{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:VFCRL7R6DHKUCG3ZS7HGFFJRGW","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":"e62c23d7950bf68d36a2894c7b44fc05da6c9025790fa8df82ccfc29aac0e2dc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-02-14T07:55:57Z","title_canon_sha256":"892f3c0fbd7c279b190e8320acce86cd57523a3ccbbfc17c29a2ecf5811afcd3"},"schema_version":"1.0","source":{"id":"2202.10226","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.10226","created_at":"2026-07-05T04:00:23Z"},{"alias_kind":"arxiv_version","alias_value":"2202.10226v2","created_at":"2026-07-05T04:00:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.10226","created_at":"2026-07-05T04:00:23Z"},{"alias_kind":"pith_short_12","alias_value":"VFCRL7R6DHKU","created_at":"2026-07-05T04:00:23Z"},{"alias_kind":"pith_short_16","alias_value":"VFCRL7R6DHKUCG3Z","created_at":"2026-07-05T04:00:23Z"},{"alias_kind":"pith_short_8","alias_value":"VFCRL7R6","created_at":"2026-07-05T04:00:23Z"}],"graph_snapshots":[{"event_id":"sha256:5a61b86e4e73ce842a90bf4f63e59ee84f876d869b7273c3085eda13bb2194c4","target":"graph","created_at":"2026-07-05T04:00:23Z","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/2202.10226/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model-based methods for recommender systems have been studied extensively for years. Modern recommender systems usually resort to 1) representation learning models which define user-item preference as the distance between their embedding representations, and 2) embedding-based Approximate Nearest Neighbor (ANN) search to tackle the efficiency problem introduced by large-scale corpus. While providing efficient retrieval, the embedding-based retrieval pattern also limits the model capacity since the form of user-item preference measure is restricted to the distance between their embedding repres","authors_text":"Bin Liu, Bo Zheng, Buting Ma, Han Zhu, Hongbo Deng, Jun Jiang, Qi Li, Qingbo Hua, Rihan Chen, Yaoxuan Wang, Yunlong Xu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-02-14T07:55:57Z","title":"Approximate Nearest Neighbor Search under Neural Similarity Metric for Large-Scale Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.10226","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":"sha256:42adb062b3fae9a0ff4debc907edac29b4942a12364e429be7b11745c1a741c1","target":"record","created_at":"2026-07-05T04:00:23Z","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":"e62c23d7950bf68d36a2894c7b44fc05da6c9025790fa8df82ccfc29aac0e2dc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-02-14T07:55:57Z","title_canon_sha256":"892f3c0fbd7c279b190e8320acce86cd57523a3ccbbfc17c29a2ecf5811afcd3"},"schema_version":"1.0","source":{"id":"2202.10226","kind":"arxiv","version":2}},"canonical_sha256":"a94515fe3e19d5411b7997ce62953135a7b0ea47ee373a35d9a868630b5b59d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a94515fe3e19d5411b7997ce62953135a7b0ea47ee373a35d9a868630b5b59d4","first_computed_at":"2026-07-05T04:00:23.084578Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:00:23.084578Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6H4N17LOQN0Whu8sK48ybxpvFtjZjCSfTgASdH3DRwUz61iF7hJqC8yd/PP1qsif003HBANHUj5yLAgMxaRZBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:00:23.085014Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.10226","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:42adb062b3fae9a0ff4debc907edac29b4942a12364e429be7b11745c1a741c1","sha256:5a61b86e4e73ce842a90bf4f63e59ee84f876d869b7273c3085eda13bb2194c4"],"state_sha256":"cf2df3a5c2dcb4b5efe9a770cc5b0321d2f782a40e200becf35438f4d9f4ce99"}