{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:Q3FUUBF6KWU5H4OBBPPPLPGU6A","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":"3d4e76aad70b4d690eef3c4239028301617a50cd6290e01d35030ba9d9bbfb73","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-18T09:25:35Z","title_canon_sha256":"d847d6b49d24140978bed38ca3e17d095289167d9945528da62daf80c33d2d0e"},"schema_version":"1.0","source":{"id":"2406.12430","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.12430","created_at":"2026-07-05T08:33:46Z"},{"alias_kind":"arxiv_version","alias_value":"2406.12430v1","created_at":"2026-07-05T08:33:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.12430","created_at":"2026-07-05T08:33:46Z"},{"alias_kind":"pith_short_12","alias_value":"Q3FUUBF6KWU5","created_at":"2026-07-05T08:33:46Z"},{"alias_kind":"pith_short_16","alias_value":"Q3FUUBF6KWU5H4OB","created_at":"2026-07-05T08:33:46Z"},{"alias_kind":"pith_short_8","alias_value":"Q3FUUBF6","created_at":"2026-07-05T08:33:46Z"}],"graph_snapshots":[{"event_id":"sha256:79eacf6f00cc6a824108c8fb323e1a1e3d28b0748340de8c74dab0bd1c77f9ae","target":"graph","created_at":"2026-07-05T08:33:46Z","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/2406.12430/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we conduct a study to utilize LLMs as a solution for decision making that requires complex data analysis. We define Decision QA as the task of answering the best decision, $d_{best}$, for a decision-making question $Q$, business rules $R$ and a database $D$. Since there is no benchmark that can examine Decision QA, we propose Decision QA benchmark, DQA. It has two scenarios, Locating and Building, constructed from two video games (Europa Universalis IV and Victoria 3) that have almost the same goal as Decision QA. To address Decision QA effectively, we also propose a new RAG tec","authors_text":"Min-Soo Kim, Myeonghwa Lee, Seonho An","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-18T09:25:35Z","title":"PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.12430","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:c57cc48d8ad6f9d0401b4382f19c69ccdb4ffe5febbfb0f32d1e0eab3ad48532","target":"record","created_at":"2026-07-05T08:33:46Z","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":"3d4e76aad70b4d690eef3c4239028301617a50cd6290e01d35030ba9d9bbfb73","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-18T09:25:35Z","title_canon_sha256":"d847d6b49d24140978bed38ca3e17d095289167d9945528da62daf80c33d2d0e"},"schema_version":"1.0","source":{"id":"2406.12430","kind":"arxiv","version":1}},"canonical_sha256":"86cb4a04be55a9d3f1c10bdef5bcd4f033c52ed37c6a65f8c7a1234f815347f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"86cb4a04be55a9d3f1c10bdef5bcd4f033c52ed37c6a65f8c7a1234f815347f8","first_computed_at":"2026-07-05T08:33:46.189108Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:33:46.189108Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tDSC8SW8MQ6WL5DSJhuGIT2jigRsdN+An5l94fmROAGhA6HipqYgvzqV1oX6tBnwWq0jfsNV81AXBGrBCXlkDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:33:46.189507Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.12430","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c57cc48d8ad6f9d0401b4382f19c69ccdb4ffe5febbfb0f32d1e0eab3ad48532","sha256:79eacf6f00cc6a824108c8fb323e1a1e3d28b0748340de8c74dab0bd1c77f9ae"],"state_sha256":"4fb4866eb5586ff63d22de6b7d4557496c84242b35225f8b47570a9b2b4f306d"}