{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:AX5PTPRWUAQFGJANDW273S4F46","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":"55c73d8036496ba676432d21ddcbb89814004f4182e920ce9f706ac64585a823","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-10-26T15:44:57Z","title_canon_sha256":"1a4bcae7896b744a723f79c2189f2242e6b7d22880d26f82475b803e927d7f03"},"schema_version":"1.0","source":{"id":"2310.17488","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.17488","created_at":"2026-07-05T07:06:37Z"},{"alias_kind":"arxiv_version","alias_value":"2310.17488v2","created_at":"2026-07-05T07:06:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.17488","created_at":"2026-07-05T07:06:37Z"},{"alias_kind":"pith_short_12","alias_value":"AX5PTPRWUAQF","created_at":"2026-07-05T07:06:37Z"},{"alias_kind":"pith_short_16","alias_value":"AX5PTPRWUAQFGJAN","created_at":"2026-07-05T07:06:37Z"},{"alias_kind":"pith_short_8","alias_value":"AX5PTPRW","created_at":"2026-07-05T07:06:37Z"}],"graph_snapshots":[{"event_id":"sha256:6fda4380b00f93edf2a637574886f7d515dee543ff51dcb6b47035e569afa376","target":"graph","created_at":"2026-07-05T07:06:37Z","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/2310.17488/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents LightLM, a lightweight Transformer-based language model for generative recommendation. While Transformer-based generative modeling has gained importance in various AI sub-fields such as NLP and vision, generative recommendation is still in its infancy due to its unique demand on personalized generative modeling. Existing works on generative recommendation often use NLP-oriented Transformer architectures such as T5, GPT, LLaMA and M6, which are heavy-weight and are not specifically designed for recommendation tasks. LightLM tackles the issue by introducing a light-weight dee","authors_text":"Kai Mei, Yongfeng Zhang","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-10-26T15:44:57Z","title":"LightLM: A Lightweight Deep and Narrow Language Model for Generative Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.17488","kind":"arxiv","version":2},"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":"sha256:239c6a933833863936b61c7128cb022ece51b2636f00516d3289ba6f6776a803","target":"record","created_at":"2026-07-05T07:06:37Z","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":"55c73d8036496ba676432d21ddcbb89814004f4182e920ce9f706ac64585a823","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2023-10-26T15:44:57Z","title_canon_sha256":"1a4bcae7896b744a723f79c2189f2242e6b7d22880d26f82475b803e927d7f03"},"schema_version":"1.0","source":{"id":"2310.17488","kind":"arxiv","version":2}},"canonical_sha256":"05faf9be36a02053240d1db5fdcb85e7a254c9e02ff05123d2c3959f6439d4c2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"05faf9be36a02053240d1db5fdcb85e7a254c9e02ff05123d2c3959f6439d4c2","first_computed_at":"2026-07-05T07:06:37.878013Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:06:37.878013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3AAy8bklq4KlXD43LiUr0h9XtUohF43itdY1/4iit2dsWaHLGj3vCbxHI7/M0w6WCL1uBT0QU/x14Rq7wpB7CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:06:37.878519Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.17488","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:239c6a933833863936b61c7128cb022ece51b2636f00516d3289ba6f6776a803","sha256:6fda4380b00f93edf2a637574886f7d515dee543ff51dcb6b47035e569afa376"],"state_sha256":"9bcd0386ce8c366e1dedc909ef5055bf54ca6de23ab0ccac81fa7dcc0a935098"}