35e8675b1136856c87afb992","schema_version":"1.0","event_id":"sha256:424041596dd45075be339d3ba702ebbade8cbf5b35e8675b1136856c87afb992"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H7WY3YHDINATEH4NPP6ODMWM3V/bundle.json","state_url":"https://pith.science/pith/H7WY3YHDINATEH4NPP6ODMWM3V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H7WY3YHDINATEH4NPP6ODMWM3V/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":"2026-08-23T04:16:02Z","links":{"resolver":"https://pith.science/pith/H7WY3YHDINATEH4NPP6ODMWM3V","bundle":"https://pith.science/pith/H7WY3YHDINATEH4NPP6ODMWM3V/bundle.json","state":"https://pith.science/pith/H7WY3YHDINATEH4NPP6ODMWM3V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H7WY3YHDINATEH4NPP6ODMWM3V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:H7WY3YHDINATEH4NPP6ODMWM3V","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":"f266caf86a7873bec61cfdf6a23438ed8dd32d0fbce3ba01eb5016bbe5100932","cross_cats_sorted":["cs.DB","cs.DC","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-23T07:47:00Z","title_canon_sha256":"a9c140d09c8aa043f1976c5f795719f420c310ea3ab4bd4217e69e9453d74a04"},"schema_version":"1.0","source":{"id":"2501.13442","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.13442","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"arxiv_version","alias_value":"2501.13442v1","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.13442","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"pith_short_12","alias_value":"H7WY3YHDINAT","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"pith_short_16","alias_value":"H7WY3YHDINATEH4N","created_at":"2026-07-05T10:04:28Z"},{"alias_kind":"pith_short_8","alias_value":"H7WY3YHD","created_at":"2026-07-05T10:04:28Z"}],"graph_snapshots":[{"event_id":"sha256:424041596dd45075be339d3ba702ebbade8cbf5b35e8675b1136856c87afb992","target":"graph","created_at":"2026-07-05T10:04:28Z","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/2501.13442/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents a novel approach for similarity search with complex filtering capabilities on billion-scale datasets, optimized for CPU inference. Our method extends the classical IVF-Flat index structure to integrate multi-dimensional filters. The proposed algorithm combines dense embeddings with discrete filtering attributes, enabling fast retrieval in high-dimensional spaces. Designed specifically for CPU-based systems, our disk-based approach offers a cost-effective solution for large-scale similarity search. We demonstrate the effectiveness of our method through a case study, showcasi","authors_text":"Aleksandar Dimov, Simeon Emanuilov","cross_cats":["cs.DB","cs.DC","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-23T07:47:00Z","title":"Billion-scale Similarity Search Using a Hybrid Indexing Approach with Advanced Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.13442","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:a8f49a4939ae0dcc4ed934eb15064bdf44e5f7c0ee9d3f7a0d88160011fe16e7","target":"record","created_at":"2026-07-05T10:04:28Z","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":"f266caf86a7873bec61cfdf6a23438ed8dd32d0fbce3ba01eb5016bbe5100932","cross_cats_sorted":["cs.DB","cs.DC","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-23T07:47:00Z","title_canon_sha256":"a9c140d09c8aa043f1976c5f795719f420c310ea3ab4bd4217e69e9453d74a04"},"schema_version":"1.0","source":{"id":"2501.13442","kind":"arxiv","version":1}},"canonical_sha256":"3fed8de0e34341321f8d7bfce1b2ccdd42e548081778c877a1253f69e6c7ad64","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3fed8de0e34341321f8d7bfce1b2ccdd42e548081778c877a1253f69e6c7ad64","first_computed_at":"2026-07-05T10:04:28.681001Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:04:28.681001Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VidhSeKC+Rc9P8sibAEjJJ+lk36BaIoMA0QyorfFnseBIePxNLWe+TF7/onj0UE2zsDJ0d5+Ix1IrI17SKe6DA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:04:28.681545Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.13442","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8f49a4939ae0dcc4ed934eb15064bdf44e5f7c0ee9d3f7a0d88160011fe16e7","sha256:424041596dd45075be339d3ba702ebbade8cbf5b35e8675b1136856c87afb992"],"state_sha256":"171cb8e50ccd0ed9d4d7574755071a275077289808e5037505cd9b7e637df486"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p3EAwbClgjG02owzq8d4KYI7Hx5FktosEw1HIEMNnEMD3bqfkQfzEMyr2zT6VuCZREnyN4xujq43uB8vVOoeAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T04:16:02.550919Z","bundle_sha256":"02db19391dc5bd425ab9c8a10cbe5699944eb5acfbdc1981013f05e6f7b59e11"}}