{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:YA6OO3O5E7GT3VJXIYT34ONTNB","short_pith_number":"pith:YA6OO3O5","canonical_record":{"source":{"id":"2412.18715","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-25T00:26:51Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"61a378d28f3fd0ee914094ff1a1d7767b9ce0f788830eee6a2ca8dc5853b8030","abstract_canon_sha256":"5b9ad3201ccae7d027f53619a39f61a6cb3e650a6191eea0a1450c3b15e72412"},"schema_version":"1.0"},"canonical_sha256":"c03ce76ddd27cd3dd5374627be39b3687fc8ec42b9d72717e52a0a9c6819ffe8","source":{"kind":"arxiv","id":"2412.18715","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.18715","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"arxiv_version","alias_value":"2412.18715v1","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.18715","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"pith_short_12","alias_value":"YA6OO3O5E7GT","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"pith_short_16","alias_value":"YA6OO3O5E7GT3VJX","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"pith_short_8","alias_value":"YA6OO3O5","created_at":"2026-07-05T09:54:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:YA6OO3O5E7GT3VJXIYT34ONTNB","target":"record","payload":{"canonical_record":{"source":{"id":"2412.18715","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-25T00:26:51Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"61a378d28f3fd0ee914094ff1a1d7767b9ce0f788830eee6a2ca8dc5853b8030","abstract_canon_sha256":"5b9ad3201ccae7d027f53619a39f61a6cb3e650a6191eea0a1450c3b15e72412"},"schema_version":"1.0"},"canonical_sha256":"c03ce76ddd27cd3dd5374627be39b3687fc8ec42b9d72717e52a0a9c6819ffe8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:54:09.606307Z","signature_b64":"7fsjgRuycpaN3b45peRdkEnoVtnM8ReY3torbOzbgaep0F6OETEo9MRWvAvjC7Wi0ubVSCOKS6OpxcyDRehZDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c03ce76ddd27cd3dd5374627be39b3687fc8ec42b9d72717e52a0a9c6819ffe8","last_reissued_at":"2026-07-05T09:54:09.605876Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:54:09.605876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.18715","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:54:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9mXZ0rsVSUt7ln3z+FwDF83GLr38JVJnf1a39XhHdtPKuTiArCtCXjHb4gxfFPi6dA7cAfQTVUjB6gwsXYiECA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T07:31:40.076488Z"},"content_sha256":"b0aa7df87982b6dde30ba77afe1fa31df4742a6ecdc3b535c4886998c3e7fec9","schema_version":"1.0","event_id":"sha256:b0aa7df87982b6dde30ba77afe1fa31df4742a6ecdc3b535c4886998c3e7fec9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:YA6OO3O5E7GT3VJXIYT34ONTNB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.AI","authors_text":"Haowei Yang, Jinghan Cao, Longfei Yun, Qingyi Lu, Yuming Tu","submitted_at":"2024-12-25T00:26:51Z","abstract_excerpt":"With the rapid development of large language models (LLMs) and the growing demand for personalized content, recommendation systems have become critical in enhancing user experience and driving engagement. Collaborative filtering algorithms, being core to many recommendation systems, have garnered significant attention for their efficiency and interpretability. However, traditional collaborative filtering approaches face numerous challenges when integrated into large-scale LLM-based systems, including high computational costs, severe data sparsity, cold start problems, and lack of scalability. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.18715","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/2412.18715/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:54:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mPa4VwI+nJoZ4beF2kwohkgSkC/1uSMwPTfe78/PknDucuUQhDvwp6yWKbRshpl9KO2E86fM3Vner5Dj0vr/Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T07:31:40.077521Z"},"content_sha256":"a30d8ce4e36c9b1b46a9feef3cedac02aed602a9e1b80f4f5ce553d54fd232b6","schema_version":"1.0","event_id":"sha256:a30d8ce4e36c9b1b46a9feef3cedac02aed602a9e1b80f4f5ce553d54fd232b6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YA6OO3O5E7GT3VJXIYT34ONTNB/bundle.json","state_url":"https://pith.science/pith/YA6OO3O5E7GT3VJXIYT34ONTNB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YA6OO3O5E7GT3VJXIYT34ONTNB/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-13T07:31:40Z","links":{"resolver":"https://pith.science/pith/YA6OO3O5E7GT3VJXIYT34ONTNB","bundle":"https://pith.science/pith/YA6OO3O5E7GT3VJXIYT34ONTNB/bundle.json","state":"https://pith.science/pith/YA6OO3O5E7GT3VJXIYT34ONTNB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YA6OO3O5E7GT3VJXIYT34ONTNB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YA6OO3O5E7GT3VJXIYT34ONTNB","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":"5b9ad3201ccae7d027f53619a39f61a6cb3e650a6191eea0a1450c3b15e72412","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-25T00:26:51Z","title_canon_sha256":"61a378d28f3fd0ee914094ff1a1d7767b9ce0f788830eee6a2ca8dc5853b8030"},"schema_version":"1.0","source":{"id":"2412.18715","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.18715","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"arxiv_version","alias_value":"2412.18715v1","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.18715","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"pith_short_12","alias_value":"YA6OO3O5E7GT","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"pith_short_16","alias_value":"YA6OO3O5E7GT3VJX","created_at":"2026-07-05T09:54:09Z"},{"alias_kind":"pith_short_8","alias_value":"YA6OO3O5","created_at":"2026-07-05T09:54:09Z"}],"graph_snapshots":[{"event_id":"sha256:a30d8ce4e36c9b1b46a9feef3cedac02aed602a9e1b80f4f5ce553d54fd232b6","target":"graph","created_at":"2026-07-05T09:54:09Z","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/2412.18715/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the rapid development of large language models (LLMs) and the growing demand for personalized content, recommendation systems have become critical in enhancing user experience and driving engagement. Collaborative filtering algorithms, being core to many recommendation systems, have garnered significant attention for their efficiency and interpretability. However, traditional collaborative filtering approaches face numerous challenges when integrated into large-scale LLM-based systems, including high computational costs, severe data sparsity, cold start problems, and lack of scalability. ","authors_text":"Haowei Yang, Jinghan Cao, Longfei Yun, Qingyi Lu, Yuming Tu","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-25T00:26:51Z","title":"Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.18715","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:b0aa7df87982b6dde30ba77afe1fa31df4742a6ecdc3b535c4886998c3e7fec9","target":"record","created_at":"2026-07-05T09:54:09Z","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":"5b9ad3201ccae7d027f53619a39f61a6cb3e650a6191eea0a1450c3b15e72412","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-25T00:26:51Z","title_canon_sha256":"61a378d28f3fd0ee914094ff1a1d7767b9ce0f788830eee6a2ca8dc5853b8030"},"schema_version":"1.0","source":{"id":"2412.18715","kind":"arxiv","version":1}},"canonical_sha256":"c03ce76ddd27cd3dd5374627be39b3687fc8ec42b9d72717e52a0a9c6819ffe8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c03ce76ddd27cd3dd5374627be39b3687fc8ec42b9d72717e52a0a9c6819ffe8","first_computed_at":"2026-07-05T09:54:09.605876Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:54:09.605876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7fsjgRuycpaN3b45peRdkEnoVtnM8ReY3torbOzbgaep0F6OETEo9MRWvAvjC7Wi0ubVSCOKS6OpxcyDRehZDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:54:09.606307Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.18715","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b0aa7df87982b6dde30ba77afe1fa31df4742a6ecdc3b535c4886998c3e7fec9","sha256:a30d8ce4e36c9b1b46a9feef3cedac02aed602a9e1b80f4f5ce553d54fd232b6"],"state_sha256":"87844a0e79e60d0ebb5f3e4d86841b5c5b64e3428ccc132a98f619b180ba71e5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e7Hdm4eRygssC/NIxI3u2EGrZEGWt1cG0obNEr0GTAoD66tUiVlsk5VorDPT2pvRd9WidAy5EwfCjU7uxcnjDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T07:31:40.085365Z","bundle_sha256":"5681457630f6188aa2791350586bb9c034f72423ff408e17e4311afdcca40c34"}}