{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:YSDD6BMRIEH5GYUYYG25UWGWH6","short_pith_number":"pith:YSDD6BMR","schema_version":"1.0","canonical_sha256":"c4863f0591410fd36298c1b5da58d63f9450344cc55f142cca3eff476a2e583b","source":{"kind":"arxiv","id":"2606.25404","version":1},"attestation_state":"computed","paper":{"title":"HEART: Coordination of Heterogeneous Expert Agents for Physically Grounded Robotic Task Planning","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Changjoo Nam, Junho Lee, Moonjeong Kang, Nayoung Kim, Seabin Lee, Wonjong Lee","submitted_at":"2026-06-24T05:02:37Z","abstract_excerpt":"Large Language Models (LLMs) can reason over complex instructions but often fail to satisfy the physical and spatial constraints required for robotic task planning. Recent LLM-based planners directly translate text into action sequences, yet they lack structured reasoning about feasibility, reachability, and logical order, resulting in invalid or incomplete plans. We present a heterogeneous multi-LLM framework that decomposes instructions into atomic reasoning tasks and allocates them to role-specialized expert agents under a token budget for real-world computational and communicational constr"},"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":"2606.25404","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2026-06-24T05:02:37Z","cross_cats_sorted":[],"title_canon_sha256":"a8e4f1c53b37879e448c60d439035dcf52009129b1133536ed11f98e703cc72b","abstract_canon_sha256":"777955d4a07e787022d708a95d76bde180e07110c3734d82f46b9027096053c7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T01:18:04.479705Z","signature_b64":"CeKbh+h7TNMnMMJYK55AmBLMjj85Rx+5SEpCAhpqMv0B6+9JqmauvdJqnKVS1wW850fYjM1Dyk/RDSoYmbFTBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c4863f0591410fd36298c1b5da58d63f9450344cc55f142cca3eff476a2e583b","last_reissued_at":"2026-06-25T01:18:04.479285Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T01:18:04.479285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"HEART: Coordination of Heterogeneous Expert Agents for Physically Grounded Robotic Task Planning","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Changjoo Nam, Junho Lee, Moonjeong Kang, Nayoung Kim, Seabin Lee, Wonjong Lee","submitted_at":"2026-06-24T05:02:37Z","abstract_excerpt":"Large Language Models (LLMs) can reason over complex instructions but often fail to satisfy the physical and spatial constraints required for robotic task planning. Recent LLM-based planners directly translate text into action sequences, yet they lack structured reasoning about feasibility, reachability, and logical order, resulting in invalid or incomplete plans. We present a heterogeneous multi-LLM framework that decomposes instructions into atomic reasoning tasks and allocates them to role-specialized expert agents under a token budget for real-world computational and communicational constr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25404","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/2606.25404/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":"2606.25404","created_at":"2026-06-25T01:18:04.479362+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.25404v1","created_at":"2026-06-25T01:18:04.479362+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25404","created_at":"2026-06-25T01:18:04.479362+00:00"},{"alias_kind":"pith_short_12","alias_value":"YSDD6BMRIEH5","created_at":"2026-06-25T01:18:04.479362+00:00"},{"alias_kind":"pith_short_16","alias_value":"YSDD6BMRIEH5GYUY","created_at":"2026-06-25T01:18:04.479362+00:00"},{"alias_kind":"pith_short_8","alias_value":"YSDD6BMR","created_at":"2026-06-25T01:18:04.479362+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/YSDD6BMRIEH5GYUYYG25UWGWH6","json":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6.json","graph_json":"https://pith.science/api/pith-number/YSDD6BMRIEH5GYUYYG25UWGWH6/graph.json","events_json":"https://pith.science/api/pith-number/YSDD6BMRIEH5GYUYYG25UWGWH6/events.json","paper":"https://pith.science/paper/YSDD6BMR"},"agent_actions":{"view_html":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6","download_json":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6.json","view_paper":"https://pith.science/paper/YSDD6BMR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.25404&json=true","fetch_graph":"https://pith.science/api/pith-number/YSDD6BMRIEH5GYUYYG25UWGWH6/graph.json","fetch_events":"https://pith.science/api/pith-number/YSDD6BMRIEH5GYUYYG25UWGWH6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6/action/storage_attestation","attest_author":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6/action/author_attestation","sign_citation":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6/action/citation_signature","submit_replication":"https://pith.science/pith/YSDD6BMRIEH5GYUYYG25UWGWH6/action/replication_record"}},"created_at":"2026-06-25T01:18:04.479362+00:00","updated_at":"2026-06-25T01:18:04.479362+00:00"}