{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3IOIWB5FF5QEV4HRZFXCJIYK36","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":"842f4f056ba4816bbadb956561ba866addd4a684ed567c9a1143bd9d8d7675ee","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-22T09:02:15Z","title_canon_sha256":"110f0acec6ffecffbf5f1e3e660d8e3d003ee8b818d53b1c9bb9ec0ea988d754"},"schema_version":"1.0","source":{"id":"2505.17149","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17149","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17149v1","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17149","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"pith_short_12","alias_value":"3IOIWB5FF5QE","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"pith_short_16","alias_value":"3IOIWB5FF5QEV4HR","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"pith_short_8","alias_value":"3IOIWB5F","created_at":"2026-07-05T11:07:47Z"}],"graph_snapshots":[{"event_id":"sha256:0f334e74836ea116016a05fcec6a7597469ddc2bb5b2e91200e55c497735a34a","target":"graph","created_at":"2026-07-05T11:07:47Z","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/2505.17149/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Predictive analysis is a cornerstone of modern decision-making, with applications in various domains. Large Language Models (LLMs) have emerged as powerful tools in enabling nuanced, knowledge-intensive conversations, thus aiding in complex decision-making tasks. With the burgeoning expectation to harness LLMs for predictive analysis, there is an urgent need to systematically assess their capability in this domain. However, there is a lack of relevant evaluations in existing studies. To bridge this gap, we introduce the \\textbf{PredictiQ} benchmark, which integrates 1130 sophisticated predicti","authors_text":"Qin Chen, Xiaojun Ma, Yuanyi Ren, Yuyang Shi","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-22T09:02:15Z","title":"Large Language Models for Predictive Analysis: How Far Are They?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17149","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":"sha256:54ab52e24cecd99c6d620ef048045c550a076d8add69a2cd7738f256abc5f490","target":"record","created_at":"2026-07-05T11:07:47Z","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":"842f4f056ba4816bbadb956561ba866addd4a684ed567c9a1143bd9d8d7675ee","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-22T09:02:15Z","title_canon_sha256":"110f0acec6ffecffbf5f1e3e660d8e3d003ee8b818d53b1c9bb9ec0ea988d754"},"schema_version":"1.0","source":{"id":"2505.17149","kind":"arxiv","version":1}},"canonical_sha256":"da1c8b07a52f604af0f1c96e24a30adf858edd5443c5fbde941e57005d7ef57f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"da1c8b07a52f604af0f1c96e24a30adf858edd5443c5fbde941e57005d7ef57f","first_computed_at":"2026-07-05T11:07:47.859139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:07:47.859139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m5G/i1WsepJRdyGu2ga52sq13gVbCKsDP88l3rXSN2E50IY76zc1SRtPIxscGxQkptYzbxtS20NM1K43HTASDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:07:47.859635Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.17149","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:54ab52e24cecd99c6d620ef048045c550a076d8add69a2cd7738f256abc5f490","sha256:0f334e74836ea116016a05fcec6a7597469ddc2bb5b2e91200e55c497735a34a"],"state_sha256":"7f431572f4e5bffa519f93164e3a0915c222a4a747e35465c6dae244423584b2"}