{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:6NXN6FQRTUU3APQQNXKEERWYON","short_pith_number":"pith:6NXN6FQR","schema_version":"1.0","canonical_sha256":"f36edf16119d29b03e106dd44246d873593794060a232f8e4df0318089518ece","source":{"kind":"arxiv","id":"2606.22681","version":1},"attestation_state":"computed","paper":{"title":"Only Ask What You Don't Know: Grounded Delta Planning for Efficient Multi-step RAG","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Claire Lin, Hung-yi Lee, Jian-Ren Lin, Jyh-Shing Roger Jang, Wei-Chieh Chou, Xuanjun Chen","submitted_at":"2026-06-21T21:46:41Z","abstract_excerpt":"Multi-hop question answering remains challenging for Retrieval-Augmented Generation (RAG) because existing approaches either propagate errors across iterative retrieval rounds or over-generate reasoning steps, increasing cost without improving accuracy. We propose Grounded Delta Planning RAG (GDP-RAG), a plan-based framework that targets only the information delta based on three simple design choices: (1) preliminary retrieval to ground planning before execution, (2) a gap-conditioned planning prompt that asks only for missing information, and (3) a skeletal trajectory that pairs each subquery"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.22681","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-21T21:46:41Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bf01c183343417cbbb224817cf92a8efd50bbbe262ac54c34dfd599293c1e4eb","abstract_canon_sha256":"99629cf10f39f9450b26f9421c32e08df9131d042d7c09ee2dd3d1718b9d6f6e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T02:13:44.726923Z","signature_b64":"/RAF0uK3lPHZ+1pNy2w8NarStdyotUzNJdNo5lZfzRN2nN5ciEJs6YrLP81M48X5/Nal9b4AMZgUR0v6ZQ1YAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f36edf16119d29b03e106dd44246d873593794060a232f8e4df0318089518ece","last_reissued_at":"2026-06-23T02:13:44.726495Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T02:13:44.726495Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Only Ask What You Don't Know: Grounded Delta Planning for Efficient Multi-step RAG","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Claire Lin, Hung-yi Lee, Jian-Ren Lin, Jyh-Shing Roger Jang, Wei-Chieh Chou, Xuanjun Chen","submitted_at":"2026-06-21T21:46:41Z","abstract_excerpt":"Multi-hop question answering remains challenging for Retrieval-Augmented Generation (RAG) because existing approaches either propagate errors across iterative retrieval rounds or over-generate reasoning steps, increasing cost without improving accuracy. We propose Grounded Delta Planning RAG (GDP-RAG), a plan-based framework that targets only the information delta based on three simple design choices: (1) preliminary retrieval to ground planning before execution, (2) a gap-conditioned planning prompt that asks only for missing information, and (3) a skeletal trajectory that pairs each subquery"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22681","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.22681/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.22681","created_at":"2026-06-23T02:13:44.726568+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.22681v1","created_at":"2026-06-23T02:13:44.726568+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.22681","created_at":"2026-06-23T02:13:44.726568+00:00"},{"alias_kind":"pith_short_12","alias_value":"6NXN6FQRTUU3","created_at":"2026-06-23T02:13:44.726568+00:00"},{"alias_kind":"pith_short_16","alias_value":"6NXN6FQRTUU3APQQ","created_at":"2026-06-23T02:13:44.726568+00:00"},{"alias_kind":"pith_short_8","alias_value":"6NXN6FQR","created_at":"2026-06-23T02:13:44.726568+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON","json":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON.json","graph_json":"https://pith.science/api/pith-number/6NXN6FQRTUU3APQQNXKEERWYON/graph.json","events_json":"https://pith.science/api/pith-number/6NXN6FQRTUU3APQQNXKEERWYON/events.json","paper":"https://pith.science/paper/6NXN6FQR"},"agent_actions":{"view_html":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON","download_json":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON.json","view_paper":"https://pith.science/paper/6NXN6FQR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.22681&json=true","fetch_graph":"https://pith.science/api/pith-number/6NXN6FQRTUU3APQQNXKEERWYON/graph.json","fetch_events":"https://pith.science/api/pith-number/6NXN6FQRTUU3APQQNXKEERWYON/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON/action/storage_attestation","attest_author":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON/action/author_attestation","sign_citation":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON/action/citation_signature","submit_replication":"https://pith.science/pith/6NXN6FQRTUU3APQQNXKEERWYON/action/replication_record"}},"created_at":"2026-06-23T02:13:44.726568+00:00","updated_at":"2026-06-23T02:13:44.726568+00:00"}