{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:7FLN57VKDNYB35QBLWRWPKGHOI","short_pith_number":"pith:7FLN57VK","canonical_record":{"source":{"id":"2209.00456","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2022-08-27T03:35:00Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1dc088add805cee0a95b4c12a30a48a5fea44065e859b6980454b4a8b68c353f","abstract_canon_sha256":"858f14de4869a4e9dd4b63e1d3ddba1c992ca376d8098463b5332acacab2e843"},"schema_version":"1.0"},"canonical_sha256":"f956defeaa1b701df6015da367a8c772111f258d57317cfb6c9bf257ba744773","source":{"kind":"arxiv","id":"2209.00456","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.00456","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"arxiv_version","alias_value":"2209.00456v2","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.00456","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"pith_short_12","alias_value":"7FLN57VKDNYB","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"pith_short_16","alias_value":"7FLN57VKDNYB35QB","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"pith_short_8","alias_value":"7FLN57VK","created_at":"2026-07-05T05:22:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:7FLN57VKDNYB35QBLWRWPKGHOI","target":"record","payload":{"canonical_record":{"source":{"id":"2209.00456","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2022-08-27T03:35:00Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1dc088add805cee0a95b4c12a30a48a5fea44065e859b6980454b4a8b68c353f","abstract_canon_sha256":"858f14de4869a4e9dd4b63e1d3ddba1c992ca376d8098463b5332acacab2e843"},"schema_version":"1.0"},"canonical_sha256":"f956defeaa1b701df6015da367a8c772111f258d57317cfb6c9bf257ba744773","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:22:10.298149Z","signature_b64":"IESIfuaHUPfK6wrCYLgc2ctKl6LlOcIMpJiWYtx0S5KqFK2aaXmhtOpVknKPyuTdso58x0oLFxEuSGvyP/HVBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f956defeaa1b701df6015da367a8c772111f258d57317cfb6c9bf257ba744773","last_reissued_at":"2026-07-05T05:22:10.297619Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:22:10.297619Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.00456","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:22:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"erp+vClmRQS9LN++YgiUpw2OQ88EmdOpA+U/781OSdyXQxYSWVtIYlLBwHRbYo9HHQv+7wOoiehTfapsndTmAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T14:18:30.924974Z"},"content_sha256":"60a5c8ca387c377d460ddf2f2107d48735b754f74549d8d68700d57bf16b9124","schema_version":"1.0","event_id":"sha256:60a5c8ca387c377d460ddf2f2107d48735b754f74549d8d68700d57bf16b9124"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:7FLN57VKDNYB35QBLWRWPKGHOI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Hengrui Zhang, Liangwei Yang, Philip S. Yu, Yu Wang, Zhiwei Liu","submitted_at":"2022-08-27T03:35:00Z","abstract_excerpt":"Aiming at exploiting the rich information in user behaviour sequences, sequential recommendation has been widely adopted in real-world recommender systems. However, current methods suffer from the following issues: 1) sparsity of user-item interactions, 2) uncertainty of sequential records, 3) long-tail items. In this paper, we propose to incorporate contrastive learning into the framework of Variational AutoEncoders to address these challenges simultaneously. Firstly, we introduce ContrastELBO, a novel training objective that extends the conventional single-view ELBO to two-view case and theo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.00456","kind":"arxiv","version":2},"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/2209.00456/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":"2026-07-05T05:22:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SFn8kPmoTnZcQ3TI3a+0Uu06BSdak7/WT4855FYYU3rlwLRGO3LpkkPo7pD/H49MWwWKWn0gNt9SnL6rdRXfBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T14:18:30.925485Z"},"content_sha256":"90b6cedaf671d2c2d4bcac573986bfcd291ebe52aa09c591b1c4e5960dcda458","schema_version":"1.0","event_id":"sha256:90b6cedaf671d2c2d4bcac573986bfcd291ebe52aa09c591b1c4e5960dcda458"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7FLN57VKDNYB35QBLWRWPKGHOI/bundle.json","state_url":"https://pith.science/pith/7FLN57VKDNYB35QBLWRWPKGHOI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7FLN57VKDNYB35QBLWRWPKGHOI/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":"2026-08-20T14:18:30Z","links":{"resolver":"https://pith.science/pith/7FLN57VKDNYB35QBLWRWPKGHOI","bundle":"https://pith.science/pith/7FLN57VKDNYB35QBLWRWPKGHOI/bundle.json","state":"https://pith.science/pith/7FLN57VKDNYB35QBLWRWPKGHOI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7FLN57VKDNYB35QBLWRWPKGHOI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:7FLN57VKDNYB35QBLWRWPKGHOI","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":"858f14de4869a4e9dd4b63e1d3ddba1c992ca376d8098463b5332acacab2e843","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2022-08-27T03:35:00Z","title_canon_sha256":"1dc088add805cee0a95b4c12a30a48a5fea44065e859b6980454b4a8b68c353f"},"schema_version":"1.0","source":{"id":"2209.00456","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.00456","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"arxiv_version","alias_value":"2209.00456v2","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.00456","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"pith_short_12","alias_value":"7FLN57VKDNYB","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"pith_short_16","alias_value":"7FLN57VKDNYB35QB","created_at":"2026-07-05T05:22:10Z"},{"alias_kind":"pith_short_8","alias_value":"7FLN57VK","created_at":"2026-07-05T05:22:10Z"}],"graph_snapshots":[{"event_id":"sha256:90b6cedaf671d2c2d4bcac573986bfcd291ebe52aa09c591b1c4e5960dcda458","target":"graph","created_at":"2026-07-05T05:22:10Z","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/2209.00456/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Aiming at exploiting the rich information in user behaviour sequences, sequential recommendation has been widely adopted in real-world recommender systems. However, current methods suffer from the following issues: 1) sparsity of user-item interactions, 2) uncertainty of sequential records, 3) long-tail items. In this paper, we propose to incorporate contrastive learning into the framework of Variational AutoEncoders to address these challenges simultaneously. Firstly, we introduce ContrastELBO, a novel training objective that extends the conventional single-view ELBO to two-view case and theo","authors_text":"Hengrui Zhang, Liangwei Yang, Philip S. Yu, Yu Wang, Zhiwei Liu","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2022-08-27T03:35:00Z","title":"ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.00456","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":"sha256:60a5c8ca387c377d460ddf2f2107d48735b754f74549d8d68700d57bf16b9124","target":"record","created_at":"2026-07-05T05:22:10Z","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":"858f14de4869a4e9dd4b63e1d3ddba1c992ca376d8098463b5332acacab2e843","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2022-08-27T03:35:00Z","title_canon_sha256":"1dc088add805cee0a95b4c12a30a48a5fea44065e859b6980454b4a8b68c353f"},"schema_version":"1.0","source":{"id":"2209.00456","kind":"arxiv","version":2}},"canonical_sha256":"f956defeaa1b701df6015da367a8c772111f258d57317cfb6c9bf257ba744773","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f956defeaa1b701df6015da367a8c772111f258d57317cfb6c9bf257ba744773","first_computed_at":"2026-07-05T05:22:10.297619Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:22:10.297619Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IESIfuaHUPfK6wrCYLgc2ctKl6LlOcIMpJiWYtx0S5KqFK2aaXmhtOpVknKPyuTdso58x0oLFxEuSGvyP/HVBA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:22:10.298149Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.00456","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:60a5c8ca387c377d460ddf2f2107d48735b754f74549d8d68700d57bf16b9124","sha256:90b6cedaf671d2c2d4bcac573986bfcd291ebe52aa09c591b1c4e5960dcda458"],"state_sha256":"b5d723b696d2ce6c82e30bc28ba71945dfba557bba7fc8b818f3727d9a97c7b4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I7dLYkSxfWe3PBoWYIWv0siaNjH0yUb1LD2me13MR7acOlnBixrd3+fFgvLZYfY/vrPPahg9I0H66QtX4WwJAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T14:18:30.928342Z","bundle_sha256":"c435de9e8366bccb894634125ff7e90c3b53dddc054796909d6780f183aecd85"}}