{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:V6F2YDDGQP6THUDAXF33MDSQEW","short_pith_number":"pith:V6F2YDDG","canonical_record":{"source":{"id":"2310.01612","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-10-02T20:03:42Z","cross_cats_sorted":[],"title_canon_sha256":"9632dd018703dc330d1a6662abdac6fe14e997b62d616569db697b364b678091","abstract_canon_sha256":"e0a4f5fa57a38b36ecc1e6a51baa4fbb95a1e1f25fd891be539c5c9a4054036b"},"schema_version":"1.0"},"canonical_sha256":"af8bac0c6683fd33d060b977b60e502597d8ec032818f85649f9ca4c3bac0a74","source":{"kind":"arxiv","id":"2310.01612","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.01612","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"arxiv_version","alias_value":"2310.01612v1","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.01612","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"pith_short_12","alias_value":"V6F2YDDGQP6T","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"pith_short_16","alias_value":"V6F2YDDGQP6THUDA","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"pith_short_8","alias_value":"V6F2YDDG","created_at":"2026-07-05T06:56:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:V6F2YDDGQP6THUDAXF33MDSQEW","target":"record","payload":{"canonical_record":{"source":{"id":"2310.01612","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-10-02T20:03:42Z","cross_cats_sorted":[],"title_canon_sha256":"9632dd018703dc330d1a6662abdac6fe14e997b62d616569db697b364b678091","abstract_canon_sha256":"e0a4f5fa57a38b36ecc1e6a51baa4fbb95a1e1f25fd891be539c5c9a4054036b"},"schema_version":"1.0"},"canonical_sha256":"af8bac0c6683fd33d060b977b60e502597d8ec032818f85649f9ca4c3bac0a74","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:56:43.095684Z","signature_b64":"X2c5RhDyVu2hNK9AH5+FESK7V7bf+1EJHrs/1BinhNifuj3+vB4L/0M/QOod3yBlwqoIGZ6//FAfiLzl/EeNCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af8bac0c6683fd33d060b977b60e502597d8ec032818f85649f9ca4c3bac0a74","last_reissued_at":"2026-07-05T06:56:43.095144Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:56:43.095144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.01612","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":"2026-07-05T06:56:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fDQGGlpnkJ86UW8Mm+/hIhKgzZ1BlCBJC0VFTHvV2NSSTIUZ8EMrO5rblurAfy0FVIqABW6x8NG/XHRsRpXeBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T08:51:04.061987Z"},"content_sha256":"24fc98b91dd2eb17c384369b26afa8993223481ce37556762fd9f2bd829e7b6a","schema_version":"1.0","event_id":"sha256:24fc98b91dd2eb17c384369b26afa8993223481ce37556762fd9f2bd829e7b6a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:V6F2YDDGQP6THUDAXF33MDSQEW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Ben Burns, Bo Peng, Srinivasan Parthasarathy, Xia Ning, Ziqi Chen","submitted_at":"2023-10-02T20:03:42Z","abstract_excerpt":"In recent years, with large language models (LLMs) achieving state-of-the-art performance in context understanding, increasing efforts have been dedicated to developing LLM-enhanced sequential recommendation (SR) methods. Considering that most existing LLMs are not specifically optimized for recommendation tasks, adapting them for SR becomes a critical step in LLM-enhanced SR methods. Though numerous adaptation methods have been developed, it still remains a significant challenge to adapt LLMs for SR both efficiently and effectively. To address this challenge, in this paper, we introduce a nov"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.01612","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/2310.01612/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":"2026-07-05T06:56:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AUSueNkR8KVkMIwqjQuzV1l55jN8XavHdSlpclI9KFaVl1/0PoRGrsRZIL2UP/WLGbikngdvie5oGCnAF1xdAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T08:51:04.062539Z"},"content_sha256":"75961862d397902a64d07f5e18bbd142a4fd7117ae505415356369a26b834a08","schema_version":"1.0","event_id":"sha256:75961862d397902a64d07f5e18bbd142a4fd7117ae505415356369a26b834a08"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V6F2YDDGQP6THUDAXF33MDSQEW/bundle.json","state_url":"https://pith.science/pith/V6F2YDDGQP6THUDAXF33MDSQEW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V6F2YDDGQP6THUDAXF33MDSQEW/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":"2026-08-09T08:51:04Z","links":{"resolver":"https://pith.science/pith/V6F2YDDGQP6THUDAXF33MDSQEW","bundle":"https://pith.science/pith/V6F2YDDGQP6THUDAXF33MDSQEW/bundle.json","state":"https://pith.science/pith/V6F2YDDGQP6THUDAXF33MDSQEW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V6F2YDDGQP6THUDAXF33MDSQEW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:V6F2YDDGQP6THUDAXF33MDSQEW","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":"e0a4f5fa57a38b36ecc1e6a51baa4fbb95a1e1f25fd891be539c5c9a4054036b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-10-02T20:03:42Z","title_canon_sha256":"9632dd018703dc330d1a6662abdac6fe14e997b62d616569db697b364b678091"},"schema_version":"1.0","source":{"id":"2310.01612","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.01612","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"arxiv_version","alias_value":"2310.01612v1","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.01612","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"pith_short_12","alias_value":"V6F2YDDGQP6T","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"pith_short_16","alias_value":"V6F2YDDGQP6THUDA","created_at":"2026-07-05T06:56:43Z"},{"alias_kind":"pith_short_8","alias_value":"V6F2YDDG","created_at":"2026-07-05T06:56:43Z"}],"graph_snapshots":[{"event_id":"sha256:75961862d397902a64d07f5e18bbd142a4fd7117ae505415356369a26b834a08","target":"graph","created_at":"2026-07-05T06:56:43Z","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/2310.01612/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, with large language models (LLMs) achieving state-of-the-art performance in context understanding, increasing efforts have been dedicated to developing LLM-enhanced sequential recommendation (SR) methods. Considering that most existing LLMs are not specifically optimized for recommendation tasks, adapting them for SR becomes a critical step in LLM-enhanced SR methods. Though numerous adaptation methods have been developed, it still remains a significant challenge to adapt LLMs for SR both efficiently and effectively. To address this challenge, in this paper, we introduce a nov","authors_text":"Ben Burns, Bo Peng, Srinivasan Parthasarathy, Xia Ning, Ziqi Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-10-02T20:03:42Z","title":"Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.01612","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":"sha256:24fc98b91dd2eb17c384369b26afa8993223481ce37556762fd9f2bd829e7b6a","target":"record","created_at":"2026-07-05T06:56:43Z","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":"e0a4f5fa57a38b36ecc1e6a51baa4fbb95a1e1f25fd891be539c5c9a4054036b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-10-02T20:03:42Z","title_canon_sha256":"9632dd018703dc330d1a6662abdac6fe14e997b62d616569db697b364b678091"},"schema_version":"1.0","source":{"id":"2310.01612","kind":"arxiv","version":1}},"canonical_sha256":"af8bac0c6683fd33d060b977b60e502597d8ec032818f85649f9ca4c3bac0a74","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af8bac0c6683fd33d060b977b60e502597d8ec032818f85649f9ca4c3bac0a74","first_computed_at":"2026-07-05T06:56:43.095144Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:56:43.095144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X2c5RhDyVu2hNK9AH5+FESK7V7bf+1EJHrs/1BinhNifuj3+vB4L/0M/QOod3yBlwqoIGZ6//FAfiLzl/EeNCg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:56:43.095684Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.01612","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:24fc98b91dd2eb17c384369b26afa8993223481ce37556762fd9f2bd829e7b6a","sha256:75961862d397902a64d07f5e18bbd142a4fd7117ae505415356369a26b834a08"],"state_sha256":"ada491d6ebb4a2d53aadc0443efa927f9660eb32592703a36c796a441f243f4b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AFhH1Sp6SQ0eaSJuG7AyJI7gk09ag68zgAtHVo2gT7FMbH9BZwOvGj2nR8ujhdW+YkeoggKNG850FlAjcXfWDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T08:51:04.067432Z","bundle_sha256":"4560c5eb689f6f7416942144ff2d4fdb0653f5670ae88eafbacfc246af2f0157"}}