{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:32UUEQARLAA3EG4KOUYACN7XOF","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":"988508d76c75e4ad4d6612318c1902aa90af932d0fb97aa472bb0a7476221c70","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-09T19:48:33Z","title_canon_sha256":"9a8cfacbb7ba6ec1d449ac0c1456e51103c157f0f7323c8922c01ade03efc51c"},"schema_version":"1.0","source":{"id":"2507.07251","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.07251","created_at":"2026-07-05T11:34:34Z"},{"alias_kind":"arxiv_version","alias_value":"2507.07251v1","created_at":"2026-07-05T11:34:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.07251","created_at":"2026-07-05T11:34:34Z"},{"alias_kind":"pith_short_12","alias_value":"32UUEQARLAA3","created_at":"2026-07-05T11:34:34Z"},{"alias_kind":"pith_short_16","alias_value":"32UUEQARLAA3EG4K","created_at":"2026-07-05T11:34:34Z"},{"alias_kind":"pith_short_8","alias_value":"32UUEQAR","created_at":"2026-07-05T11:34:34Z"}],"graph_snapshots":[{"event_id":"sha256:35ea6695094642ec9ab43de0af2dddbd92abb43e4e525213091324fdf7e1f661","target":"graph","created_at":"2026-07-05T11:34:34Z","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/2507.07251/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditional recommendation algorithms are not designed to provide personalized recommendations based on user preferences provided through text, e.g., \"I enjoy light-hearted comedies with a lot of humor\". Large Language Models (LLMs) have emerged as one of the most promising tools for natural language processing in recent years. This research proposes a novel framework that mimics how a close friend would recommend items based on their knowledge of an individual's tastes. We leverage LLMs to enhance movie recommendation systems by refining traditional algorithm outputs and integrating them with","authors_text":"Aaron Goldstein, Ayan Dutta","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-09T19:48:33Z","title":"A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.07251","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":"sha256:65fabf84d5983639075ba2b9d0ef1dd9eefd1235c762817df1fef9f184b3d08a","target":"record","created_at":"2026-07-05T11:34:34Z","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":"988508d76c75e4ad4d6612318c1902aa90af932d0fb97aa472bb0a7476221c70","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-07-09T19:48:33Z","title_canon_sha256":"9a8cfacbb7ba6ec1d449ac0c1456e51103c157f0f7323c8922c01ade03efc51c"},"schema_version":"1.0","source":{"id":"2507.07251","kind":"arxiv","version":1}},"canonical_sha256":"dea94240115801b21b8a75300137f7716ee168f63394f0100e055c1271a8f91c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dea94240115801b21b8a75300137f7716ee168f63394f0100e055c1271a8f91c","first_computed_at":"2026-07-05T11:34:34.212945Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:34:34.212945Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/7w3o+W0s5bHaCkkv2URSPWR23dij2DVrrIFq1lq/bu04sgsGd/HiB7wJ4fPT6uVQ7+1yXuwIwimHcJU8HtsAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:34:34.213335Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.07251","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:65fabf84d5983639075ba2b9d0ef1dd9eefd1235c762817df1fef9f184b3d08a","sha256:35ea6695094642ec9ab43de0af2dddbd92abb43e4e525213091324fdf7e1f661"],"state_sha256":"ea26b6b442425bbc1b2a2cacbecac934a37d55c0017115444f388861a2f51adf"}