{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:66WON2DN3HG5CZ65XIBJ7Z7LTT","short_pith_number":"pith:66WON2DN","canonical_record":{"source":{"id":"2402.01339","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-02T11:52:07Z","cross_cats_sorted":[],"title_canon_sha256":"d26124338235945a6ad93b4e47e8c25c9c3fe5197a8c707d3f4112821ed0cd24","abstract_canon_sha256":"25625224eb14534c2d8cff9494c08072357e654cd4687f020e79f9a8933cb4a1"},"schema_version":"1.0"},"canonical_sha256":"f7ace6e86dd9cdd167ddba029fe7eb9cc00fd2bbd4ff958ecf4f6294a6c442ca","source":{"kind":"arxiv","id":"2402.01339","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01339","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01339v2","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01339","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"pith_short_12","alias_value":"66WON2DN3HG5","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"pith_short_16","alias_value":"66WON2DN3HG5CZ65","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"pith_short_8","alias_value":"66WON2DN","created_at":"2026-07-05T09:59:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:66WON2DN3HG5CZ65XIBJ7Z7LTT","target":"record","payload":{"canonical_record":{"source":{"id":"2402.01339","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-02T11:52:07Z","cross_cats_sorted":[],"title_canon_sha256":"d26124338235945a6ad93b4e47e8c25c9c3fe5197a8c707d3f4112821ed0cd24","abstract_canon_sha256":"25625224eb14534c2d8cff9494c08072357e654cd4687f020e79f9a8933cb4a1"},"schema_version":"1.0"},"canonical_sha256":"f7ace6e86dd9cdd167ddba029fe7eb9cc00fd2bbd4ff958ecf4f6294a6c442ca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:59:43.697643Z","signature_b64":"b9yWoCtCT99fsZaukpBBwjsfV696sq2e0az00nJS0bqWkoJ1I5OEA/x62xKPZEIUoFLhF9ECOpMmS6ZtA415CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f7ace6e86dd9cdd167ddba029fe7eb9cc00fd2bbd4ff958ecf4f6294a6c442ca","last_reissued_at":"2026-07-05T09:59:43.697104Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:59:43.697104Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.01339","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:59:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3tGprYsy+OVv2GzkR7NDeQdfWlFlDczTWeahRCD7QXDqvu8DrG3lEpfO2gCu1fZasd7/Mxk0TZPZhPum9hAXBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:46:38.823831Z"},"content_sha256":"12fdffdfe69a24284d7e51b20d2b7749752190212b087b5e2459d5edadc2d4cc","schema_version":"1.0","event_id":"sha256:12fdffdfe69a24284d7e51b20d2b7749752190212b087b5e2459d5edadc2d4cc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:66WON2DN3HG5CZ65XIBJ7Z7LTT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Sequential Recommendations with LLMs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Artun Boz, Dietmar Jannach, Jesse Harte, Marios Fragkoulis, Panos Louridas, Vassilios Karakoidas, Wouter Zorgdrager, Zoe Kotti","submitted_at":"2024-02-02T11:52:07Z","abstract_excerpt":"The sequential recommendation problem has attracted considerable research attention in the past few years, leading to the rise of numerous recommendation models. In this work, we explore how Large Language Models (LLMs), which are nowadays introducing disruptive effects in many AI-based applications, can be used to build or improve sequential recommendation approaches. Specifically, we design three orthogonal approaches and hybrids of those to leverage the power of LLMs in different ways. In addition, we investigate the potential of each approach by focusing on its comprising technical aspects"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01339","kind":"arxiv","version":2},"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/2402.01339/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":"2026-07-05T09:59:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1rTi+utWyWlT2LjG0M18T5i6al5LVlgiLsoM5Fkzpk4TD0xXDsd5IyVgqse9fj/OA0HULA74BTZkKeQ0uhBpCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:46:38.824476Z"},"content_sha256":"f97aa7b6c5bd169c5ff043d9da881f473e00bfc16a69b23f7438960d5f77e861","schema_version":"1.0","event_id":"sha256:f97aa7b6c5bd169c5ff043d9da881f473e00bfc16a69b23f7438960d5f77e861"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/66WON2DN3HG5CZ65XIBJ7Z7LTT/bundle.json","state_url":"https://pith.science/pith/66WON2DN3HG5CZ65XIBJ7Z7LTT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/66WON2DN3HG5CZ65XIBJ7Z7LTT/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":"2026-08-08T20:46:38Z","links":{"resolver":"https://pith.science/pith/66WON2DN3HG5CZ65XIBJ7Z7LTT","bundle":"https://pith.science/pith/66WON2DN3HG5CZ65XIBJ7Z7LTT/bundle.json","state":"https://pith.science/pith/66WON2DN3HG5CZ65XIBJ7Z7LTT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/66WON2DN3HG5CZ65XIBJ7Z7LTT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:66WON2DN3HG5CZ65XIBJ7Z7LTT","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":"25625224eb14534c2d8cff9494c08072357e654cd4687f020e79f9a8933cb4a1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-02T11:52:07Z","title_canon_sha256":"d26124338235945a6ad93b4e47e8c25c9c3fe5197a8c707d3f4112821ed0cd24"},"schema_version":"1.0","source":{"id":"2402.01339","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01339","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01339v2","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01339","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"pith_short_12","alias_value":"66WON2DN3HG5","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"pith_short_16","alias_value":"66WON2DN3HG5CZ65","created_at":"2026-07-05T09:59:43Z"},{"alias_kind":"pith_short_8","alias_value":"66WON2DN","created_at":"2026-07-05T09:59:43Z"}],"graph_snapshots":[{"event_id":"sha256:f97aa7b6c5bd169c5ff043d9da881f473e00bfc16a69b23f7438960d5f77e861","target":"graph","created_at":"2026-07-05T09:59:43Z","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/2402.01339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The sequential recommendation problem has attracted considerable research attention in the past few years, leading to the rise of numerous recommendation models. In this work, we explore how Large Language Models (LLMs), which are nowadays introducing disruptive effects in many AI-based applications, can be used to build or improve sequential recommendation approaches. Specifically, we design three orthogonal approaches and hybrids of those to leverage the power of LLMs in different ways. In addition, we investigate the potential of each approach by focusing on its comprising technical aspects","authors_text":"Artun Boz, Dietmar Jannach, Jesse Harte, Marios Fragkoulis, Panos Louridas, Vassilios Karakoidas, Wouter Zorgdrager, Zoe Kotti","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-02T11:52:07Z","title":"Improving Sequential Recommendations with LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01339","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":"sha256:12fdffdfe69a24284d7e51b20d2b7749752190212b087b5e2459d5edadc2d4cc","target":"record","created_at":"2026-07-05T09:59:43Z","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":"25625224eb14534c2d8cff9494c08072357e654cd4687f020e79f9a8933cb4a1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-02-02T11:52:07Z","title_canon_sha256":"d26124338235945a6ad93b4e47e8c25c9c3fe5197a8c707d3f4112821ed0cd24"},"schema_version":"1.0","source":{"id":"2402.01339","kind":"arxiv","version":2}},"canonical_sha256":"f7ace6e86dd9cdd167ddba029fe7eb9cc00fd2bbd4ff958ecf4f6294a6c442ca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f7ace6e86dd9cdd167ddba029fe7eb9cc00fd2bbd4ff958ecf4f6294a6c442ca","first_computed_at":"2026-07-05T09:59:43.697104Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:59:43.697104Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"b9yWoCtCT99fsZaukpBBwjsfV696sq2e0az00nJS0bqWkoJ1I5OEA/x62xKPZEIUoFLhF9ECOpMmS6ZtA415CA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:59:43.697643Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.01339","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:12fdffdfe69a24284d7e51b20d2b7749752190212b087b5e2459d5edadc2d4cc","sha256:f97aa7b6c5bd169c5ff043d9da881f473e00bfc16a69b23f7438960d5f77e861"],"state_sha256":"3b29874493119f23686387b786a5aec264fc4e9dea2bc695118f8bb7f5f669ec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f1d2QkNHpvSXcs8Ky/cRFa/ptsITtA9V6+aVqc8oilFkfiVyQmps9lVngHTnqr+2x7cOpgHPiGDT0LhXamwjCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:46:38.828647Z","bundle_sha256":"cf91d12ef474c6e01cd9f1a2e9a870ab86ec57c3deb52d0efa33c8e7a8124425"}}