{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NWBZMTQ2YA67YLRNUDKRGOEIKK","short_pith_number":"pith:NWBZMTQ2","canonical_record":{"source":{"id":"2410.05429","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T18:49:55Z","cross_cats_sorted":[],"title_canon_sha256":"05c7901a832e09aa4c822d1b17cbcce9983f04c75cc22c9947bc7e64de4d7c8d","abstract_canon_sha256":"5b2806517f4923844e37c7c3cab2aaa7fca2fcf09965e958dfb74fe1e9958246"},"schema_version":"1.0"},"canonical_sha256":"6d83964e1ac03dfc2e2da0d5133888529f4473664297e70fa38289fc0fc3061b","source":{"kind":"arxiv","id":"2410.05429","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.05429","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"arxiv_version","alias_value":"2410.05429v1","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.05429","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"pith_short_12","alias_value":"NWBZMTQ2YA67","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"pith_short_16","alias_value":"NWBZMTQ2YA67YLRN","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"pith_short_8","alias_value":"NWBZMTQ2","created_at":"2026-07-05T09:17:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NWBZMTQ2YA67YLRNUDKRGOEIKK","target":"record","payload":{"canonical_record":{"source":{"id":"2410.05429","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T18:49:55Z","cross_cats_sorted":[],"title_canon_sha256":"05c7901a832e09aa4c822d1b17cbcce9983f04c75cc22c9947bc7e64de4d7c8d","abstract_canon_sha256":"5b2806517f4923844e37c7c3cab2aaa7fca2fcf09965e958dfb74fe1e9958246"},"schema_version":"1.0"},"canonical_sha256":"6d83964e1ac03dfc2e2da0d5133888529f4473664297e70fa38289fc0fc3061b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:17:19.122974Z","signature_b64":"Z8Tns0rQZrUp+Kfqx7Y0uDBHfrCeY5xSh+3UjnndMCB9cfUGRDAaLxuCpIIupmLdefPdXx8FQUE/BUdPczQCDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6d83964e1ac03dfc2e2da0d5133888529f4473664297e70fa38289fc0fc3061b","last_reissued_at":"2026-07-05T09:17:19.122495Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:17:19.122495Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.05429","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":"2026-07-05T09:17:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FEkbknN9muWRZc5SmtYNj0yRt16RC04yrHJBBqTg1uWovD+pg1/rloeofS6eN5zXsiDT9aEURXLjKTMZ1WVOBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:44:52.701446Z"},"content_sha256":"1f95c1ac76b90895c32be640486d820708dcae5babf0b5d0654df0b302e88254","schema_version":"1.0","event_id":"sha256:1f95c1ac76b90895c32be640486d820708dcae5babf0b5d0654df0b302e88254"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NWBZMTQ2YA67YLRNUDKRGOEIKK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Diffusion Imitation from Observation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bo-Ruei Huang, Chun-Kai Yang, Chun-Mao Lai, Dai-Jie Wu, Shao-Hua Sun","submitted_at":"2024-10-07T18:49:55Z","abstract_excerpt":"Learning from observation (LfO) aims to imitate experts by learning from state-only demonstrations without requiring action labels. Existing adversarial imitation learning approaches learn a generator agent policy to produce state transitions that are indistinguishable to a discriminator that learns to classify agent and expert state transitions. Despite its simplicity in formulation, these methods are often sensitive to hyperparameters and brittle to train. Motivated by the recent success of diffusion models in generative modeling, we propose to integrate a diffusion model into the adversaria"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.05429","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/2410.05429/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":"2026-07-05T09:17:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dKkPdGmoGAJr5OZjc0rgsMIJDuXHW22LkTvhMm6PnsX/yslVLu1VD4QL/8eGLwl/Nn7AQuc+AvKrgqhvKyU/BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:44:52.701817Z"},"content_sha256":"b4dbc3936ca88d619a9bf44db49c5f335c1a4b0ef016af6bde84cdd1a01ec058","schema_version":"1.0","event_id":"sha256:b4dbc3936ca88d619a9bf44db49c5f335c1a4b0ef016af6bde84cdd1a01ec058"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NWBZMTQ2YA67YLRNUDKRGOEIKK/bundle.json","state_url":"https://pith.science/pith/NWBZMTQ2YA67YLRNUDKRGOEIKK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NWBZMTQ2YA67YLRNUDKRGOEIKK/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":"2026-07-07T11:44:52Z","links":{"resolver":"https://pith.science/pith/NWBZMTQ2YA67YLRNUDKRGOEIKK","bundle":"https://pith.science/pith/NWBZMTQ2YA67YLRNUDKRGOEIKK/bundle.json","state":"https://pith.science/pith/NWBZMTQ2YA67YLRNUDKRGOEIKK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NWBZMTQ2YA67YLRNUDKRGOEIKK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NWBZMTQ2YA67YLRNUDKRGOEIKK","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":"5b2806517f4923844e37c7c3cab2aaa7fca2fcf09965e958dfb74fe1e9958246","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T18:49:55Z","title_canon_sha256":"05c7901a832e09aa4c822d1b17cbcce9983f04c75cc22c9947bc7e64de4d7c8d"},"schema_version":"1.0","source":{"id":"2410.05429","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.05429","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"arxiv_version","alias_value":"2410.05429v1","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.05429","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"pith_short_12","alias_value":"NWBZMTQ2YA67","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"pith_short_16","alias_value":"NWBZMTQ2YA67YLRN","created_at":"2026-07-05T09:17:19Z"},{"alias_kind":"pith_short_8","alias_value":"NWBZMTQ2","created_at":"2026-07-05T09:17:19Z"}],"graph_snapshots":[{"event_id":"sha256:b4dbc3936ca88d619a9bf44db49c5f335c1a4b0ef016af6bde84cdd1a01ec058","target":"graph","created_at":"2026-07-05T09:17:19Z","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/2410.05429/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning from observation (LfO) aims to imitate experts by learning from state-only demonstrations without requiring action labels. Existing adversarial imitation learning approaches learn a generator agent policy to produce state transitions that are indistinguishable to a discriminator that learns to classify agent and expert state transitions. Despite its simplicity in formulation, these methods are often sensitive to hyperparameters and brittle to train. Motivated by the recent success of diffusion models in generative modeling, we propose to integrate a diffusion model into the adversaria","authors_text":"Bo-Ruei Huang, Chun-Kai Yang, Chun-Mao Lai, Dai-Jie Wu, Shao-Hua Sun","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T18:49:55Z","title":"Diffusion Imitation from Observation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.05429","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":"sha256:1f95c1ac76b90895c32be640486d820708dcae5babf0b5d0654df0b302e88254","target":"record","created_at":"2026-07-05T09:17:19Z","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":"5b2806517f4923844e37c7c3cab2aaa7fca2fcf09965e958dfb74fe1e9958246","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-07T18:49:55Z","title_canon_sha256":"05c7901a832e09aa4c822d1b17cbcce9983f04c75cc22c9947bc7e64de4d7c8d"},"schema_version":"1.0","source":{"id":"2410.05429","kind":"arxiv","version":1}},"canonical_sha256":"6d83964e1ac03dfc2e2da0d5133888529f4473664297e70fa38289fc0fc3061b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6d83964e1ac03dfc2e2da0d5133888529f4473664297e70fa38289fc0fc3061b","first_computed_at":"2026-07-05T09:17:19.122495Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:17:19.122495Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z8Tns0rQZrUp+Kfqx7Y0uDBHfrCeY5xSh+3UjnndMCB9cfUGRDAaLxuCpIIupmLdefPdXx8FQUE/BUdPczQCDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:17:19.122974Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.05429","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1f95c1ac76b90895c32be640486d820708dcae5babf0b5d0654df0b302e88254","sha256:b4dbc3936ca88d619a9bf44db49c5f335c1a4b0ef016af6bde84cdd1a01ec058"],"state_sha256":"aabc8ba3ae2b81b3ea3688550f4fbc5bf420724df726d9a104c3f5b4de661049"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"weRLs1vurvLnQCb1uPOKhV82lh2Q5GjKZ3Xds281fzEC/lFTOGE70w/LsiGCN/PbTXX334hH4uMQBXrUtOuqBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T11:44:52.703745Z","bundle_sha256":"264ff29693a50cd44327252ffa7f9ba9700c05d7b2933d6682094208d425403c"}}