{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:D4OQWF5VTCOPFTT5UKIMOFL2GE","short_pith_number":"pith:D4OQWF5V","canonical_record":{"source":{"id":"2411.01284","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-02T15:28:06Z","cross_cats_sorted":[],"title_canon_sha256":"9daf964238a3e0b7c7107fdf03936f3e5372194c92618c6dee785bf6a1c5eb3a","abstract_canon_sha256":"cc63f6bad8516dbbcb38986a46a07af3184810d8c90b0022436384c4d219e835"},"schema_version":"1.0"},"canonical_sha256":"1f1d0b17b5989cf2ce7da290c7157a313c67b8cb204207751c58e8b174ed5702","source":{"kind":"arxiv","id":"2411.01284","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.01284","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"arxiv_version","alias_value":"2411.01284v1","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.01284","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"pith_short_12","alias_value":"D4OQWF5VTCOP","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"pith_short_16","alias_value":"D4OQWF5VTCOPFTT5","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"pith_short_8","alias_value":"D4OQWF5V","created_at":"2026-07-05T09:30:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:D4OQWF5VTCOPFTT5UKIMOFL2GE","target":"record","payload":{"canonical_record":{"source":{"id":"2411.01284","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-02T15:28:06Z","cross_cats_sorted":[],"title_canon_sha256":"9daf964238a3e0b7c7107fdf03936f3e5372194c92618c6dee785bf6a1c5eb3a","abstract_canon_sha256":"cc63f6bad8516dbbcb38986a46a07af3184810d8c90b0022436384c4d219e835"},"schema_version":"1.0"},"canonical_sha256":"1f1d0b17b5989cf2ce7da290c7157a313c67b8cb204207751c58e8b174ed5702","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:30:27.943227Z","signature_b64":"m2/rByBSo8iH+5hOXjqIAANK9bXqSwb+vUIXTIiWIOPeMdZBc4DSvnXsIbLBfxVUEKIj3K0wFQJdTF4MneaFAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f1d0b17b5989cf2ce7da290c7157a313c67b8cb204207751c58e8b174ed5702","last_reissued_at":"2026-07-05T09:30:27.942783Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:30:27.942783Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.01284","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:30:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZMBgyFNVnFsMRJTyKp7ONn1T6jZEOX2n4MMWgVMN6G46rySreVVWgxTvCXbgBf8oXwXeffOxUPaTHIetouy+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T02:11:21.316541Z"},"content_sha256":"2c86fabba73ee71b495db6e7838e3d396a8bec69c259de6ec3867286f820e264","schema_version":"1.0","event_id":"sha256:2c86fabba73ee71b495db6e7838e3d396a8bec69c259de6ec3867286f820e264"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:D4OQWF5VTCOPFTT5UKIMOFL2GE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Task-Oriented Hierarchical Object Decomposition for Visuomotor Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Bernadette Bucher, Dinesh Jayaraman, Jianing Qian, Yunshuang Li","submitted_at":"2024-11-02T15:28:06Z","abstract_excerpt":"Good pre-trained visual representations could enable robots to learn visuomotor policy efficiently. Still, existing representations take a one-size-fits-all-tasks approach that comes with two important drawbacks: (1) Being completely task-agnostic, these representations cannot effectively ignore any task-irrelevant information in the scene, and (2) They often lack the representational capacity to handle unconstrained/complex real-world scenes. Instead, we propose to train a large combinatorial family of representations organized by scene entities: objects and object parts. This hierarchical ob"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.01284","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/2411.01284/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":"2026-07-05T09:30:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CiHls9OqYQWAorq8wgHOHA2tdHPkgj207A+aSyHH+smPT4TtwLqD7WyIIC61f3lkadRWK7QgB7SktwoX96LsBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T02:11:21.317164Z"},"content_sha256":"aa8830999cc61c7c41f1d89253f70dc9593e4c9dd169c314c47dbb09056c93e8","schema_version":"1.0","event_id":"sha256:aa8830999cc61c7c41f1d89253f70dc9593e4c9dd169c314c47dbb09056c93e8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D4OQWF5VTCOPFTT5UKIMOFL2GE/bundle.json","state_url":"https://pith.science/pith/D4OQWF5VTCOPFTT5UKIMOFL2GE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D4OQWF5VTCOPFTT5UKIMOFL2GE/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":"2026-08-06T02:11:21Z","links":{"resolver":"https://pith.science/pith/D4OQWF5VTCOPFTT5UKIMOFL2GE","bundle":"https://pith.science/pith/D4OQWF5VTCOPFTT5UKIMOFL2GE/bundle.json","state":"https://pith.science/pith/D4OQWF5VTCOPFTT5UKIMOFL2GE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D4OQWF5VTCOPFTT5UKIMOFL2GE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:D4OQWF5VTCOPFTT5UKIMOFL2GE","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":"cc63f6bad8516dbbcb38986a46a07af3184810d8c90b0022436384c4d219e835","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-02T15:28:06Z","title_canon_sha256":"9daf964238a3e0b7c7107fdf03936f3e5372194c92618c6dee785bf6a1c5eb3a"},"schema_version":"1.0","source":{"id":"2411.01284","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.01284","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"arxiv_version","alias_value":"2411.01284v1","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.01284","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"pith_short_12","alias_value":"D4OQWF5VTCOP","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"pith_short_16","alias_value":"D4OQWF5VTCOPFTT5","created_at":"2026-07-05T09:30:27Z"},{"alias_kind":"pith_short_8","alias_value":"D4OQWF5V","created_at":"2026-07-05T09:30:27Z"}],"graph_snapshots":[{"event_id":"sha256:aa8830999cc61c7c41f1d89253f70dc9593e4c9dd169c314c47dbb09056c93e8","target":"graph","created_at":"2026-07-05T09:30:27Z","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/2411.01284/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Good pre-trained visual representations could enable robots to learn visuomotor policy efficiently. Still, existing representations take a one-size-fits-all-tasks approach that comes with two important drawbacks: (1) Being completely task-agnostic, these representations cannot effectively ignore any task-irrelevant information in the scene, and (2) They often lack the representational capacity to handle unconstrained/complex real-world scenes. Instead, we propose to train a large combinatorial family of representations organized by scene entities: objects and object parts. This hierarchical ob","authors_text":"Bernadette Bucher, Dinesh Jayaraman, Jianing Qian, Yunshuang Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-02T15:28:06Z","title":"Task-Oriented Hierarchical Object Decomposition for Visuomotor Control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.01284","kind":"arxiv","version":1},"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":"sha256:2c86fabba73ee71b495db6e7838e3d396a8bec69c259de6ec3867286f820e264","target":"record","created_at":"2026-07-05T09:30:27Z","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":"cc63f6bad8516dbbcb38986a46a07af3184810d8c90b0022436384c4d219e835","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-02T15:28:06Z","title_canon_sha256":"9daf964238a3e0b7c7107fdf03936f3e5372194c92618c6dee785bf6a1c5eb3a"},"schema_version":"1.0","source":{"id":"2411.01284","kind":"arxiv","version":1}},"canonical_sha256":"1f1d0b17b5989cf2ce7da290c7157a313c67b8cb204207751c58e8b174ed5702","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f1d0b17b5989cf2ce7da290c7157a313c67b8cb204207751c58e8b174ed5702","first_computed_at":"2026-07-05T09:30:27.942783Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:30:27.942783Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m2/rByBSo8iH+5hOXjqIAANK9bXqSwb+vUIXTIiWIOPeMdZBc4DSvnXsIbLBfxVUEKIj3K0wFQJdTF4MneaFAg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:30:27.943227Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.01284","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c86fabba73ee71b495db6e7838e3d396a8bec69c259de6ec3867286f820e264","sha256:aa8830999cc61c7c41f1d89253f70dc9593e4c9dd169c314c47dbb09056c93e8"],"state_sha256":"b5d3bf62f2515fdb5b5052940cd602392c0288cb8d3923d307a25f93491a75dd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hz1wie8oOnmJxxua3vEtT+oKO1lAO1jyfAQ2PF9Un4TQfFPO+By3/hKx2dGYHMF+TfHAx+6lp9bwzTMa+vcQAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T02:11:21.321337Z","bundle_sha256":"83ca2985d10da4514dbb8240b5c55d28b4a191bdee347021909841b197ca81c8"}}