{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:X6JYF3OJPC2PHBXYTOUNB6TKCY","short_pith_number":"pith:X6JYF3OJ","canonical_record":{"source":{"id":"2510.00566","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-10-01T06:38:45Z","cross_cats_sorted":["cs.AI","cs.DB"],"title_canon_sha256":"f8062900a21b76a245bd02d338a8c692742c2abba6c118e3a53ea23ba8ef7aac","abstract_canon_sha256":"c92b782a55c2270d3f5a5b7d3ef8510fa62d22328b41dab19228b5804ab9cab4"},"schema_version":"1.0"},"canonical_sha256":"bf9382edc978b4f386f89ba8d0fa6a1625dfe81445469b7af893918e3e9477e3","source":{"kind":"arxiv","id":"2510.00566","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.00566","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"arxiv_version","alias_value":"2510.00566v4","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.00566","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"pith_short_12","alias_value":"X6JYF3OJPC2P","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"pith_short_16","alias_value":"X6JYF3OJPC2PHBXY","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"pith_short_8","alias_value":"X6JYF3OJ","created_at":"2026-07-07T00:15:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:X6JYF3OJPC2PHBXYTOUNB6TKCY","target":"record","payload":{"canonical_record":{"source":{"id":"2510.00566","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-10-01T06:38:45Z","cross_cats_sorted":["cs.AI","cs.DB"],"title_canon_sha256":"f8062900a21b76a245bd02d338a8c692742c2abba6c118e3a53ea23ba8ef7aac","abstract_canon_sha256":"c92b782a55c2270d3f5a5b7d3ef8510fa62d22328b41dab19228b5804ab9cab4"},"schema_version":"1.0"},"canonical_sha256":"bf9382edc978b4f386f89ba8d0fa6a1625dfe81445469b7af893918e3e9477e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T00:15:50.103558Z","signature_b64":"RwB5Y5O2mhFTo6LzQ9MpWvaqbvmpjj8Xl5V8mpHjjwl3cJLIbzCRUdAA12Fcqps11wDV7X4vzwCf5BF7KQH9BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bf9382edc978b4f386f89ba8d0fa6a1625dfe81445469b7af893918e3e9477e3","last_reissued_at":"2026-07-07T00:15:50.102714Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T00:15:50.102714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2510.00566","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-07T00:15:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JtD8vNrmjbrf+TlnCUmB7KFUIG9UR7Ti+No7h5vK40m6pUyQT3rkS/QjVymvx74odu6jzZZvFkS/RMpYbjd0DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:19:56.859467Z"},"content_sha256":"55f0b61197b09b0593c514d5c82246903791949a21301ba94da856fb1f7bcb74","schema_version":"1.0","event_id":"sha256:55f0b61197b09b0593c514d5c82246903791949a21301ba94da856fb1f7bcb74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:X6JYF3OJPC2PHBXYTOUNB6TKCY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Panorama: Fast-Track Nearest Neighbors","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.DB"],"primary_cat":"cs.LG","authors_text":"Akash Nayar, Alexis Schlomer, Jignesh M. Patel, Panagiotis Karras, Sayan Ranu, Vansh Ramani","submitted_at":"2025-10-01T06:38:45Z","abstract_excerpt":"Approximate Nearest-Neighbor Search (ANNS) pipelines for high-dimensional neural embeddings spend the bulk of their query time in candidate verification, making it the primary bottleneck in the search process. In this paper, we present PANORAMA, a state-of-the-art refinement technique that accelerates verification by exploiting the inherent spectral decay of these embeddings. Using PCA to compact signal energy, PANORAMA evaluates candidate distances incrementally, computing at each step a strict lower bound on the full-vector distance and dynamically pruning candidates the moment this bound ex"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.00566","kind":"arxiv","version":4},"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/2510.00566/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":"2026-07-07T00:15:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ES3ShbaqA9p2pVPtcGHPNs2EFgVIyfZn87Zbxb1Ruawbdej8fZhpZP4rlkVmGV3luCsZMg+Qi8QV3sjYw/cNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:19:56.859958Z"},"content_sha256":"9b807d209389d4c5c81ad7b13f523936e660f96cfe1d6be6c8b919a7bb90cbd4","schema_version":"1.0","event_id":"sha256:9b807d209389d4c5c81ad7b13f523936e660f96cfe1d6be6c8b919a7bb90cbd4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X6JYF3OJPC2PHBXYTOUNB6TKCY/bundle.json","state_url":"https://pith.science/pith/X6JYF3OJPC2PHBXYTOUNB6TKCY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X6JYF3OJPC2PHBXYTOUNB6TKCY/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":"2026-08-11T04:19:56Z","links":{"resolver":"https://pith.science/pith/X6JYF3OJPC2PHBXYTOUNB6TKCY","bundle":"https://pith.science/pith/X6JYF3OJPC2PHBXYTOUNB6TKCY/bundle.json","state":"https://pith.science/pith/X6JYF3OJPC2PHBXYTOUNB6TKCY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X6JYF3OJPC2PHBXYTOUNB6TKCY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:X6JYF3OJPC2PHBXYTOUNB6TKCY","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":"c92b782a55c2270d3f5a5b7d3ef8510fa62d22328b41dab19228b5804ab9cab4","cross_cats_sorted":["cs.AI","cs.DB"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-10-01T06:38:45Z","title_canon_sha256":"f8062900a21b76a245bd02d338a8c692742c2abba6c118e3a53ea23ba8ef7aac"},"schema_version":"1.0","source":{"id":"2510.00566","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.00566","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"arxiv_version","alias_value":"2510.00566v4","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.00566","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"pith_short_12","alias_value":"X6JYF3OJPC2P","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"pith_short_16","alias_value":"X6JYF3OJPC2PHBXY","created_at":"2026-07-07T00:15:50Z"},{"alias_kind":"pith_short_8","alias_value":"X6JYF3OJ","created_at":"2026-07-07T00:15:50Z"}],"graph_snapshots":[{"event_id":"sha256:9b807d209389d4c5c81ad7b13f523936e660f96cfe1d6be6c8b919a7bb90cbd4","target":"graph","created_at":"2026-07-07T00:15:50Z","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/2510.00566/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Approximate Nearest-Neighbor Search (ANNS) pipelines for high-dimensional neural embeddings spend the bulk of their query time in candidate verification, making it the primary bottleneck in the search process. In this paper, we present PANORAMA, a state-of-the-art refinement technique that accelerates verification by exploiting the inherent spectral decay of these embeddings. Using PCA to compact signal energy, PANORAMA evaluates candidate distances incrementally, computing at each step a strict lower bound on the full-vector distance and dynamically pruning candidates the moment this bound ex","authors_text":"Akash Nayar, Alexis Schlomer, Jignesh M. Patel, Panagiotis Karras, Sayan Ranu, Vansh Ramani","cross_cats":["cs.AI","cs.DB"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-10-01T06:38:45Z","title":"Panorama: Fast-Track Nearest Neighbors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.00566","kind":"arxiv","version":4},"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":"sha256:55f0b61197b09b0593c514d5c82246903791949a21301ba94da856fb1f7bcb74","target":"record","created_at":"2026-07-07T00:15:50Z","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":"c92b782a55c2270d3f5a5b7d3ef8510fa62d22328b41dab19228b5804ab9cab4","cross_cats_sorted":["cs.AI","cs.DB"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-10-01T06:38:45Z","title_canon_sha256":"f8062900a21b76a245bd02d338a8c692742c2abba6c118e3a53ea23ba8ef7aac"},"schema_version":"1.0","source":{"id":"2510.00566","kind":"arxiv","version":4}},"canonical_sha256":"bf9382edc978b4f386f89ba8d0fa6a1625dfe81445469b7af893918e3e9477e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bf9382edc978b4f386f89ba8d0fa6a1625dfe81445469b7af893918e3e9477e3","first_computed_at":"2026-07-07T00:15:50.102714Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-07T00:15:50.102714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RwB5Y5O2mhFTo6LzQ9MpWvaqbvmpjj8Xl5V8mpHjjwl3cJLIbzCRUdAA12Fcqps11wDV7X4vzwCf5BF7KQH9BQ==","signature_status":"signed_v1","signed_at":"2026-07-07T00:15:50.103558Z","signed_message":"canonical_sha256_bytes"},"source_id":"2510.00566","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:55f0b61197b09b0593c514d5c82246903791949a21301ba94da856fb1f7bcb74","sha256:9b807d209389d4c5c81ad7b13f523936e660f96cfe1d6be6c8b919a7bb90cbd4"],"state_sha256":"5bb7bdf5b03d1a3f0e7deb9e781ba126949bb21b070d75b9cf87c5442b3ecd9a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6BGs5Cpaydg/KNYT7++EX9QaS3ji2kP1hbGX5v8UPew9HGvIyLcUEQSE66PypcfceRHupxy3Ups4Innjc2VFCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T04:19:56.863397Z","bundle_sha256":"0f7317a6206161885a39b0c64bd194a17813df6ff6f02cd758448d41b7829c79"}}