{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:WLW3AU42UYTDLU6TSGLE5L6SZM","short_pith_number":"pith:WLW3AU42","canonical_record":{"source":{"id":"2305.05658","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-05-09T17:52:59Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CV","cs.LG"],"title_canon_sha256":"001998eb0a63dc9a01498fb01e9e1d9ca404252d82765e0b687d0925105672df","abstract_canon_sha256":"e355fb7a07c4999d1562577e3d2aa7f1aded4f6111848f5615ae390943a6d89d"},"schema_version":"1.0"},"canonical_sha256":"b2edb0539aa62635d3d391964eafd2cb071c826c3f464b3495e56afbf15f2479","source":{"kind":"arxiv","id":"2305.05658","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.05658","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"arxiv_version","alias_value":"2305.05658v2","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.05658","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"pith_short_12","alias_value":"WLW3AU42UYTD","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"pith_short_16","alias_value":"WLW3AU42UYTDLU6T","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"pith_short_8","alias_value":"WLW3AU42","created_at":"2026-07-05T07:13:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:WLW3AU42UYTDLU6TSGLE5L6SZM","target":"record","payload":{"canonical_record":{"source":{"id":"2305.05658","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-05-09T17:52:59Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CV","cs.LG"],"title_canon_sha256":"001998eb0a63dc9a01498fb01e9e1d9ca404252d82765e0b687d0925105672df","abstract_canon_sha256":"e355fb7a07c4999d1562577e3d2aa7f1aded4f6111848f5615ae390943a6d89d"},"schema_version":"1.0"},"canonical_sha256":"b2edb0539aa62635d3d391964eafd2cb071c826c3f464b3495e56afbf15f2479","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:13:41.809761Z","signature_b64":"Azl/PFFcWKrBY1MOhrhn3MiBvX1tC5G+PXsSwol8T2q/dGQYpKrrxjpWoFJnk4DG71yl1p0OANghsHgcxVrbCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b2edb0539aa62635d3d391964eafd2cb071c826c3f464b3495e56afbf15f2479","last_reissued_at":"2026-07-05T07:13:41.809177Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:13:41.809177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.05658","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":"2026-07-05T07:13:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E9ggp5ekft9jSiRcuLK4hjy4L/CtMQiiH0RZXeq2mHQ5EjkklifLFGXdEbueSTUPWmKfVci4cosa8zw1qXfEBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:27:11.242035Z"},"content_sha256":"7c6c1ef31db46c9949f18a9e387182e4852f76c22a52bf6e83197f737ba935c9","schema_version":"1.0","event_id":"sha256:7c6c1ef31db46c9949f18a9e387182e4852f76c22a52bf6e83197f737ba935c9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:WLW3AU42UYTDLU6TSGLE5L6SZM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TidyBot: Personalized Robot Assistance with Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.CV","cs.LG"],"primary_cat":"cs.RO","authors_text":"Adam Kan, Andy Zeng, Jeannette Bohg, Jimmy Wu, Marion Lepert, Rika Antonova, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser","submitted_at":"2023-05-09T17:52:59Z","abstract_excerpt":"For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios. In this work, we investigate personalization of household cleanup with robots that can tidy up rooms by picking up objects and putting them away. A key challenge is determining the proper place to put each object, as people's preferences can vary greatly depending on personal taste or cultural background. For instance, one person may prefer storing shirts in the drawer, while another may prefer them on the shelf. We aim to build systems that can learn "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.05658","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/2305.05658/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":"2026-07-05T07:13:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ly5FdUjJVNE/rSHUHiiPJfDG0xnHYdbeYZhQDuJqrMWvlGqjgMp/GQdFJL29LY3eoMQpZ3NA/DbdXuVo/AUVAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:27:11.242638Z"},"content_sha256":"814c3c049314833693b44c0c98158027cee68c2e06f1fe0f26dfc23e8312d677","schema_version":"1.0","event_id":"sha256:814c3c049314833693b44c0c98158027cee68c2e06f1fe0f26dfc23e8312d677"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WLW3AU42UYTDLU6TSGLE5L6SZM/bundle.json","state_url":"https://pith.science/pith/WLW3AU42UYTDLU6TSGLE5L6SZM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WLW3AU42UYTDLU6TSGLE5L6SZM/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":"2026-08-09T17:27:11Z","links":{"resolver":"https://pith.science/pith/WLW3AU42UYTDLU6TSGLE5L6SZM","bundle":"https://pith.science/pith/WLW3AU42UYTDLU6TSGLE5L6SZM/bundle.json","state":"https://pith.science/pith/WLW3AU42UYTDLU6TSGLE5L6SZM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WLW3AU42UYTDLU6TSGLE5L6SZM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WLW3AU42UYTDLU6TSGLE5L6SZM","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":"e355fb7a07c4999d1562577e3d2aa7f1aded4f6111848f5615ae390943a6d89d","cross_cats_sorted":["cs.AI","cs.CL","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-05-09T17:52:59Z","title_canon_sha256":"001998eb0a63dc9a01498fb01e9e1d9ca404252d82765e0b687d0925105672df"},"schema_version":"1.0","source":{"id":"2305.05658","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.05658","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"arxiv_version","alias_value":"2305.05658v2","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.05658","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"pith_short_12","alias_value":"WLW3AU42UYTD","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"pith_short_16","alias_value":"WLW3AU42UYTDLU6T","created_at":"2026-07-05T07:13:41Z"},{"alias_kind":"pith_short_8","alias_value":"WLW3AU42","created_at":"2026-07-05T07:13:41Z"}],"graph_snapshots":[{"event_id":"sha256:814c3c049314833693b44c0c98158027cee68c2e06f1fe0f26dfc23e8312d677","target":"graph","created_at":"2026-07-05T07:13:41Z","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/2305.05658/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios. In this work, we investigate personalization of household cleanup with robots that can tidy up rooms by picking up objects and putting them away. A key challenge is determining the proper place to put each object, as people's preferences can vary greatly depending on personal taste or cultural background. For instance, one person may prefer storing shirts in the drawer, while another may prefer them on the shelf. We aim to build systems that can learn ","authors_text":"Adam Kan, Andy Zeng, Jeannette Bohg, Jimmy Wu, Marion Lepert, Rika Antonova, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser","cross_cats":["cs.AI","cs.CL","cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-05-09T17:52:59Z","title":"TidyBot: Personalized Robot Assistance with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.05658","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":"sha256:7c6c1ef31db46c9949f18a9e387182e4852f76c22a52bf6e83197f737ba935c9","target":"record","created_at":"2026-07-05T07:13:41Z","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":"e355fb7a07c4999d1562577e3d2aa7f1aded4f6111848f5615ae390943a6d89d","cross_cats_sorted":["cs.AI","cs.CL","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-05-09T17:52:59Z","title_canon_sha256":"001998eb0a63dc9a01498fb01e9e1d9ca404252d82765e0b687d0925105672df"},"schema_version":"1.0","source":{"id":"2305.05658","kind":"arxiv","version":2}},"canonical_sha256":"b2edb0539aa62635d3d391964eafd2cb071c826c3f464b3495e56afbf15f2479","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b2edb0539aa62635d3d391964eafd2cb071c826c3f464b3495e56afbf15f2479","first_computed_at":"2026-07-05T07:13:41.809177Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:13:41.809177Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Azl/PFFcWKrBY1MOhrhn3MiBvX1tC5G+PXsSwol8T2q/dGQYpKrrxjpWoFJnk4DG71yl1p0OANghsHgcxVrbCg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:13:41.809761Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.05658","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c6c1ef31db46c9949f18a9e387182e4852f76c22a52bf6e83197f737ba935c9","sha256:814c3c049314833693b44c0c98158027cee68c2e06f1fe0f26dfc23e8312d677"],"state_sha256":"79906fca474ff116a5808b5363d383cf5f20b28a924254ff00fe92a8d70fccea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z4+ZdridI6IjCw1WGwA3ti1dl0HEN1Z64bZvO6yzN8Nzq2FU1x+WSqUiFOqrrlZ1h9MXUobTWW5YBlwlIh/cAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T17:27:11.246883Z","bundle_sha256":"6c3e4626e5c2ed02afb7570116a33282eaa82c042c24a90eb9275092c012c07d"}}