{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:Q5232NDYNQLHMEK37BL26URS3U","short_pith_number":"pith:Q5232NDY","canonical_record":{"source":{"id":"2103.09944","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2021-03-17T23:13:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ba474a72ba8441d6e913bcb2d25529c692dae88e38acfd584c31a0525d6e0976","abstract_canon_sha256":"073aad4339080c9ad248a3967eabcb7beb5a5e69744f938e4b4f8ef5ff957286"},"schema_version":"1.0"},"canonical_sha256":"8775bd34786c1676115bf857af5232dd16c6b27c7d05e8283b098b0ff844743a","source":{"kind":"arxiv","id":"2103.09944","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.09944","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"arxiv_version","alias_value":"2103.09944v1","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.09944","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"pith_short_12","alias_value":"Q5232NDYNQLH","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"pith_short_16","alias_value":"Q5232NDYNQLHMEK3","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"pith_short_8","alias_value":"Q5232NDY","created_at":"2026-07-05T02:24:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:Q5232NDYNQLHMEK37BL26URS3U","target":"record","payload":{"canonical_record":{"source":{"id":"2103.09944","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2021-03-17T23:13:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ba474a72ba8441d6e913bcb2d25529c692dae88e38acfd584c31a0525d6e0976","abstract_canon_sha256":"073aad4339080c9ad248a3967eabcb7beb5a5e69744f938e4b4f8ef5ff957286"},"schema_version":"1.0"},"canonical_sha256":"8775bd34786c1676115bf857af5232dd16c6b27c7d05e8283b098b0ff844743a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:24:15.224155Z","signature_b64":"KbZt72GQU5E1BjHkW8H+eeBILA97GO3REDA9b3vFw82d3D6t/jGDnjvRj4Q5+35bCJMRXbZK2wyap2bjxsvsDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8775bd34786c1676115bf857af5232dd16c6b27c7d05e8283b098b0ff844743a","last_reissued_at":"2026-07-05T02:24:15.223728Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:24:15.223728Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.09944","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":"2026-07-05T02:24:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ywPsbxsqrwjU7Xm2Oy6sdcAZLFaBg0klBysrGW3BZ3PFPQ7Dn3lcHrgHLF5ERiKv5LAGLlG9lyJgxuQPZ8GRAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T04:16:02.742785Z"},"content_sha256":"2c26bf81ecdbb4579f45bdcb46a394a85e6c6b251f8609bd65dc5e3070c057c4","schema_version":"1.0","event_id":"sha256:2c26bf81ecdbb4579f45bdcb46a394a85e6c6b251f8609bd65dc5e3070c057c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:Q5232NDYNQLHMEK37BL26URS3U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IRLI: Iterative Re-partitioning for Learning to Index","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Alexander J Smola, Anshumali Shrivastava, Gaurav Gupta, Tharun Medini","submitted_at":"2021-03-17T23:13:25Z","abstract_excerpt":"Neural models have transformed the fundamental information retrieval problem of mapping a query to a giant set of items. However, the need for efficient and low latency inference forces the community to reconsider efficient approximate near-neighbor search in the item space. To this end, learning to index is gaining much interest in recent times. Methods have to trade between obtaining high accuracy while maintaining load balance and scalability in distributed settings. We propose a novel approach called IRLI (pronounced `early'), which iteratively partitions the items by learning the relevant"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.09944","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/2103.09944/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":"2026-07-05T02:24:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fb7zQEJju9Kz61lnXkp20VNIpv2qVH/SEVdSzAlQi3lhj8JB5DVbJe9/26prHVLVff3+nMr0lQnA6hpoa5CNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T04:16:02.743378Z"},"content_sha256":"a583d1c2926d696a6aca694bddfd134a8d30d619639415db43e8ad9c9b36700a","schema_version":"1.0","event_id":"sha256:a583d1c2926d696a6aca694bddfd134a8d30d619639415db43e8ad9c9b36700a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q5232NDYNQLHMEK37BL26URS3U/bundle.json","state_url":"https://pith.science/pith/Q5232NDYNQLHMEK37BL26URS3U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q5232NDYNQLHMEK37BL26URS3U/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":"2026-08-04T04:16:02Z","links":{"resolver":"https://pith.science/pith/Q5232NDYNQLHMEK37BL26URS3U","bundle":"https://pith.science/pith/Q5232NDYNQLHMEK37BL26URS3U/bundle.json","state":"https://pith.science/pith/Q5232NDYNQLHMEK37BL26URS3U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q5232NDYNQLHMEK37BL26URS3U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:Q5232NDYNQLHMEK37BL26URS3U","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":"073aad4339080c9ad248a3967eabcb7beb5a5e69744f938e4b4f8ef5ff957286","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2021-03-17T23:13:25Z","title_canon_sha256":"ba474a72ba8441d6e913bcb2d25529c692dae88e38acfd584c31a0525d6e0976"},"schema_version":"1.0","source":{"id":"2103.09944","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.09944","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"arxiv_version","alias_value":"2103.09944v1","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.09944","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"pith_short_12","alias_value":"Q5232NDYNQLH","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"pith_short_16","alias_value":"Q5232NDYNQLHMEK3","created_at":"2026-07-05T02:24:15Z"},{"alias_kind":"pith_short_8","alias_value":"Q5232NDY","created_at":"2026-07-05T02:24:15Z"}],"graph_snapshots":[{"event_id":"sha256:a583d1c2926d696a6aca694bddfd134a8d30d619639415db43e8ad9c9b36700a","target":"graph","created_at":"2026-07-05T02:24:15Z","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/2103.09944/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural models have transformed the fundamental information retrieval problem of mapping a query to a giant set of items. However, the need for efficient and low latency inference forces the community to reconsider efficient approximate near-neighbor search in the item space. To this end, learning to index is gaining much interest in recent times. Methods have to trade between obtaining high accuracy while maintaining load balance and scalability in distributed settings. We propose a novel approach called IRLI (pronounced `early'), which iteratively partitions the items by learning the relevant","authors_text":"Alexander J Smola, Anshumali Shrivastava, Gaurav Gupta, Tharun Medini","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2021-03-17T23:13:25Z","title":"IRLI: Iterative Re-partitioning for Learning to Index"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.09944","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":"sha256:2c26bf81ecdbb4579f45bdcb46a394a85e6c6b251f8609bd65dc5e3070c057c4","target":"record","created_at":"2026-07-05T02:24:15Z","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":"073aad4339080c9ad248a3967eabcb7beb5a5e69744f938e4b4f8ef5ff957286","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2021-03-17T23:13:25Z","title_canon_sha256":"ba474a72ba8441d6e913bcb2d25529c692dae88e38acfd584c31a0525d6e0976"},"schema_version":"1.0","source":{"id":"2103.09944","kind":"arxiv","version":1}},"canonical_sha256":"8775bd34786c1676115bf857af5232dd16c6b27c7d05e8283b098b0ff844743a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8775bd34786c1676115bf857af5232dd16c6b27c7d05e8283b098b0ff844743a","first_computed_at":"2026-07-05T02:24:15.223728Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:24:15.223728Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KbZt72GQU5E1BjHkW8H+eeBILA97GO3REDA9b3vFw82d3D6t/jGDnjvRj4Q5+35bCJMRXbZK2wyap2bjxsvsDA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:24:15.224155Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.09944","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c26bf81ecdbb4579f45bdcb46a394a85e6c6b251f8609bd65dc5e3070c057c4","sha256:a583d1c2926d696a6aca694bddfd134a8d30d619639415db43e8ad9c9b36700a"],"state_sha256":"7b663a0e688beb683959149582cff002578356f8a66ccb21f1242bfc9f38cfe9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q+9KinsTUBgXsYuwY0IxKwovMEUmTkHgfZ+UvNvWTmb5dhitM3aQ7kfaGAtpndG5THhTVQwuxeVxfBIQr77rCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T04:16:02.747245Z","bundle_sha256":"fcb88e1b462eea2294c26e1c6d0883043b018b171560d5234b55d6b2f53bc0f4"}}