{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UTKB2M5X2KAG6L6WDQNBKFWJAO","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":"e344f5385e4c772fcf36bf01b03b084fd921c25efab932b75425a7ac0c2bb3b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-18T20:35:03Z","title_canon_sha256":"b947a21dda4b481ce33f12b131e5667a52d1fbe5d31e77a9bf736d313037b2bd"},"schema_version":"1.0","source":{"id":"2501.10871","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.10871","created_at":"2026-07-05T10:02:59Z"},{"alias_kind":"arxiv_version","alias_value":"2501.10871v1","created_at":"2026-07-05T10:02:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.10871","created_at":"2026-07-05T10:02:59Z"},{"alias_kind":"pith_short_12","alias_value":"UTKB2M5X2KAG","created_at":"2026-07-05T10:02:59Z"},{"alias_kind":"pith_short_16","alias_value":"UTKB2M5X2KAG6L6W","created_at":"2026-07-05T10:02:59Z"},{"alias_kind":"pith_short_8","alias_value":"UTKB2M5X","created_at":"2026-07-05T10:02:59Z"}],"graph_snapshots":[{"event_id":"sha256:4cbc2613cd37fd64bc6390fa79574c331a358218e466fa3e66ae41c317487fc1","target":"graph","created_at":"2026-07-05T10:02:59Z","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/2501.10871/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recommendation systems play a critical role in enhancing user experience and engagement in various online platforms. Traditional methods, such as Collaborative Filtering (CF) and Content-Based Filtering (CBF), rely heavily on past user interactions or item features. However, these models often fail to capture the dynamic and evolving nature of user preferences. To address these limitations, we propose DUIP (Dynamic User Intent Prediction), a novel framework that combines LSTM networks with Large Language Models (LLMs) to dynamically capture user intent and generate personalized item recommenda","authors_text":"Jiani Wang, Peiyang Yu, Xiaochuan Xu, Zeqiu Xu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-18T20:35:03Z","title":"Enhancing User Intent for Recommendation Systems via Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.10871","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:a10091f102710d3edc575cde9400f5c75a90840eac6f6e2e17adf8ca497f5738","target":"record","created_at":"2026-07-05T10:02:59Z","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":"e344f5385e4c772fcf36bf01b03b084fd921c25efab932b75425a7ac0c2bb3b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-01-18T20:35:03Z","title_canon_sha256":"b947a21dda4b481ce33f12b131e5667a52d1fbe5d31e77a9bf736d313037b2bd"},"schema_version":"1.0","source":{"id":"2501.10871","kind":"arxiv","version":1}},"canonical_sha256":"a4d41d33b7d2806f2fd61c1a1516c903b8c8194e418b7ea866e803fe7ddd534e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a4d41d33b7d2806f2fd61c1a1516c903b8c8194e418b7ea866e803fe7ddd534e","first_computed_at":"2026-07-05T10:02:59.964014Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:02:59.964014Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"te0thYdlk4zJSSZprInqZ681UZSy3CT3Tf6N9wGnwr+7iBiXYkOw4gKSJjYgiNNlLWTL7vUkT4htSoLTcVl+Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:02:59.964501Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.10871","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a10091f102710d3edc575cde9400f5c75a90840eac6f6e2e17adf8ca497f5738","sha256:4cbc2613cd37fd64bc6390fa79574c331a358218e466fa3e66ae41c317487fc1"],"state_sha256":"eae920d6312446bfa354a7301a976f8671f5b2ea706fa0bfc50bc848bba5438b"}