{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:53N4BT7IE3UXZX3YSQHJVPW4FQ","short_pith_number":"pith:53N4BT7I","canonical_record":{"source":{"id":"2602.12244","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-12T18:28:28Z","cross_cats_sorted":[],"title_canon_sha256":"c3f85823fbc0baba8dfe641c7c452c7e2181711b557a8fda235b2e5f96ae05e4","abstract_canon_sha256":"d645b8f0c0d77ea39c9de083f148321e6c10a7c26cb9209b9295c7e96de2cbc1"},"schema_version":"1.0"},"canonical_sha256":"eedbc0cfe826e97cdf78940e9abedc2c3f025b021394454b4310dc6b96f54603","source":{"kind":"arxiv","id":"2602.12244","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.12244","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"arxiv_version","alias_value":"2602.12244v2","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.12244","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"pith_short_12","alias_value":"53N4BT7IE3UX","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"53N4BT7IE3UXZX3Y","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"53N4BT7I","created_at":"2026-08-04T00:31:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:53N4BT7IE3UXZX3YSQHJVPW4FQ","target":"record","payload":{"canonical_record":{"source":{"id":"2602.12244","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-12T18:28:28Z","cross_cats_sorted":[],"title_canon_sha256":"c3f85823fbc0baba8dfe641c7c452c7e2181711b557a8fda235b2e5f96ae05e4","abstract_canon_sha256":"d645b8f0c0d77ea39c9de083f148321e6c10a7c26cb9209b9295c7e96de2cbc1"},"schema_version":"1.0"},"canonical_sha256":"eedbc0cfe826e97cdf78940e9abedc2c3f025b021394454b4310dc6b96f54603","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T00:31:12.546905Z","signature_b64":"CrzLC5yqVkK+9qYVBsvm+dlNyW9XzmbmOn2FNEQz6D0jBOd1PZTOi5AVSXPAEFpDfk3iOnLuKYYgECkucRNJAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eedbc0cfe826e97cdf78940e9abedc2c3f025b021394454b4310dc6b96f54603","last_reissued_at":"2026-08-04T00:31:12.545390Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T00:31:12.545390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.12244","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-04T00:31:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aR1ZBYJNM6v3cX67rxO0zczsRN2C2giEpeV5ryqnjCAFWtEfNWC8yvejPr5x1zerSRifFebJ3bZhUTzEnWh6Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T11:15:40.400768Z"},"content_sha256":"1105944ef9a5ee66bcb3ad1551a29de02093a66085327e6eebda940ae71446bc","schema_version":"1.0","event_id":"sha256:1105944ef9a5ee66bcb3ad1551a29de02093a66085327e6eebda940ae71446bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:53N4BT7IE3UXZX3YSQHJVPW4FQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Any House Any Task: Scalable Long-Horizon Planning for Abstract Human Tasks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cewu Lu, Panpan Cai, Rengming Huang, Yang Li, Zhihong Liu","submitted_at":"2026-02-12T18:28:28Z","abstract_excerpt":"Open world language conditioned task planning is crucial for robots operating in large-scale household environments. While many recent works attempt to address this problem using Large Language Models (LLMs) via prompting or training, a key challenge remains scalability. Performance often degrades rapidly with increasing environment size, plan length, instruction ambiguity, and constraint complexity. In this work, we propose Any House Any Task (AHAT), a household task planner optimized for long-horizon planning in large environments given ambiguous human instructions. At its core, AHAT utilize"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.12244","kind":"arxiv","version":2},"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/2602.12244/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-04T00:31:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fPWdyFIHVZVi+Qvwz8dh1uPI1MesljWZGizdX6WXymYNLtxfVJK7l2Q3dKbCgVopxFXfDWeBVYiP3ue2alSOCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T11:15:40.401186Z"},"content_sha256":"fdb21f8e1122053a330f64728ce9e8b2a69f3a9e700431894a8704a79f353457","schema_version":"1.0","event_id":"sha256:fdb21f8e1122053a330f64728ce9e8b2a69f3a9e700431894a8704a79f353457"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/53N4BT7IE3UXZX3YSQHJVPW4FQ/bundle.json","state_url":"https://pith.science/pith/53N4BT7IE3UXZX3YSQHJVPW4FQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/53N4BT7IE3UXZX3YSQHJVPW4FQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T11:15:40Z","links":{"resolver":"https://pith.science/pith/53N4BT7IE3UXZX3YSQHJVPW4FQ","bundle":"https://pith.science/pith/53N4BT7IE3UXZX3YSQHJVPW4FQ/bundle.json","state":"https://pith.science/pith/53N4BT7IE3UXZX3YSQHJVPW4FQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/53N4BT7IE3UXZX3YSQHJVPW4FQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:53N4BT7IE3UXZX3YSQHJVPW4FQ","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":"d645b8f0c0d77ea39c9de083f148321e6c10a7c26cb9209b9295c7e96de2cbc1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-12T18:28:28Z","title_canon_sha256":"c3f85823fbc0baba8dfe641c7c452c7e2181711b557a8fda235b2e5f96ae05e4"},"schema_version":"1.0","source":{"id":"2602.12244","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.12244","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"arxiv_version","alias_value":"2602.12244v2","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.12244","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"pith_short_12","alias_value":"53N4BT7IE3UX","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"53N4BT7IE3UXZX3Y","created_at":"2026-08-04T00:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"53N4BT7I","created_at":"2026-08-04T00:31:12Z"}],"graph_snapshots":[{"event_id":"sha256:fdb21f8e1122053a330f64728ce9e8b2a69f3a9e700431894a8704a79f353457","target":"graph","created_at":"2026-08-04T00:31:12Z","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/2602.12244/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Open world language conditioned task planning is crucial for robots operating in large-scale household environments. While many recent works attempt to address this problem using Large Language Models (LLMs) via prompting or training, a key challenge remains scalability. Performance often degrades rapidly with increasing environment size, plan length, instruction ambiguity, and constraint complexity. In this work, we propose Any House Any Task (AHAT), a household task planner optimized for long-horizon planning in large environments given ambiguous human instructions. At its core, AHAT utilize","authors_text":"Cewu Lu, Panpan Cai, Rengming Huang, Yang Li, Zhihong Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-12T18:28:28Z","title":"Any House Any Task: Scalable Long-Horizon Planning for Abstract Human Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.12244","kind":"arxiv","version":2},"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":"sha256:1105944ef9a5ee66bcb3ad1551a29de02093a66085327e6eebda940ae71446bc","target":"record","created_at":"2026-08-04T00:31:12Z","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":"d645b8f0c0d77ea39c9de083f148321e6c10a7c26cb9209b9295c7e96de2cbc1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-12T18:28:28Z","title_canon_sha256":"c3f85823fbc0baba8dfe641c7c452c7e2181711b557a8fda235b2e5f96ae05e4"},"schema_version":"1.0","source":{"id":"2602.12244","kind":"arxiv","version":2}},"canonical_sha256":"eedbc0cfe826e97cdf78940e9abedc2c3f025b021394454b4310dc6b96f54603","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eedbc0cfe826e97cdf78940e9abedc2c3f025b021394454b4310dc6b96f54603","first_computed_at":"2026-08-04T00:31:12.545390Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T00:31:12.545390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CrzLC5yqVkK+9qYVBsvm+dlNyW9XzmbmOn2FNEQz6D0jBOd1PZTOi5AVSXPAEFpDfk3iOnLuKYYgECkucRNJAA==","signature_status":"signed_v1","signed_at":"2026-08-04T00:31:12.546905Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.12244","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1105944ef9a5ee66bcb3ad1551a29de02093a66085327e6eebda940ae71446bc","sha256:fdb21f8e1122053a330f64728ce9e8b2a69f3a9e700431894a8704a79f353457"],"state_sha256":"a5591b521a9c75c3c556b343cdf318cca798df21ce54969076189ae1329e701e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ETTpgXpNfID7JN2dfL3k0XkAHXjwHC4DkAWu6DU/leHVJ0UEI5ncXHFUuuMgn9+TN0ispj7rDaH/fTkgRF2BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T11:15:40.406226Z","bundle_sha256":"9e6dc1d1c5b7dd3d0d574647da636da05f5f50f54c0ff94dd66b4361739c1700"}}