{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DCECIQDN7AR56XYTRY5QUUDVPV","short_pith_number":"pith:DCECIQDN","canonical_record":{"source":{"id":"2607.25329","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-07-28T06:27:33Z","cross_cats_sorted":[],"title_canon_sha256":"5f5a6e76f69e4037ca20d47c73280eca2c06a62f9549c58c21fa922bb0fc5d7e","abstract_canon_sha256":"8f118523048770dddab18f309dac37589d92d2cf2e9f3f12b82c3f55e0662d28"},"schema_version":"1.0"},"canonical_sha256":"188824406df823df5f138e3b0a50757d4bc9f975be15c8a4f3a1012c2d46ee99","source":{"kind":"arxiv","id":"2607.25329","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.25329","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"arxiv_version","alias_value":"2607.25329v1","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.25329","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"pith_short_12","alias_value":"DCECIQDN7AR5","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"pith_short_16","alias_value":"DCECIQDN7AR56XYT","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"pith_short_8","alias_value":"DCECIQDN","created_at":"2026-07-29T01:25:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DCECIQDN7AR56XYTRY5QUUDVPV","target":"record","payload":{"canonical_record":{"source":{"id":"2607.25329","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-07-28T06:27:33Z","cross_cats_sorted":[],"title_canon_sha256":"5f5a6e76f69e4037ca20d47c73280eca2c06a62f9549c58c21fa922bb0fc5d7e","abstract_canon_sha256":"8f118523048770dddab18f309dac37589d92d2cf2e9f3f12b82c3f55e0662d28"},"schema_version":"1.0"},"canonical_sha256":"188824406df823df5f138e3b0a50757d4bc9f975be15c8a4f3a1012c2d46ee99","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-29T01:25:09.507013Z","signature_b64":"+mQVvyMSciMxpVoiyR1uPdU1tQG3S7os9sbzXuUKauNVggk5yxCW945k3xNhw7obiiDZps6oVXyhWuVdcIlCBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"188824406df823df5f138e3b0a50757d4bc9f975be15c8a4f3a1012c2d46ee99","last_reissued_at":"2026-07-29T01:25:09.506205Z","signature_status":"signed_v1","first_computed_at":"2026-07-29T01:25:09.506205Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.25329","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":"2026-07-29T01:25:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KW5mhyv9vLcPzztuDFU7VH3+UtVZAFL+4fzZA6NXtfFrThA2DV86gVtpwV0zM/SThWPHUNuRX2bNfkD7iBhoDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:43:24.106143Z"},"content_sha256":"41139753f0cbef2f1b873ddba112f524ac9c74ea778bc5135e32b865ef515288","schema_version":"1.0","event_id":"sha256:41139753f0cbef2f1b873ddba112f524ac9c74ea778bc5135e32b865ef515288"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DCECIQDN7AR56XYTRY5QUUDVPV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Grevo: A Unified Generative Recommendation Framework with Evolutionary Item Indexing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Honghui Bao, Hongwei Zhang, Huanjie Wang, Liwei Guan, Zekai Sun","submitted_at":"2026-07-28T06:27:33Z","abstract_excerpt":"Generative recommendation has recently emerged as a promising paradigm that reformulates retrieval as autoregressive generation over semantic identifiers (SIDs), achieving strong performance and drawing increasing attention as an alternative to matching. Despite this progress, SIDs are typically frozen by a content-based tokenizer before the recommender is trained, leaving a persistent gap between what best reconstructs an item's content and what a recommender can predict from user behavior. Recent end-to-end methods close this gap by jointly training the tokenizer and the recommender, but cou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.25329","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/2607.25329/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":"2026-07-29T01:25:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c5xpQloQ9kskuBsxDJe3qzdex7x01PltTXOUgGODpsnh8K8/vhajakxGXcPdZ1DZDnbXYGV3zGRMKkEd2duWDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:43:24.106723Z"},"content_sha256":"1a462559af413243577687f0d3dab221f19ff10c49d67c9615d3bc4a329a7acd","schema_version":"1.0","event_id":"sha256:1a462559af413243577687f0d3dab221f19ff10c49d67c9615d3bc4a329a7acd"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:DCECIQDN7AR56XYTRY5QUUDVPV","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1109/TPAMI.2018.2889473) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Yury A. Malkov and Dmitry A. Yashunin. 2020. Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs.IEEE Trans. Pattern Anal. Mach. Intell.42, 4 (2020), 824–836. doi:10.1109/TPAMI.2018. 2889","arxiv_id":"2607.25329","detector":"doi_compliance","evidence":{"ref_index":15,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"10.1109/tpami.2018","reconstructed_doi":"10.1109/TPAMI.2018.2889473"},"severity":"advisory","ref_index":15,"audited_at":"2026-08-01T02:52:37.132474Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/TPAMI.2018.2889473","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"f41b9b344009c033df328a2b54a5f2f717958c7c5fcab0e84ee272e28d236587","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":14958,"payload_sha256":"f3beebbdafe6378efc9e5a14efbb4a013773edf7a19336da36932680b8ce7871","signature_b64":"yJNC6nytdCEAYio1krMUMufgCJAhVxbXr0tT1CLJnF+Z2ROAmWpEEZfocXmGc+OMNnKbnKKjtQHftwnxVrpzCA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-01T02:56:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nE3j3iHM+o4Z258Tes67e4hy85q5Azp5S5UqKI5/TvobtvMTwTaiX/KROqsFQnQgg9qnJMfo+NipA4b7qqNvCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:43:24.110155Z"},"content_sha256":"f624a943c492bcc451a34314c68882bec1bc594dff237ebf0dbbae464763c9aa","schema_version":"1.0","event_id":"sha256:f624a943c492bcc451a34314c68882bec1bc594dff237ebf0dbbae464763c9aa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DCECIQDN7AR56XYTRY5QUUDVPV/bundle.json","state_url":"https://pith.science/pith/DCECIQDN7AR56XYTRY5QUUDVPV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DCECIQDN7AR56XYTRY5QUUDVPV/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":"2026-08-04T06:43:24Z","links":{"resolver":"https://pith.science/pith/DCECIQDN7AR56XYTRY5QUUDVPV","bundle":"https://pith.science/pith/DCECIQDN7AR56XYTRY5QUUDVPV/bundle.json","state":"https://pith.science/pith/DCECIQDN7AR56XYTRY5QUUDVPV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DCECIQDN7AR56XYTRY5QUUDVPV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DCECIQDN7AR56XYTRY5QUUDVPV","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8f118523048770dddab18f309dac37589d92d2cf2e9f3f12b82c3f55e0662d28","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-07-28T06:27:33Z","title_canon_sha256":"5f5a6e76f69e4037ca20d47c73280eca2c06a62f9549c58c21fa922bb0fc5d7e"},"schema_version":"1.0","source":{"id":"2607.25329","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.25329","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"arxiv_version","alias_value":"2607.25329v1","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.25329","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"pith_short_12","alias_value":"DCECIQDN7AR5","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"pith_short_16","alias_value":"DCECIQDN7AR56XYT","created_at":"2026-07-29T01:25:09Z"},{"alias_kind":"pith_short_8","alias_value":"DCECIQDN","created_at":"2026-07-29T01:25:09Z"}],"graph_snapshots":[{"event_id":"sha256:1a462559af413243577687f0d3dab221f19ff10c49d67c9615d3bc4a329a7acd","target":"graph","created_at":"2026-07-29T01:25:09Z","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/2607.25329/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative recommendation has recently emerged as a promising paradigm that reformulates retrieval as autoregressive generation over semantic identifiers (SIDs), achieving strong performance and drawing increasing attention as an alternative to matching. Despite this progress, SIDs are typically frozen by a content-based tokenizer before the recommender is trained, leaving a persistent gap between what best reconstructs an item's content and what a recommender can predict from user behavior. Recent end-to-end methods close this gap by jointly training the tokenizer and the recommender, but cou","authors_text":"Honghui Bao, Hongwei Zhang, Huanjie Wang, Liwei Guan, Zekai Sun","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-07-28T06:27:33Z","title":"Grevo: A Unified Generative Recommendation Framework with Evolutionary Item Indexing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.25329","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":"sha256:41139753f0cbef2f1b873ddba112f524ac9c74ea778bc5135e32b865ef515288","target":"record","created_at":"2026-07-29T01:25:09Z","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":"8f118523048770dddab18f309dac37589d92d2cf2e9f3f12b82c3f55e0662d28","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-07-28T06:27:33Z","title_canon_sha256":"5f5a6e76f69e4037ca20d47c73280eca2c06a62f9549c58c21fa922bb0fc5d7e"},"schema_version":"1.0","source":{"id":"2607.25329","kind":"arxiv","version":1}},"canonical_sha256":"188824406df823df5f138e3b0a50757d4bc9f975be15c8a4f3a1012c2d46ee99","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"188824406df823df5f138e3b0a50757d4bc9f975be15c8a4f3a1012c2d46ee99","first_computed_at":"2026-07-29T01:25:09.506205Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-29T01:25:09.506205Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+mQVvyMSciMxpVoiyR1uPdU1tQG3S7os9sbzXuUKauNVggk5yxCW945k3xNhw7obiiDZps6oVXyhWuVdcIlCBg==","signature_status":"signed_v1","signed_at":"2026-07-29T01:25:09.507013Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.25329","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:41139753f0cbef2f1b873ddba112f524ac9c74ea778bc5135e32b865ef515288","sha256:1a462559af413243577687f0d3dab221f19ff10c49d67c9615d3bc4a329a7acd","sha256:f624a943c492bcc451a34314c68882bec1bc594dff237ebf0dbbae464763c9aa"],"state_sha256":"87660178c35298ed0abc4d95c24984bb88413074c0d2b09a37b4e87baeddd505"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lzUhdzAUcdv1mgc19Z+/VDaXPp77CxG573iEbZwrvVbO1XMUEG7og7OoBbUr1AOqxKDga5+Uq9bE04Rt/9WJAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T06:43:24.112360Z","bundle_sha256":"07ae85ac6805d0669bab8c14ccc7c39be1800967b9b1981811a5378094e51787"}}