{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HFKNGNZUZ52HCJRAP32J7L6YU7","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":"de840ce30238438e7d148e84f33382f5440d9e24cdcf16ce98ccb3de2def2386","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-05T15:22:36Z","title_canon_sha256":"834977cef82afd3d3d147b63b0d7097346462bcacdc3a32e8695a2663a7acc40"},"schema_version":"1.0","source":{"id":"2410.04197","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04197","created_at":"2026-07-05T09:16:30Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04197v1","created_at":"2026-07-05T09:16:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04197","created_at":"2026-07-05T09:16:30Z"},{"alias_kind":"pith_short_12","alias_value":"HFKNGNZUZ52H","created_at":"2026-07-05T09:16:30Z"},{"alias_kind":"pith_short_16","alias_value":"HFKNGNZUZ52HCJRA","created_at":"2026-07-05T09:16:30Z"},{"alias_kind":"pith_short_8","alias_value":"HFKNGNZU","created_at":"2026-07-05T09:16:30Z"}],"graph_snapshots":[{"event_id":"sha256:f00133934f23a296f3543558b8956032ae555f1e1513558c160f22e1dd404f2a","target":"graph","created_at":"2026-07-05T09:16:30Z","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/2410.04197/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Evaluating the creativity of large language models (LLMs) in story writing is difficult because LLM-generated stories could seemingly look creative but be very similar to some existing stories in their huge and proprietary training corpus. To overcome this challenge, we introduce a novel benchmark dataset with varying levels of prompt specificity: CS4 ($\\mathbf{C}$omparing the $\\mathbf{S}$kill of $\\mathbf{C}$reating $\\mathbf{S}$tories by $\\mathbf{C}$ontrolling the $\\mathbf{S}$ynthesized $\\mathbf{C}$onstraint $\\mathbf{S}$pecificity). By increasing the number of requirements/constraints in the p","authors_text":"Anirudh Atmakuru, Anirudh Lakkaraju, Hamed Zamani, Haw-Shiuan Chang, Jatin Nainani, Rohith Siddhartha Reddy Bheemreddy, Zonghai Yao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-05T15:22:36Z","title":"CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraints"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04197","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":"sha256:4e427dcdf2fa3625377a36f27f21b56e7e831184daa537e7e9dc43619ecd070f","target":"record","created_at":"2026-07-05T09:16:30Z","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":"de840ce30238438e7d148e84f33382f5440d9e24cdcf16ce98ccb3de2def2386","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-05T15:22:36Z","title_canon_sha256":"834977cef82afd3d3d147b63b0d7097346462bcacdc3a32e8695a2663a7acc40"},"schema_version":"1.0","source":{"id":"2410.04197","kind":"arxiv","version":1}},"canonical_sha256":"3954d33734cf747126207ef49fafd8a7e43bf367f5851211328f298c9bb2f77f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3954d33734cf747126207ef49fafd8a7e43bf367f5851211328f298c9bb2f77f","first_computed_at":"2026-07-05T09:16:30.631395Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:16:30.631395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UWkO9fW5jkbqIVM2JtFlMDe1n7SCwKV1emS3kPmwio8ekYZVn8Z1NnnJMltXYuaQ/NXYLMPLvzephqU3Bqp+Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:16:30.631883Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.04197","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e427dcdf2fa3625377a36f27f21b56e7e831184daa537e7e9dc43619ecd070f","sha256:f00133934f23a296f3543558b8956032ae555f1e1513558c160f22e1dd404f2a"],"state_sha256":"d8e6e56a552ce1273c973351861714a31773138c7cc8b8ae4a4fca6dedda5f77"}