{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:5RIMJNEHUZG6ZQTSFMHHY6KPBU","short_pith_number":"pith:5RIMJNEH","canonical_record":{"source":{"id":"1904.05538","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-04-11T05:20:57Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"0602d3f54c00ba55974126943e17ba4dab4c0f03f226833761d0c690b763fc21","abstract_canon_sha256":"33f8ff8d6924a4567ab8f102e36ae053e9da3115f4d9ab33821eaa66bd17cb85"},"schema_version":"1.0"},"canonical_sha256":"ec50c4b487a64decc2722b0e7c794f0d206f4b321d241a698e6567808745e7a5","source":{"kind":"arxiv","id":"1904.05538","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.05538","created_at":"2026-05-17T23:48:49Z"},{"alias_kind":"arxiv_version","alias_value":"1904.05538v1","created_at":"2026-05-17T23:48:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05538","created_at":"2026-05-17T23:48:49Z"},{"alias_kind":"pith_short_12","alias_value":"5RIMJNEHUZG6","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"5RIMJNEHUZG6ZQTS","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"5RIMJNEH","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:5RIMJNEHUZG6ZQTSFMHHY6KPBU","target":"record","payload":{"canonical_record":{"source":{"id":"1904.05538","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-04-11T05:20:57Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"0602d3f54c00ba55974126943e17ba4dab4c0f03f226833761d0c690b763fc21","abstract_canon_sha256":"33f8ff8d6924a4567ab8f102e36ae053e9da3115f4d9ab33821eaa66bd17cb85"},"schema_version":"1.0"},"canonical_sha256":"ec50c4b487a64decc2722b0e7c794f0d206f4b321d241a698e6567808745e7a5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:49.218636Z","signature_b64":"2N4b1JP3BvqC+/ROmTqcaZyNROntYF7cBLG7TQcZydBZLIpwdfNTK9nssGSSMc1OR/7Kj3VPK/BLGpEhmn2vAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ec50c4b487a64decc2722b0e7c794f0d206f4b321d241a698e6567808745e7a5","last_reissued_at":"2026-05-17T23:48:49.218037Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:49.218037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.05538","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":"2026-05-17T23:48:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XgvS9aYaxXQ/h0zWYVxvBT2YIYkX1EfJTp+IzLcU46p1n/pQiOw5PzJSCCqsDVgkbL+K9tC4tx/7+3bv7yt4BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T17:36:38.244887Z"},"content_sha256":"4bc2212854ed222459e47734d13ad796ecb6541fff476b2393b6ae91ad9b51e1","schema_version":"1.0","event_id":"sha256:4bc2212854ed222459e47734d13ad796ecb6541fff476b2393b6ae91ad9b51e1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:5RIMJNEHUZG6ZQTSFMHHY6KPBU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Annie Xie, Chelsea Finn, Frederik Ebert, Sergey Levine","submitted_at":"2019-04-11T05:20:57Z","abstract_excerpt":"Machine learning techniques have enabled robots to learn narrow, yet complex tasks and also perform broad, yet simple skills with a wide variety of objects. However, learning a model that can both perform complex tasks and generalize to previously unseen objects and goals remains a significant challenge. We study this challenge in the context of \"improvisational\" tool use: a robot is presented with novel objects and a user-specified goal (e.g., sweep some clutter into the dustpan), and must figure out, using only raw image observations, how to accomplish the goal using the available objects as"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05538","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":""},"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":"2026-05-17T23:48:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EV3ArKK/GdNMGSbfaU7XdQLSZBxqdBdSx1lyrpOQaB786Bhsx51pqaWAARy+8LRQ3dhW90hwTR9s6u5IJRs6Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T17:36:38.245243Z"},"content_sha256":"b1e3e3b4ae871650b48c3920efd0208eb68173a6cdc734dbca847252ecaa4144","schema_version":"1.0","event_id":"sha256:b1e3e3b4ae871650b48c3920efd0208eb68173a6cdc734dbca847252ecaa4144"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5RIMJNEHUZG6ZQTSFMHHY6KPBU/bundle.json","state_url":"https://pith.science/pith/5RIMJNEHUZG6ZQTSFMHHY6KPBU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5RIMJNEHUZG6ZQTSFMHHY6KPBU/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":"2026-06-01T17:36:38Z","links":{"resolver":"https://pith.science/pith/5RIMJNEHUZG6ZQTSFMHHY6KPBU","bundle":"https://pith.science/pith/5RIMJNEHUZG6ZQTSFMHHY6KPBU/bundle.json","state":"https://pith.science/pith/5RIMJNEHUZG6ZQTSFMHHY6KPBU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5RIMJNEHUZG6ZQTSFMHHY6KPBU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:5RIMJNEHUZG6ZQTSFMHHY6KPBU","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":"33f8ff8d6924a4567ab8f102e36ae053e9da3115f4d9ab33821eaa66bd17cb85","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-04-11T05:20:57Z","title_canon_sha256":"0602d3f54c00ba55974126943e17ba4dab4c0f03f226833761d0c690b763fc21"},"schema_version":"1.0","source":{"id":"1904.05538","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.05538","created_at":"2026-05-17T23:48:49Z"},{"alias_kind":"arxiv_version","alias_value":"1904.05538v1","created_at":"2026-05-17T23:48:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05538","created_at":"2026-05-17T23:48:49Z"},{"alias_kind":"pith_short_12","alias_value":"5RIMJNEHUZG6","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"5RIMJNEHUZG6ZQTS","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"5RIMJNEH","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:b1e3e3b4ae871650b48c3920efd0208eb68173a6cdc734dbca847252ecaa4144","target":"graph","created_at":"2026-05-17T23:48:49Z","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"},"paper":{"abstract_excerpt":"Machine learning techniques have enabled robots to learn narrow, yet complex tasks and also perform broad, yet simple skills with a wide variety of objects. However, learning a model that can both perform complex tasks and generalize to previously unseen objects and goals remains a significant challenge. We study this challenge in the context of \"improvisational\" tool use: a robot is presented with novel objects and a user-specified goal (e.g., sweep some clutter into the dustpan), and must figure out, using only raw image observations, how to accomplish the goal using the available objects as","authors_text":"Annie Xie, Chelsea Finn, Frederik Ebert, Sergey Levine","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-04-11T05:20:57Z","title":"Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05538","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":"sha256:4bc2212854ed222459e47734d13ad796ecb6541fff476b2393b6ae91ad9b51e1","target":"record","created_at":"2026-05-17T23:48:49Z","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":"33f8ff8d6924a4567ab8f102e36ae053e9da3115f4d9ab33821eaa66bd17cb85","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-04-11T05:20:57Z","title_canon_sha256":"0602d3f54c00ba55974126943e17ba4dab4c0f03f226833761d0c690b763fc21"},"schema_version":"1.0","source":{"id":"1904.05538","kind":"arxiv","version":1}},"canonical_sha256":"ec50c4b487a64decc2722b0e7c794f0d206f4b321d241a698e6567808745e7a5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ec50c4b487a64decc2722b0e7c794f0d206f4b321d241a698e6567808745e7a5","first_computed_at":"2026-05-17T23:48:49.218037Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:49.218037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2N4b1JP3BvqC+/ROmTqcaZyNROntYF7cBLG7TQcZydBZLIpwdfNTK9nssGSSMc1OR/7Kj3VPK/BLGpEhmn2vAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:49.218636Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.05538","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4bc2212854ed222459e47734d13ad796ecb6541fff476b2393b6ae91ad9b51e1","sha256:b1e3e3b4ae871650b48c3920efd0208eb68173a6cdc734dbca847252ecaa4144"],"state_sha256":"a7cf8d31c7a3be25f3191f458e9f52331d084e8d01dc0d5baae41fff1185db91"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0f0WgCVLRQwHxzASO+9y53CoWqJNp1WOtBTE9n5AvFedx2sVkWcX2IMbz/UmVUTWzJ4jvDYqxBlpNv0pcgl1Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T17:36:38.247194Z","bundle_sha256":"b359fe0acdec20b0526df318dad8a593c3372d09cf67ff9937419d665e9b161a"}}