{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FONGVI2VUKM5WOEU3QSD2EHYSR","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":"2fdc30d75456e2379f36e83ab3aac18c9861b26cb9b561c7ba1226f0da129226","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-16T13:27:06Z","title_canon_sha256":"a1fd2ac357d297bbc67f2a0ea0f4b990b80af77dcfb9b86c57f09cee10ab53aa"},"schema_version":"1.0","source":{"id":"2506.21579","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21579","created_at":"2026-07-05T11:27:56Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21579v1","created_at":"2026-07-05T11:27:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21579","created_at":"2026-07-05T11:27:56Z"},{"alias_kind":"pith_short_12","alias_value":"FONGVI2VUKM5","created_at":"2026-07-05T11:27:56Z"},{"alias_kind":"pith_short_16","alias_value":"FONGVI2VUKM5WOEU","created_at":"2026-07-05T11:27:56Z"},{"alias_kind":"pith_short_8","alias_value":"FONGVI2V","created_at":"2026-07-05T11:27:56Z"}],"graph_snapshots":[{"event_id":"sha256:8c428aecff03bc40ce7e703938084e0206aed5e8269fb0f55782296efd51830a","target":"graph","created_at":"2026-07-05T11:27:56Z","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/2506.21579/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sequential recommendation aims to predict users' future interactions by modeling collaborative filtering (CF) signals from historical behaviors of similar users or items. Traditional sequential recommenders predominantly rely on ID-based embeddings, which capture CF signals through high-order co-occurrence patterns. However, these embeddings depend solely on past interactions, lacking transferable knowledge to generalize to unseen domains. Recent advances in large language models (LLMs) have motivated text-based recommendation approaches that derive item representations from textual descriptio","authors_text":"An Zhang, Tat-Seng Chua, Xiaohao Liu, Yingzhi He, Yunshan Ma","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-16T13:27:06Z","title":"LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21579","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":"sha256:33a0430331206cd36d3ba386d24893db363bc8dcfa08cfc31ad5170fb82d495a","target":"record","created_at":"2026-07-05T11:27:56Z","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":"2fdc30d75456e2379f36e83ab3aac18c9861b26cb9b561c7ba1226f0da129226","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-16T13:27:06Z","title_canon_sha256":"a1fd2ac357d297bbc67f2a0ea0f4b990b80af77dcfb9b86c57f09cee10ab53aa"},"schema_version":"1.0","source":{"id":"2506.21579","kind":"arxiv","version":1}},"canonical_sha256":"2b9a6aa355a299db3894dc243d10f894770e5a2f25198508ad1ad83d59e01712","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2b9a6aa355a299db3894dc243d10f894770e5a2f25198508ad1ad83d59e01712","first_computed_at":"2026-07-05T11:27:56.716867Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:27:56.716867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HjCNqxGJCJmizo2ElPh/KLW4ZJzgcjnvwP/XgVmeyKvMD8yWaJNbJKnQxi58iHXJMgsmY3Zfl8k9RASLT3bSAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:27:56.717411Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.21579","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:33a0430331206cd36d3ba386d24893db363bc8dcfa08cfc31ad5170fb82d495a","sha256:8c428aecff03bc40ce7e703938084e0206aed5e8269fb0f55782296efd51830a"],"state_sha256":"4fa4078e80e6e4695c90ddf61c8bc3f9e55eac5692c947b0bf4c3bdbb0c11dc1"}