{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:FUYSS4WWR5XOS2MYMAJ2LQKCO5","short_pith_number":"pith:FUYSS4WW","canonical_record":{"source":{"id":"2307.13494","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2023-07-25T13:42:22Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"c28a9cc478391d6e8e7369f5cc2b9feeab01c5d9c3ca68da5468c36e88602faf","abstract_canon_sha256":"9d4c56729e117211ea910d2947234808173bac2f58bdff0609f158776441e8e2"},"schema_version":"1.0"},"canonical_sha256":"2d312972d68f6ee969986013a5c142775f99a210b8484c926f959abc5c819dad","source":{"kind":"arxiv","id":"2307.13494","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.13494","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"arxiv_version","alias_value":"2307.13494v5","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.13494","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"pith_short_12","alias_value":"FUYSS4WWR5XO","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"pith_short_16","alias_value":"FUYSS4WWR5XOS2MY","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"pith_short_8","alias_value":"FUYSS4WW","created_at":"2026-07-05T07:18:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:FUYSS4WWR5XOS2MYMAJ2LQKCO5","target":"record","payload":{"canonical_record":{"source":{"id":"2307.13494","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2023-07-25T13:42:22Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"c28a9cc478391d6e8e7369f5cc2b9feeab01c5d9c3ca68da5468c36e88602faf","abstract_canon_sha256":"9d4c56729e117211ea910d2947234808173bac2f58bdff0609f158776441e8e2"},"schema_version":"1.0"},"canonical_sha256":"2d312972d68f6ee969986013a5c142775f99a210b8484c926f959abc5c819dad","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:18:59.229133Z","signature_b64":"XkmSXjY3/UMHtHqOJZijeBVZB0TPoE33HMCId3Ezj6Sg+au3i/rxxUL6r2azxssFE1PdKYn0pqZs41+UPLEABw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2d312972d68f6ee969986013a5c142775f99a210b8484c926f959abc5c819dad","last_reissued_at":"2026-07-05T07:18:59.228680Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:18:59.228680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.13494","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:18:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BFpaPdXJBoX1aRuK/ewkudE08KE6+bYz/4qkKTkkfMz+OhEii9qkclbKWkV/13GhQojLi4+mjoX6ON+Ub86vDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T01:26:56.631737Z"},"content_sha256":"4f8b57fb1cdeb5704495124c171422e14cdcb92221d3ac17162029979f78b1c4","schema_version":"1.0","event_id":"sha256:4f8b57fb1cdeb5704495124c171422e14cdcb92221d3ac17162029979f78b1c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:FUYSS4WWR5XOS2MYMAJ2LQKCO5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Duet: efficient and scalable hybriD neUral rElation undersTanding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.DB","authors_text":"Chang Shu, Donghua Yang, Hongzhi Wang, Kaixin Zhang, Yabin Lu, Yu Yan, Ziqi Li","submitted_at":"2023-07-25T13:42:22Z","abstract_excerpt":"Learned cardinality estimation methods have achieved high precision compared to traditional methods. Among learned methods, query-driven approaches have faced the workload drift problem for a long time. Although both data-driven and hybrid methods are proposed to avoid this problem, most of them suffer from high training and estimation costs, limited scalability, instability, and long-tail distribution problems on high-dimensional tables, which seriously affects the practical application of learned cardinality estimators. In this paper, we prove that most of these problems are directly caused "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.13494","kind":"arxiv","version":5},"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/2307.13494/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":"2026-07-05T07:18:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"28uPCs+Cih6RhGOXj39US6chzO8GfpMSJig77zJSillU9FB1Z1TozYL4SsSXsY2Smg9l4kwmvqEv7rIZF67UCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T01:26:56.632100Z"},"content_sha256":"5c14827457c00572be08013507ba658764629068a7e421904926d2d2bfbf6d3a","schema_version":"1.0","event_id":"sha256:5c14827457c00572be08013507ba658764629068a7e421904926d2d2bfbf6d3a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FUYSS4WWR5XOS2MYMAJ2LQKCO5/bundle.json","state_url":"https://pith.science/pith/FUYSS4WWR5XOS2MYMAJ2LQKCO5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FUYSS4WWR5XOS2MYMAJ2LQKCO5/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":"2026-07-17T01:26:56Z","links":{"resolver":"https://pith.science/pith/FUYSS4WWR5XOS2MYMAJ2LQKCO5","bundle":"https://pith.science/pith/FUYSS4WWR5XOS2MYMAJ2LQKCO5/bundle.json","state":"https://pith.science/pith/FUYSS4WWR5XOS2MYMAJ2LQKCO5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FUYSS4WWR5XOS2MYMAJ2LQKCO5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:FUYSS4WWR5XOS2MYMAJ2LQKCO5","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":"9d4c56729e117211ea910d2947234808173bac2f58bdff0609f158776441e8e2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2023-07-25T13:42:22Z","title_canon_sha256":"c28a9cc478391d6e8e7369f5cc2b9feeab01c5d9c3ca68da5468c36e88602faf"},"schema_version":"1.0","source":{"id":"2307.13494","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.13494","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"arxiv_version","alias_value":"2307.13494v5","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.13494","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"pith_short_12","alias_value":"FUYSS4WWR5XO","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"pith_short_16","alias_value":"FUYSS4WWR5XOS2MY","created_at":"2026-07-05T07:18:59Z"},{"alias_kind":"pith_short_8","alias_value":"FUYSS4WW","created_at":"2026-07-05T07:18:59Z"}],"graph_snapshots":[{"event_id":"sha256:5c14827457c00572be08013507ba658764629068a7e421904926d2d2bfbf6d3a","target":"graph","created_at":"2026-07-05T07:18:59Z","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/2307.13494/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learned cardinality estimation methods have achieved high precision compared to traditional methods. Among learned methods, query-driven approaches have faced the workload drift problem for a long time. Although both data-driven and hybrid methods are proposed to avoid this problem, most of them suffer from high training and estimation costs, limited scalability, instability, and long-tail distribution problems on high-dimensional tables, which seriously affects the practical application of learned cardinality estimators. In this paper, we prove that most of these problems are directly caused ","authors_text":"Chang Shu, Donghua Yang, Hongzhi Wang, Kaixin Zhang, Yabin Lu, Yu Yan, Ziqi Li","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2023-07-25T13:42:22Z","title":"Duet: efficient and scalable hybriD neUral rElation undersTanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.13494","kind":"arxiv","version":5},"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":"sha256:4f8b57fb1cdeb5704495124c171422e14cdcb92221d3ac17162029979f78b1c4","target":"record","created_at":"2026-07-05T07:18:59Z","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":"9d4c56729e117211ea910d2947234808173bac2f58bdff0609f158776441e8e2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2023-07-25T13:42:22Z","title_canon_sha256":"c28a9cc478391d6e8e7369f5cc2b9feeab01c5d9c3ca68da5468c36e88602faf"},"schema_version":"1.0","source":{"id":"2307.13494","kind":"arxiv","version":5}},"canonical_sha256":"2d312972d68f6ee969986013a5c142775f99a210b8484c926f959abc5c819dad","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d312972d68f6ee969986013a5c142775f99a210b8484c926f959abc5c819dad","first_computed_at":"2026-07-05T07:18:59.228680Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:18:59.228680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XkmSXjY3/UMHtHqOJZijeBVZB0TPoE33HMCId3Ezj6Sg+au3i/rxxUL6r2azxssFE1PdKYn0pqZs41+UPLEABw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:18:59.229133Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.13494","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4f8b57fb1cdeb5704495124c171422e14cdcb92221d3ac17162029979f78b1c4","sha256:5c14827457c00572be08013507ba658764629068a7e421904926d2d2bfbf6d3a"],"state_sha256":"5b489fcb446224c815efcd7146fff9202f7e29365879e7b0a50086c371f1e681"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4U1nX4P6DyTAgou5zYZLcevbGpibgQwVrZTDJJh1v6N+qxCnwoxSLTCJHOCCUAoSwmU9xZ4zUcIZlcXJ5lpyDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-17T01:26:56.634183Z","bundle_sha256":"7b633e70d5605ecff54442a135e765c68c890c62c7417a92fcba1c6070fd9166"}}