{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2CCYNU7Q33VZF6YO2LNVYE3LO2","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":"6c7857cd3c171951b2d3cd607ec5a3fe25556be374bbb21cfae5f67190da79fb","cross_cats_sorted":["cs.DB","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2024-05-29T20:40:20Z","title_canon_sha256":"d4598748b87d3a39b199016c49dd08b277fe8f570439763ccb6b3cce641cae0f"},"schema_version":"1.0","source":{"id":"2405.19504","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.19504","created_at":"2026-06-10T00:08:24Z"},{"alias_kind":"arxiv_version","alias_value":"2405.19504v2","created_at":"2026-06-10T00:08:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19504","created_at":"2026-06-10T00:08:24Z"},{"alias_kind":"pith_short_12","alias_value":"2CCYNU7Q33VZ","created_at":"2026-06-10T00:08:24Z"},{"alias_kind":"pith_short_16","alias_value":"2CCYNU7Q33VZF6YO","created_at":"2026-06-10T00:08:24Z"},{"alias_kind":"pith_short_8","alias_value":"2CCYNU7Q","created_at":"2026-06-10T00:08:24Z"}],"graph_snapshots":[{"event_id":"sha256:4b01edcca02101c9435682c083758492eb3841b98f9e6086f539c14c2d75748f","target":"graph","created_at":"2026-06-10T00:08:24Z","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/2405.19504/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural embedding models have become a fundamental component of modern information retrieval (IR) pipelines. These models produce a single embedding $x \\in \\mathbb{R}^d$ per data-point, allowing for fast retrieval via highly optimized maximum inner product search (MIPS) algorithms. Recently, beginning with the landmark ColBERT paper, multi-vector models, which produce a set of embedding per data point, have achieved markedly superior performance for IR tasks. Unfortunately, using these models for IR is computationally expensive due to the increased complexity of multi-vector retrieval and scori","authors_text":"Jason Lee, Laxman Dhulipala, Majid Hadian, Rajesh Jayaram, Vahab Mirrokni","cross_cats":["cs.DB","cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2024-05-29T20:40:20Z","title":"MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19504","kind":"arxiv","version":2},"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":"sha256:31c8ee6f65042ec7d101bb1c17fea49a9c1b1b53f347072c6ab5b9bdb79f249a","target":"record","created_at":"2026-06-10T00:08:24Z","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":"6c7857cd3c171951b2d3cd607ec5a3fe25556be374bbb21cfae5f67190da79fb","cross_cats_sorted":["cs.DB","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2024-05-29T20:40:20Z","title_canon_sha256":"d4598748b87d3a39b199016c49dd08b277fe8f570439763ccb6b3cce641cae0f"},"schema_version":"1.0","source":{"id":"2405.19504","kind":"arxiv","version":2}},"canonical_sha256":"d08586d3f0deeb92fb0ed2db5c136b768d2028f51d057b69c1cdb9cd1611bc52","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d08586d3f0deeb92fb0ed2db5c136b768d2028f51d057b69c1cdb9cd1611bc52","first_computed_at":"2026-06-10T00:08:24.897954Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-10T00:08:24.897954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hmlSeIOXFBK9mgVas/CmIzng2RZUuEw5mW1FbeSG4SX8UFC3v3Un+aOyL8Nny91KUDlPUmEKSycCEUn+wexjDg==","signature_status":"signed_v1","signed_at":"2026-06-10T00:08:24.899203Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.19504","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:31c8ee6f65042ec7d101bb1c17fea49a9c1b1b53f347072c6ab5b9bdb79f249a","sha256:4b01edcca02101c9435682c083758492eb3841b98f9e6086f539c14c2d75748f"],"state_sha256":"30ae757c0df0894f6f405aadf2923c3c7612ef677404e5b2d47c0fbe96bbafaa"}