{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:V3NE6BBVJFIUCWB6YSPU7IDPX5","short_pith_number":"pith:V3NE6BBV","schema_version":"1.0","canonical_sha256":"aeda4f0435495141583ec49f4fa06fbf7f6e778230c48f037cb92229250c03f9","source":{"kind":"arxiv","id":"2506.01673","version":1},"attestation_state":"computed","paper":{"title":"GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.IR","authors_text":"Eunseong Choi, Hye-Young Kim, Jongwuk Lee, Minjin Choi, Sunkyung Lee","submitted_at":"2025-06-02T13:42:46Z","abstract_excerpt":"Generative recommendation is an emerging paradigm that leverages the extensive knowledge of large language models by formulating recommendations into a text-to-text generation task. However, existing studies face two key limitations in (i) incorporating implicit item relationships and (ii) utilizing rich yet lengthy item information. To address these challenges, we propose a Generative Recommender via semantic-Aware Multi-granular late fusion (GRAM), introducing two synergistic innovations. First, we design semantic-to-lexical translation to encode implicit hierarchical and collaborative item "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.01673","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2025-06-02T13:42:46Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"c43912a60bc16da69220e83e4663f20fd0017a586a58df5eaa4bf6e84e090e79","abstract_canon_sha256":"18c2d5d9252477fcb86d772db17ed63a1df469f74c6e76186355a263988058c6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:14:17.687275Z","signature_b64":"zfyGWBJL+54jQU7lRWtEbAuC8VXLSdh8mHEeOkqymc3g3gw4fDb31gLt9G7EETu2sILT3r2dD7wXDa22y84NCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aeda4f0435495141583ec49f4fa06fbf7f6e778230c48f037cb92229250c03f9","last_reissued_at":"2026-07-05T11:14:17.686822Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:14:17.686822Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.IR","authors_text":"Eunseong Choi, Hye-Young Kim, Jongwuk Lee, Minjin Choi, Sunkyung Lee","submitted_at":"2025-06-02T13:42:46Z","abstract_excerpt":"Generative recommendation is an emerging paradigm that leverages the extensive knowledge of large language models by formulating recommendations into a text-to-text generation task. However, existing studies face two key limitations in (i) incorporating implicit item relationships and (ii) utilizing rich yet lengthy item information. To address these challenges, we propose a Generative Recommender via semantic-Aware Multi-granular late fusion (GRAM), introducing two synergistic innovations. First, we design semantic-to-lexical translation to encode implicit hierarchical and collaborative item "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01673","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2506.01673/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.01673","created_at":"2026-07-05T11:14:17.686878+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.01673v1","created_at":"2026-07-05T11:14:17.686878+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01673","created_at":"2026-07-05T11:14:17.686878+00:00"},{"alias_kind":"pith_short_12","alias_value":"V3NE6BBVJFIU","created_at":"2026-07-05T11:14:17.686878+00:00"},{"alias_kind":"pith_short_16","alias_value":"V3NE6BBVJFIUCWB6","created_at":"2026-07-05T11:14:17.686878+00:00"},{"alias_kind":"pith_short_8","alias_value":"V3NE6BBV","created_at":"2026-07-05T11:14:17.686878+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2509.13648","citing_title":"Sequential Data Augmentation for Generative Recommendation","ref_index":29,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5","json":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5.json","graph_json":"https://pith.science/api/pith-number/V3NE6BBVJFIUCWB6YSPU7IDPX5/graph.json","events_json":"https://pith.science/api/pith-number/V3NE6BBVJFIUCWB6YSPU7IDPX5/events.json","paper":"https://pith.science/paper/V3NE6BBV"},"agent_actions":{"view_html":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5","download_json":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5.json","view_paper":"https://pith.science/paper/V3NE6BBV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.01673&json=true","fetch_graph":"https://pith.science/api/pith-number/V3NE6BBVJFIUCWB6YSPU7IDPX5/graph.json","fetch_events":"https://pith.science/api/pith-number/V3NE6BBVJFIUCWB6YSPU7IDPX5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5/action/storage_attestation","attest_author":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5/action/author_attestation","sign_citation":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5/action/citation_signature","submit_replication":"https://pith.science/pith/V3NE6BBVJFIUCWB6YSPU7IDPX5/action/replication_record"}},"created_at":"2026-07-05T11:14:17.686878+00:00","updated_at":"2026-07-05T11:14:17.686878+00:00"}