{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:SFGGLXHRXLYRQE6SFZQNRR4G4X","short_pith_number":"pith:SFGGLXHR","canonical_record":{"source":{"id":"2310.12238","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-18T18:26:01Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"536474e63ffe11796c37d9d08099dbce9ff017a6d168f98b10bc97451a7f404a","abstract_canon_sha256":"501b02845cd21a9637a9093e4dbd3a527ee127f1ee9fef45f292d36d19c55b31"},"schema_version":"1.0"},"canonical_sha256":"914c65dcf1baf11813d22e60d8c786e5f22d00c8239f7653aedc88de5ef649bf","source":{"kind":"arxiv","id":"2310.12238","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.12238","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"arxiv_version","alias_value":"2310.12238v1","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.12238","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"pith_short_12","alias_value":"SFGGLXHRXLYR","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"pith_short_16","alias_value":"SFGGLXHRXLYRQE6S","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"pith_short_8","alias_value":"SFGGLXHR","created_at":"2026-07-05T07:02:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:SFGGLXHRXLYRQE6SFZQNRR4G4X","target":"record","payload":{"canonical_record":{"source":{"id":"2310.12238","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-18T18:26:01Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"536474e63ffe11796c37d9d08099dbce9ff017a6d168f98b10bc97451a7f404a","abstract_canon_sha256":"501b02845cd21a9637a9093e4dbd3a527ee127f1ee9fef45f292d36d19c55b31"},"schema_version":"1.0"},"canonical_sha256":"914c65dcf1baf11813d22e60d8c786e5f22d00c8239f7653aedc88de5ef649bf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:02:35.436375Z","signature_b64":"sQLrBQv6L227M1C2MG7VEQ21K8baRKIcMRXicUE+qprBiWb0ftg6UaDtUYOt0Yod+tfKqkv2br1mPCiXfm7qBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"914c65dcf1baf11813d22e60d8c786e5f22d00c8239f7653aedc88de5ef649bf","last_reissued_at":"2026-07-05T07:02:35.435905Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:02:35.435905Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.12238","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":"2026-07-05T07:02:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nM2nmJpIZWqxXXTKVRYat2HSPaa6SowMmnMbWFcjzXOrEgB7pEALcvJS87n/iQ5dsAT+6Vbn5dzBxi8/lnmNAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T00:40:57.255908Z"},"content_sha256":"870cd09612e126c2c9e902aedca3bdf3485b3c622c46c6277887f873e40a95f9","schema_version":"1.0","event_id":"sha256:870cd09612e126c2c9e902aedca3bdf3485b3c622c46c6277887f873e40a95f9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:SFGGLXHRXLYRQE6SFZQNRR4G4X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Few-Shot In-Context Imitation Learning via Implicit Graph Alignment","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Edward Johns, Vitalis Vosylius","submitted_at":"2023-10-18T18:26:01Z","abstract_excerpt":"Consider the following problem: given a few demonstrations of a task across a few different objects, how can a robot learn to perform that same task on new, previously unseen objects? This is challenging because the large variety of objects within a class makes it difficult to infer the task-relevant relationship between the new objects and the objects in the demonstrations. We address this by formulating imitation learning as a conditional alignment problem between graph representations of objects. Consequently, we show that this conditioning allows for in-context learning, where a robot can "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.12238","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/2310.12238/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":"2026-07-05T07:02:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PsnKKAFk/XRTWVH5KuJjiPDPq8oZJi+SSBuXBvfjDgWv3Az4SHGvAX9K1VPxc2XCvPmxROdzDyXTvqU64sm2Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T00:40:57.256815Z"},"content_sha256":"ad64e12576ba0a429ac4a159440044ab39b3411401bd5691c6f05575d722a8d6","schema_version":"1.0","event_id":"sha256:ad64e12576ba0a429ac4a159440044ab39b3411401bd5691c6f05575d722a8d6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SFGGLXHRXLYRQE6SFZQNRR4G4X/bundle.json","state_url":"https://pith.science/pith/SFGGLXHRXLYRQE6SFZQNRR4G4X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SFGGLXHRXLYRQE6SFZQNRR4G4X/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":"2026-08-16T00:40:57Z","links":{"resolver":"https://pith.science/pith/SFGGLXHRXLYRQE6SFZQNRR4G4X","bundle":"https://pith.science/pith/SFGGLXHRXLYRQE6SFZQNRR4G4X/bundle.json","state":"https://pith.science/pith/SFGGLXHRXLYRQE6SFZQNRR4G4X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SFGGLXHRXLYRQE6SFZQNRR4G4X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:SFGGLXHRXLYRQE6SFZQNRR4G4X","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":"501b02845cd21a9637a9093e4dbd3a527ee127f1ee9fef45f292d36d19c55b31","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-18T18:26:01Z","title_canon_sha256":"536474e63ffe11796c37d9d08099dbce9ff017a6d168f98b10bc97451a7f404a"},"schema_version":"1.0","source":{"id":"2310.12238","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.12238","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"arxiv_version","alias_value":"2310.12238v1","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.12238","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"pith_short_12","alias_value":"SFGGLXHRXLYR","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"pith_short_16","alias_value":"SFGGLXHRXLYRQE6S","created_at":"2026-07-05T07:02:35Z"},{"alias_kind":"pith_short_8","alias_value":"SFGGLXHR","created_at":"2026-07-05T07:02:35Z"}],"graph_snapshots":[{"event_id":"sha256:ad64e12576ba0a429ac4a159440044ab39b3411401bd5691c6f05575d722a8d6","target":"graph","created_at":"2026-07-05T07:02:35Z","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/2310.12238/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Consider the following problem: given a few demonstrations of a task across a few different objects, how can a robot learn to perform that same task on new, previously unseen objects? This is challenging because the large variety of objects within a class makes it difficult to infer the task-relevant relationship between the new objects and the objects in the demonstrations. We address this by formulating imitation learning as a conditional alignment problem between graph representations of objects. Consequently, we show that this conditioning allows for in-context learning, where a robot can ","authors_text":"Edward Johns, Vitalis Vosylius","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-18T18:26:01Z","title":"Few-Shot In-Context Imitation Learning via Implicit Graph Alignment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.12238","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":"sha256:870cd09612e126c2c9e902aedca3bdf3485b3c622c46c6277887f873e40a95f9","target":"record","created_at":"2026-07-05T07:02:35Z","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":"501b02845cd21a9637a9093e4dbd3a527ee127f1ee9fef45f292d36d19c55b31","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-18T18:26:01Z","title_canon_sha256":"536474e63ffe11796c37d9d08099dbce9ff017a6d168f98b10bc97451a7f404a"},"schema_version":"1.0","source":{"id":"2310.12238","kind":"arxiv","version":1}},"canonical_sha256":"914c65dcf1baf11813d22e60d8c786e5f22d00c8239f7653aedc88de5ef649bf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"914c65dcf1baf11813d22e60d8c786e5f22d00c8239f7653aedc88de5ef649bf","first_computed_at":"2026-07-05T07:02:35.435905Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:02:35.435905Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sQLrBQv6L227M1C2MG7VEQ21K8baRKIcMRXicUE+qprBiWb0ftg6UaDtUYOt0Yod+tfKqkv2br1mPCiXfm7qBA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:02:35.436375Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.12238","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:870cd09612e126c2c9e902aedca3bdf3485b3c622c46c6277887f873e40a95f9","sha256:ad64e12576ba0a429ac4a159440044ab39b3411401bd5691c6f05575d722a8d6"],"state_sha256":"71a151d0ce2aeb063d47643ec9d436f2ac923c07db9e8f48c3aa27911a29c985"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ugF2qbTmJSW71PQYcGBN14LpNm/oyTv2Rpu8Wx9vqZwiCt3W7nM4x1sQZL7mmyHzeKs+8t2+zhHpMC/MElvqAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T00:40:57.275745Z","bundle_sha256":"5a13ebcd3c1e8c2f2c0c1cc48758105eb576eaec5f5d65d1a2ff601157b13a13"}}