{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZDHTNVL7XUQP4DVUEH5UTHFEMH","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":"ea22e6300cb9d3153274a4f660c595318283111fd8333cbc6732e5ba1cb57f20","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-01-11T15:22:55Z","title_canon_sha256":"2f8b456b4ccfc671eed958eade3d97635cab56f159f73244533ea99cf082c9c4"},"schema_version":"1.0","source":{"id":"2401.05975","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.05975","created_at":"2026-07-05T09:33:07Z"},{"alias_kind":"arxiv_version","alias_value":"2401.05975v5","created_at":"2026-07-05T09:33:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.05975","created_at":"2026-07-05T09:33:07Z"},{"alias_kind":"pith_short_12","alias_value":"ZDHTNVL7XUQP","created_at":"2026-07-05T09:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZDHTNVL7XUQP4DVU","created_at":"2026-07-05T09:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZDHTNVL7","created_at":"2026-07-05T09:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:71c8878d2b2ecf4cd436c90016df90962a4967276d35c090923b62fe1d45cbec","target":"graph","created_at":"2026-07-05T09:33:07Z","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/2401.05975/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Intent learning, which aims to learn users' intents for user understanding and item recommendation, has become a hot research spot in recent years. However, existing methods suffer from complex and cumbersome alternating optimization, limiting performance and scalability. To this end, we propose a novel intent learning method termed \\underline{ELCRec}, by unifying behavior representation learning into an \\underline{E}nd-to-end \\underline{L}earnable \\underline{C}lustering framework, for effective and efficient \\underline{Rec}ommendation. Concretely, we encode user behavior sequences and initial","authors_text":"Jian Ma, Jun Xia, Kejun Zhang, Shengju Yu, Shihao Zhu, Wenliang Zhong, Xinwang Liu, Yingwei Ma, Yue Liu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-01-11T15:22:55Z","title":"End-to-end Learnable Clustering for Intent Learning in Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.05975","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":"sha256:3e11b64868af0cbffabd6054b6e01ad7415cf7d2602f555649de0dbbbe6b9113","target":"record","created_at":"2026-07-05T09:33:07Z","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":"ea22e6300cb9d3153274a4f660c595318283111fd8333cbc6732e5ba1cb57f20","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2024-01-11T15:22:55Z","title_canon_sha256":"2f8b456b4ccfc671eed958eade3d97635cab56f159f73244533ea99cf082c9c4"},"schema_version":"1.0","source":{"id":"2401.05975","kind":"arxiv","version":5}},"canonical_sha256":"c8cf36d57fbd20fe0eb421fb499ca461c683959eed9725c05a43470ea6371b00","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c8cf36d57fbd20fe0eb421fb499ca461c683959eed9725c05a43470ea6371b00","first_computed_at":"2026-07-05T09:33:07.910003Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:33:07.910003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sX4xfexI8j6BR0VYtszg4l2uurxc/Te0dbKV4avCUKl2Z6teg3tKOU39yc4Q9WRaLK05JKajzZbuRIh0P70EDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:33:07.911094Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.05975","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e11b64868af0cbffabd6054b6e01ad7415cf7d2602f555649de0dbbbe6b9113","sha256:71c8878d2b2ecf4cd436c90016df90962a4967276d35c090923b62fe1d45cbec"],"state_sha256":"a514e8dd9c22856c94342b547a1752d5d99b596612f75b3fb98835d01f22e136"}