{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:NLVIF2C65NMEGWYZ2SLUPKFCR6","short_pith_number":"pith:NLVIF2C6","schema_version":"1.0","canonical_sha256":"6aea82e85eeb58435b19d49747a8a28f85427d213930a57abe62bc417f39c919","source":{"kind":"arxiv","id":"2605.23414","version":1},"attestation_state":"computed","paper":{"title":"When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Lanjun Wang, Shilong Jin, Zehao Wang, Zhao Cao","submitted_at":"2026-05-22T09:24:12Z","abstract_excerpt":"LLM-based multi-agent systems can fail even when planned actions are executed correctly because agents may misjudge their knowledge when evaluating plan feasibility, a phenomenon we term epistemic miscalibration in planning. Unlike execution errors, epistemic miscalibration is latent during planning, as generated plans can remain self-consistent and executable without observable errors; the miscalibration is also dynamic, as new information can alter feasibility assessments, potentially obscuring past miscalibration signals and causing them to recur over time. To address this, we propose the E"},"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":"2605.23414","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-22T09:24:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d26a7ead58c07fff9e0c7bac98db60cee02206b97d30a2045a1732add9a09d46","abstract_canon_sha256":"03ddbcacd3a8d2e58d76e5643809e48b11c3a8691c24575cff7300ffd8944ea1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-25T02:01:53.276538Z","signature_b64":"h0fAUEPvuuNuicXC90jfdFLz4fdhqAaHE1gEudhfq2HLbfI2CsFQ3RCSOkO0nV7+ho+FOqeNq9fmve1GO9mmAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6aea82e85eeb58435b19d49747a8a28f85427d213930a57abe62bc417f39c919","last_reissued_at":"2026-05-25T02:01:53.275948Z","signature_status":"signed_v1","first_computed_at":"2026-05-25T02:01:53.275948Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Lanjun Wang, Shilong Jin, Zehao Wang, Zhao Cao","submitted_at":"2026-05-22T09:24:12Z","abstract_excerpt":"LLM-based multi-agent systems can fail even when planned actions are executed correctly because agents may misjudge their knowledge when evaluating plan feasibility, a phenomenon we term epistemic miscalibration in planning. Unlike execution errors, epistemic miscalibration is latent during planning, as generated plans can remain self-consistent and executable without observable errors; the miscalibration is also dynamic, as new information can alter feasibility assessments, potentially obscuring past miscalibration signals and causing them to recur over time. To address this, we propose the E"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23414","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/2605.23414/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":"2605.23414","created_at":"2026-05-25T02:01:53.276054+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.23414v1","created_at":"2026-05-25T02:01:53.276054+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23414","created_at":"2026-05-25T02:01:53.276054+00:00"},{"alias_kind":"pith_short_12","alias_value":"NLVIF2C65NME","created_at":"2026-05-25T02:01:53.276054+00:00"},{"alias_kind":"pith_short_16","alias_value":"NLVIF2C65NMEGWYZ","created_at":"2026-05-25T02:01:53.276054+00:00"},{"alias_kind":"pith_short_8","alias_value":"NLVIF2C6","created_at":"2026-05-25T02:01:53.276054+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/NLVIF2C65NMEGWYZ2SLUPKFCR6","json":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6.json","graph_json":"https://pith.science/api/pith-number/NLVIF2C65NMEGWYZ2SLUPKFCR6/graph.json","events_json":"https://pith.science/api/pith-number/NLVIF2C65NMEGWYZ2SLUPKFCR6/events.json","paper":"https://pith.science/paper/NLVIF2C6"},"agent_actions":{"view_html":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6","download_json":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6.json","view_paper":"https://pith.science/paper/NLVIF2C6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.23414&json=true","fetch_graph":"https://pith.science/api/pith-number/NLVIF2C65NMEGWYZ2SLUPKFCR6/graph.json","fetch_events":"https://pith.science/api/pith-number/NLVIF2C65NMEGWYZ2SLUPKFCR6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6/action/storage_attestation","attest_author":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6/action/author_attestation","sign_citation":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6/action/citation_signature","submit_replication":"https://pith.science/pith/NLVIF2C65NMEGWYZ2SLUPKFCR6/action/replication_record"}},"created_at":"2026-05-25T02:01:53.276054+00:00","updated_at":"2026-05-25T02:01:53.276054+00:00"}