{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:RJXDRPTEMIOD5HPWXGHAT6XXY3","short_pith_number":"pith:RJXDRPTE","canonical_record":{"source":{"id":"2504.17613","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T14:36:10Z","cross_cats_sorted":[],"title_canon_sha256":"502dc3ff0302374a8b8d174058def9e11af3a0d904ed189d5f29ac5d2138a137","abstract_canon_sha256":"c6b8735deb1138b4be16110dae92fe5cf18e1d153b77cfd976076abc6c9cddc9"},"schema_version":"1.0"},"canonical_sha256":"8a6e38be64621c3e9df6b98e09faf7c6d3e9ebe18f8a01d8c628ab14d1f7a3fd","source":{"kind":"arxiv","id":"2504.17613","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.17613","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"arxiv_version","alias_value":"2504.17613v1","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.17613","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"pith_short_12","alias_value":"RJXDRPTEMIOD","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"pith_short_16","alias_value":"RJXDRPTEMIOD5HPW","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"pith_short_8","alias_value":"RJXDRPTE","created_at":"2026-07-05T10:53:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:RJXDRPTEMIOD5HPWXGHAT6XXY3","target":"record","payload":{"canonical_record":{"source":{"id":"2504.17613","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T14:36:10Z","cross_cats_sorted":[],"title_canon_sha256":"502dc3ff0302374a8b8d174058def9e11af3a0d904ed189d5f29ac5d2138a137","abstract_canon_sha256":"c6b8735deb1138b4be16110dae92fe5cf18e1d153b77cfd976076abc6c9cddc9"},"schema_version":"1.0"},"canonical_sha256":"8a6e38be64621c3e9df6b98e09faf7c6d3e9ebe18f8a01d8c628ab14d1f7a3fd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:53:32.661715Z","signature_b64":"0snoyfT6rAyBetr8hQDAaBYVlxuO6AgZwpalK/7lBkubmUhf/hnMiplGCrKA0gLvBDyIIeaWPdGxzAKoqubdDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a6e38be64621c3e9df6b98e09faf7c6d3e9ebe18f8a01d8c628ab14d1f7a3fd","last_reissued_at":"2026-07-05T10:53:32.661180Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:53:32.661180Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.17613","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":"2026-07-05T10:53:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KsQYcJGzAMo1gv2ZjFHlh3DXnMM67eXtPU+D1vjK9rbKzmHnhKBf0nJhlQOvoGITVnxIIeDWAropCUs7gfhRDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T05:41:27.394550Z"},"content_sha256":"cbdee17568af729402c5fddcf2cb3fdd5eb5521d4d199f8cf6a8104240e75731","schema_version":"1.0","event_id":"sha256:cbdee17568af729402c5fddcf2cb3fdd5eb5521d4d199f8cf6a8104240e75731"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:RJXDRPTEMIOD5HPWXGHAT6XXY3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bowen Deng, Chang Xu, Hao Li, Jiang Bian, Min Hou, Yuhao Huang","submitted_at":"2025-04-24T14:36:10Z","abstract_excerpt":"Synthetic Electronic Health Record (EHR) time-series generation is crucial for advancing clinical machine learning models, as it helps address data scarcity by providing more training data. However, most existing approaches focus primarily on replicating statistical distributions and temporal dependencies of real-world data. We argue that fidelity to observed data alone does not guarantee better model performance, as common patterns may dominate, limiting the representation of rare but important conditions. This highlights the need for generate synthetic samples to improve performance of speci"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.17613","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/2504.17613/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":"2026-07-05T10:53:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vk9zmtkIH5azLlKUBNrDh15zwgHx2RsN8yySYssVK2hqlpNGhLBYWdapNVgRXUARBhvw7+HDQli8J6pC5u2iBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T05:41:27.398969Z"},"content_sha256":"3094347fefa2527f228b991fef50bbb8b7c7505c6a5317490261d45ec62abdb3","schema_version":"1.0","event_id":"sha256:3094347fefa2527f228b991fef50bbb8b7c7505c6a5317490261d45ec62abdb3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RJXDRPTEMIOD5HPWXGHAT6XXY3/bundle.json","state_url":"https://pith.science/pith/RJXDRPTEMIOD5HPWXGHAT6XXY3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RJXDRPTEMIOD5HPWXGHAT6XXY3/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":"2026-08-17T05:41:27Z","links":{"resolver":"https://pith.science/pith/RJXDRPTEMIOD5HPWXGHAT6XXY3","bundle":"https://pith.science/pith/RJXDRPTEMIOD5HPWXGHAT6XXY3/bundle.json","state":"https://pith.science/pith/RJXDRPTEMIOD5HPWXGHAT6XXY3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RJXDRPTEMIOD5HPWXGHAT6XXY3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RJXDRPTEMIOD5HPWXGHAT6XXY3","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":"c6b8735deb1138b4be16110dae92fe5cf18e1d153b77cfd976076abc6c9cddc9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T14:36:10Z","title_canon_sha256":"502dc3ff0302374a8b8d174058def9e11af3a0d904ed189d5f29ac5d2138a137"},"schema_version":"1.0","source":{"id":"2504.17613","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.17613","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"arxiv_version","alias_value":"2504.17613v1","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.17613","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"pith_short_12","alias_value":"RJXDRPTEMIOD","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"pith_short_16","alias_value":"RJXDRPTEMIOD5HPW","created_at":"2026-07-05T10:53:32Z"},{"alias_kind":"pith_short_8","alias_value":"RJXDRPTE","created_at":"2026-07-05T10:53:32Z"}],"graph_snapshots":[{"event_id":"sha256:3094347fefa2527f228b991fef50bbb8b7c7505c6a5317490261d45ec62abdb3","target":"graph","created_at":"2026-07-05T10:53:32Z","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/2504.17613/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Synthetic Electronic Health Record (EHR) time-series generation is crucial for advancing clinical machine learning models, as it helps address data scarcity by providing more training data. However, most existing approaches focus primarily on replicating statistical distributions and temporal dependencies of real-world data. We argue that fidelity to observed data alone does not guarantee better model performance, as common patterns may dominate, limiting the representation of rare but important conditions. This highlights the need for generate synthetic samples to improve performance of speci","authors_text":"Bowen Deng, Chang Xu, Hao Li, Jiang Bian, Min Hou, Yuhao Huang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T14:36:10Z","title":"TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.17613","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:cbdee17568af729402c5fddcf2cb3fdd5eb5521d4d199f8cf6a8104240e75731","target":"record","created_at":"2026-07-05T10:53:32Z","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":"c6b8735deb1138b4be16110dae92fe5cf18e1d153b77cfd976076abc6c9cddc9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T14:36:10Z","title_canon_sha256":"502dc3ff0302374a8b8d174058def9e11af3a0d904ed189d5f29ac5d2138a137"},"schema_version":"1.0","source":{"id":"2504.17613","kind":"arxiv","version":1}},"canonical_sha256":"8a6e38be64621c3e9df6b98e09faf7c6d3e9ebe18f8a01d8c628ab14d1f7a3fd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a6e38be64621c3e9df6b98e09faf7c6d3e9ebe18f8a01d8c628ab14d1f7a3fd","first_computed_at":"2026-07-05T10:53:32.661180Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:53:32.661180Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0snoyfT6rAyBetr8hQDAaBYVlxuO6AgZwpalK/7lBkubmUhf/hnMiplGCrKA0gLvBDyIIeaWPdGxzAKoqubdDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:53:32.661715Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.17613","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cbdee17568af729402c5fddcf2cb3fdd5eb5521d4d199f8cf6a8104240e75731","sha256:3094347fefa2527f228b991fef50bbb8b7c7505c6a5317490261d45ec62abdb3"],"state_sha256":"48e5637cfe4a52360fbe1f41ca845236844b6071ce9972b4b950a1bb7c581a12"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SOO2mZ8eBhcbXVZqZQpBReRIYb4m8xTaFHG7AwjkFetydknuL/RjmYOreaz/Q6ccKIoHtRJ3UzOb9qrripiODA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T05:41:27.419041Z","bundle_sha256":"34ab5aad1e588cc6029ff0ce97f1a90e0733cd0ee35afbafab178ae4fe906413"}}