{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:ZYHJZL2HEWNQDWOBKVDMTPGLUO","short_pith_number":"pith:ZYHJZL2H","canonical_record":{"source":{"id":"1906.04386","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-11T04:29:07Z","cross_cats_sorted":["cs.IR","stat.ML"],"title_canon_sha256":"adca9d85ef829206255819fe9cf539740b34a22a7ece152cddba9f42bc655188","abstract_canon_sha256":"11ffd55fa6898514a937394e3ff285b74b27ba135f4b280efc70901affafa0d1"},"schema_version":"1.0"},"canonical_sha256":"ce0e9caf47259b01d9c15546c9bccba3bccd683e552c35c6500accc672916ca2","source":{"kind":"arxiv","id":"1906.04386","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.04386","created_at":"2026-05-17T23:43:39Z"},{"alias_kind":"arxiv_version","alias_value":"1906.04386v1","created_at":"2026-05-17T23:43:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.04386","created_at":"2026-05-17T23:43:39Z"},{"alias_kind":"pith_short_12","alias_value":"ZYHJZL2HEWNQ","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"ZYHJZL2HEWNQDWOB","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"ZYHJZL2H","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:ZYHJZL2HEWNQDWOBKVDMTPGLUO","target":"record","payload":{"canonical_record":{"source":{"id":"1906.04386","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-11T04:29:07Z","cross_cats_sorted":["cs.IR","stat.ML"],"title_canon_sha256":"adca9d85ef829206255819fe9cf539740b34a22a7ece152cddba9f42bc655188","abstract_canon_sha256":"11ffd55fa6898514a937394e3ff285b74b27ba135f4b280efc70901affafa0d1"},"schema_version":"1.0"},"canonical_sha256":"ce0e9caf47259b01d9c15546c9bccba3bccd683e552c35c6500accc672916ca2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:43:39.434993Z","signature_b64":"nW/WYe9AUZsLuAO+FF9upiFuINIdfPKdq68NNr4JLgu+OtxUxe6KUy5bXksu5C8SIzQ5IcpR0aZwy+HSfLPJDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce0e9caf47259b01d9c15546c9bccba3bccd683e552c35c6500accc672916ca2","last_reissued_at":"2026-05-17T23:43:39.434442Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:43:39.434442Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.04386","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":"2026-05-17T23:43:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QDF31QeDdDFUlF0OldrcN6dOT1/pKKZZE2KfiGJ0+fAVU6QAxI/ClTEpX0qoC5Bi3y9odzFTKJoTVx8unNHYAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T04:23:40.997465Z"},"content_sha256":"8d452e2f09e9f13f3c463f8a595fc0e05175d2abaa76bf6d74b683c3405a8616","schema_version":"1.0","event_id":"sha256:8d452e2f09e9f13f3c463f8a595fc0e05175d2abaa76bf6d74b683c3405a8616"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:ZYHJZL2HEWNQDWOBKVDMTPGLUO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Coupled Variational Recurrent Collaborative Filtering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Qingquan Song, Shiyu Chang, Xia Hu","submitted_at":"2019-06-11T04:29:07Z","abstract_excerpt":"We focus on the problem of streaming recommender system and explore novel collaborative filtering algorithms to handle the data dynamicity and complexity in a streaming manner. Although deep neural networks have demonstrated the effectiveness of recommendation tasks, it is lack of explorations on integrating probabilistic models and deep architectures under streaming recommendation settings. Conjoining the complementary advantages of probabilistic models and deep neural networks could enhance both model effectiveness and the understanding of inference uncertainties. To bridge the gap, in this "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.04386","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":""},"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":"2026-05-17T23:43:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u9Z7WFBNmB+unADBV0T28b35n2EzkJ1dnx+McAVcf0psN/B4EY4dX52mpcl0HgJ5rfElHH2byf9AMNm4+bDkAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T04:23:40.997946Z"},"content_sha256":"9ae4e2a15d812b7f563b7e635ff694bb7881704d1f535cefc0a0972b5be4f402","schema_version":"1.0","event_id":"sha256:9ae4e2a15d812b7f563b7e635ff694bb7881704d1f535cefc0a0972b5be4f402"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZYHJZL2HEWNQDWOBKVDMTPGLUO/bundle.json","state_url":"https://pith.science/pith/ZYHJZL2HEWNQDWOBKVDMTPGLUO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZYHJZL2HEWNQDWOBKVDMTPGLUO/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":"2026-05-25T04:23:40Z","links":{"resolver":"https://pith.science/pith/ZYHJZL2HEWNQDWOBKVDMTPGLUO","bundle":"https://pith.science/pith/ZYHJZL2HEWNQDWOBKVDMTPGLUO/bundle.json","state":"https://pith.science/pith/ZYHJZL2HEWNQDWOBKVDMTPGLUO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZYHJZL2HEWNQDWOBKVDMTPGLUO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZYHJZL2HEWNQDWOBKVDMTPGLUO","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":"11ffd55fa6898514a937394e3ff285b74b27ba135f4b280efc70901affafa0d1","cross_cats_sorted":["cs.IR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-11T04:29:07Z","title_canon_sha256":"adca9d85ef829206255819fe9cf539740b34a22a7ece152cddba9f42bc655188"},"schema_version":"1.0","source":{"id":"1906.04386","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.04386","created_at":"2026-05-17T23:43:39Z"},{"alias_kind":"arxiv_version","alias_value":"1906.04386v1","created_at":"2026-05-17T23:43:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.04386","created_at":"2026-05-17T23:43:39Z"},{"alias_kind":"pith_short_12","alias_value":"ZYHJZL2HEWNQ","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"ZYHJZL2HEWNQDWOB","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"ZYHJZL2H","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:9ae4e2a15d812b7f563b7e635ff694bb7881704d1f535cefc0a0972b5be4f402","target":"graph","created_at":"2026-05-17T23:43:39Z","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"},"paper":{"abstract_excerpt":"We focus on the problem of streaming recommender system and explore novel collaborative filtering algorithms to handle the data dynamicity and complexity in a streaming manner. Although deep neural networks have demonstrated the effectiveness of recommendation tasks, it is lack of explorations on integrating probabilistic models and deep architectures under streaming recommendation settings. Conjoining the complementary advantages of probabilistic models and deep neural networks could enhance both model effectiveness and the understanding of inference uncertainties. To bridge the gap, in this ","authors_text":"Qingquan Song, Shiyu Chang, Xia Hu","cross_cats":["cs.IR","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-11T04:29:07Z","title":"Coupled Variational Recurrent Collaborative Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.04386","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":"sha256:8d452e2f09e9f13f3c463f8a595fc0e05175d2abaa76bf6d74b683c3405a8616","target":"record","created_at":"2026-05-17T23:43:39Z","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":"11ffd55fa6898514a937394e3ff285b74b27ba135f4b280efc70901affafa0d1","cross_cats_sorted":["cs.IR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-11T04:29:07Z","title_canon_sha256":"adca9d85ef829206255819fe9cf539740b34a22a7ece152cddba9f42bc655188"},"schema_version":"1.0","source":{"id":"1906.04386","kind":"arxiv","version":1}},"canonical_sha256":"ce0e9caf47259b01d9c15546c9bccba3bccd683e552c35c6500accc672916ca2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ce0e9caf47259b01d9c15546c9bccba3bccd683e552c35c6500accc672916ca2","first_computed_at":"2026-05-17T23:43:39.434442Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:43:39.434442Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nW/WYe9AUZsLuAO+FF9upiFuINIdfPKdq68NNr4JLgu+OtxUxe6KUy5bXksu5C8SIzQ5IcpR0aZwy+HSfLPJDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:43:39.434993Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.04386","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d452e2f09e9f13f3c463f8a595fc0e05175d2abaa76bf6d74b683c3405a8616","sha256:9ae4e2a15d812b7f563b7e635ff694bb7881704d1f535cefc0a0972b5be4f402"],"state_sha256":"d3510e65c8fa46d98e5762c837d398898f0ee10b35fab355227020feab299847"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WUZ0xrJq6K0+kwAJaXzXQyCd5yGm3PhWf5E1WA+7TH5TGC8iKzLcEmAYDP/5zCFdIgjTRd+sk6mxmtx1mkz/Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T04:23:41.001289Z","bundle_sha256":"a2581df7555ae11eba1e2a1054a81cf8ee34b48fde05666905956f1775644a6e"}}