{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:RCMNCOS5JDEJ6E2532PRET7E76","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":"e16a657916b795ea22b5d3cf5e940283e390136f22f47ff1c97348c902dbda8d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T09:04:07Z","title_canon_sha256":"afb07a1a3ea0f01f4b8a0932b84d05948e5b2a7d3ea9017f237fa53676784551"},"schema_version":"1.0","source":{"id":"2605.29631","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.29631","created_at":"2026-05-29T01:05:51Z"},{"alias_kind":"arxiv_version","alias_value":"2605.29631v1","created_at":"2026-05-29T01:05:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29631","created_at":"2026-05-29T01:05:51Z"},{"alias_kind":"pith_short_12","alias_value":"RCMNCOS5JDEJ","created_at":"2026-05-29T01:05:51Z"},{"alias_kind":"pith_short_16","alias_value":"RCMNCOS5JDEJ6E25","created_at":"2026-05-29T01:05:51Z"},{"alias_kind":"pith_short_8","alias_value":"RCMNCOS5","created_at":"2026-05-29T01:05:51Z"}],"graph_snapshots":[{"event_id":"sha256:6268457f86f66b61341d24253f153963c3156ff27fd62db5ed7d9195cf646c76","target":"graph","created_at":"2026-05-29T01:05:51Z","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/2605.29631/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Randomized controlled trials are a cornerstone of medicine and the social sciences as they enable reliable estimates of causal effects. However, they are costly and time-consuming to conduct, motivating interest in predicting causal effects from existing experimental evidence. Recent advances in large language models (LLMs) have demonstrated strong performance on knowledge-intensive tasks, raising the question of whether these models can be used for forecasting causal effect sizes. To investigate this, we introduce Query2Effect, a new large-scale benchmark consisting of more than 72,000 natura","authors_text":"Abelardo Carlos Martinez Lorenzo, Arianna Legovini, Giuliano Martinelli, Jasmin Baier, Linxi Wang, Piriyakorn Piriyatamwong, Riccardo Orlando, Samuel Fraiberger, Satvik Garg, Sharif Kazemi","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T09:04:07Z","title":"Predicting Causal Effects from Natural Language Queries using Structured Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29631","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:f7c6d208ce37550cd37147d2217c67bf7c36a03b9241ffc482bbf3b183f1b8ff","target":"record","created_at":"2026-05-29T01:05:51Z","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":"e16a657916b795ea22b5d3cf5e940283e390136f22f47ff1c97348c902dbda8d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T09:04:07Z","title_canon_sha256":"afb07a1a3ea0f01f4b8a0932b84d05948e5b2a7d3ea9017f237fa53676784551"},"schema_version":"1.0","source":{"id":"2605.29631","kind":"arxiv","version":1}},"canonical_sha256":"8898d13a5d48c89f135dde9f124fe4ffa314687a89b53b17c7e39d19c35a1b0e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8898d13a5d48c89f135dde9f124fe4ffa314687a89b53b17c7e39d19c35a1b0e","first_computed_at":"2026-05-29T01:05:51.960011Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T01:05:51.960011Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"odViLkO93ljKzuEdtyK7J/106nmJGgJwV75Aq9xgdd9kr7k35/ZBI9g8yjC4/pvwaGnKlZHlbSWxx6ZTu+RoDA==","signature_status":"signed_v1","signed_at":"2026-05-29T01:05:51.960693Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.29631","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f7c6d208ce37550cd37147d2217c67bf7c36a03b9241ffc482bbf3b183f1b8ff","sha256:6268457f86f66b61341d24253f153963c3156ff27fd62db5ed7d9195cf646c76"],"state_sha256":"2e051cae21f3ad8b34084aa416aa71a4dcdcb1695a3cd14d653008a94ce8ec7e"}