{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YDUBA5SQ6DLQPWKS4SIKKPHPOG","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":"e04f8ecb4b67493dd109c0c5dfdb64045e0828e946b9d9a83549aed8ce61ec14","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-05-06T13:53:03Z","title_canon_sha256":"c62edab31bd18731448b2302ecd4c93fc2adeac9839a66730165efa0dca87371"},"schema_version":"1.0","source":{"id":"2405.03480","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03480","created_at":"2026-07-05T08:16:03Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03480v1","created_at":"2026-07-05T08:16:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03480","created_at":"2026-07-05T08:16:03Z"},{"alias_kind":"pith_short_12","alias_value":"YDUBA5SQ6DLQ","created_at":"2026-07-05T08:16:03Z"},{"alias_kind":"pith_short_16","alias_value":"YDUBA5SQ6DLQPWKS","created_at":"2026-07-05T08:16:03Z"},{"alias_kind":"pith_short_8","alias_value":"YDUBA5SQ","created_at":"2026-07-05T08:16:03Z"}],"graph_snapshots":[{"event_id":"sha256:57483d16bb5d1ff2a625a492c34bd69d684869c4dd048a6d5f5a4b8cec9fc3ba","target":"graph","created_at":"2026-07-05T08:16:03Z","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/2405.03480/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The future of conversational agents will provide users with personalized information responses. However, a significant challenge in developing models is the lack of large-scale dialogue datasets that span multiple sessions and reflect real-world user preferences. Previous approaches rely on experts in a wizard-of-oz setup that is difficult to scale, particularly for personalized tasks. Our method, LAPS, addresses this by using large language models (LLMs) to guide a single human worker in generating personalized dialogues. This method has proven to speed up the creation process and improve qua","authors_text":"Andrew Ramsay, Arjen P. de Vries, Faegheh Hasibi, Hideaki Joko, Jeff Dalton, Shubham Chatterjee","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-05-06T13:53:03Z","title":"Doing Personal LAPS: LLM-Augmented Dialogue Construction for Personalized Multi-Session Conversational Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03480","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":"sha256:032a2a0b19024c22d4f7ed68f242619cd23a9e2b16ab69eb723c5f94c161463b","target":"record","created_at":"2026-07-05T08:16:03Z","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":"e04f8ecb4b67493dd109c0c5dfdb64045e0828e946b9d9a83549aed8ce61ec14","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-05-06T13:53:03Z","title_canon_sha256":"c62edab31bd18731448b2302ecd4c93fc2adeac9839a66730165efa0dca87371"},"schema_version":"1.0","source":{"id":"2405.03480","kind":"arxiv","version":1}},"canonical_sha256":"c0e8107650f0d707d952e490a53cef718c93fa15b4710196bef7872e34ae7f33","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c0e8107650f0d707d952e490a53cef718c93fa15b4710196bef7872e34ae7f33","first_computed_at":"2026-07-05T08:16:03.578094Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:16:03.578094Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4FTbH5ZIXqhRs3jQQ0eT4CEgWh6c0F1RF+twwHH0gf3WLDb5CQVbJ0vpo1Gi+gHLKXfd47aNCle4atp3v/EVCw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:16:03.578539Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.03480","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:032a2a0b19024c22d4f7ed68f242619cd23a9e2b16ab69eb723c5f94c161463b","sha256:57483d16bb5d1ff2a625a492c34bd69d684869c4dd048a6d5f5a4b8cec9fc3ba"],"state_sha256":"8418bab0c53f051da0292da871858fadcaefdd17a469106214d93ef084130a13"}