{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4PL5HXLDTDWFWZJDJ6GVXN45PZ","short_pith_number":"pith:4PL5HXLD","canonical_record":{"source":{"id":"2503.22531","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-03-28T15:33:28Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"b28741d2960207f8f5443203e9143d4424504eb8f103d3a42818a8a86cb02f7d","abstract_canon_sha256":"1375d47784f64321e85cf544ae83f5e884d2bdc68fc9adb05e9e8342b70b88a2"},"schema_version":"1.0"},"canonical_sha256":"e3d7d3dd6398ec5b65234f8d5bb79d7e540a01ebb95f08c504001834103bea88","source":{"kind":"arxiv","id":"2503.22531","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.22531","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"2503.22531v1","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.22531","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"4PL5HXLDTDWF","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"pith_short_16","alias_value":"4PL5HXLDTDWFWZJD","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"pith_short_8","alias_value":"4PL5HXLD","created_at":"2026-07-05T10:41:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4PL5HXLDTDWFWZJDJ6GVXN45PZ","target":"record","payload":{"canonical_record":{"source":{"id":"2503.22531","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-03-28T15:33:28Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"b28741d2960207f8f5443203e9143d4424504eb8f103d3a42818a8a86cb02f7d","abstract_canon_sha256":"1375d47784f64321e85cf544ae83f5e884d2bdc68fc9adb05e9e8342b70b88a2"},"schema_version":"1.0"},"canonical_sha256":"e3d7d3dd6398ec5b65234f8d5bb79d7e540a01ebb95f08c504001834103bea88","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:41:06.285308Z","signature_b64":"yjBUuY4pGM8FTzX/kU4mnDRcAOU+O291KyPbEF7OxjQyR0SisOppFgRw8ChozIaaG9/lA2byrHqEuc+bBBWLDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e3d7d3dd6398ec5b65234f8d5bb79d7e540a01ebb95f08c504001834103bea88","last_reissued_at":"2026-07-05T10:41:06.284842Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:41:06.284842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.22531","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":"2026-07-05T10:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BkH0OVgxH4RZ4160ob7YsP8zqax67mM4ruB8ZmH80PFxBoUEPMMx5nEtRs8wxVPsIj5zWcViinUjFdyCz/mAAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T09:45:17.033823Z"},"content_sha256":"bc8fe09ea7d085b6fca3d1c79f0b3c8b8e3ea18450f868af8595be9adb7741d8","schema_version":"1.0","event_id":"sha256:bc8fe09ea7d085b6fca3d1c79f0b3c8b8e3ea18450f868af8595be9adb7741d8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4PL5HXLDTDWFWZJDJ6GVXN45PZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deterministic Medical Image Translation via High-fidelity Brownian Bridges","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Carri Glide-Hurst, Ming Dong, Nicholas Summerfield, Peiyong Wang, Qisheng He","submitted_at":"2025-03-28T15:33:28Z","abstract_excerpt":"Recent studies have shown that diffusion models produce superior synthetic images when compared to Generative Adversarial Networks (GANs). However, their outputs are often non-deterministic and lack high fidelity to the ground truth due to the inherent randomness. In this paper, we propose a novel High-fidelity Brownian bridge model (HiFi-BBrg) for deterministic medical image translations. Our model comprises two distinct yet mutually beneficial mappings: a generation mapping and a reconstruction mapping. The Brownian bridge training process is guided by the fidelity loss and adversarial train"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.22531","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/2503.22531/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":"2026-07-05T10:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KJfy/pqJp6CjxxCvm5K5cJDhBfMAzlkDnjOEoeoOc2UGrKuI7j3t5cQ56q7ILO1biAFKPjfiBSnpF1ZzhCebCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T09:45:17.034349Z"},"content_sha256":"fe35cd71e5bb5fda066789fe7a92bee39b45e3fd940b3cf07cd111a57f93a26e","schema_version":"1.0","event_id":"sha256:fe35cd71e5bb5fda066789fe7a92bee39b45e3fd940b3cf07cd111a57f93a26e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4PL5HXLDTDWFWZJDJ6GVXN45PZ/bundle.json","state_url":"https://pith.science/pith/4PL5HXLDTDWFWZJDJ6GVXN45PZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4PL5HXLDTDWFWZJDJ6GVXN45PZ/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":"2026-08-16T09:45:17Z","links":{"resolver":"https://pith.science/pith/4PL5HXLDTDWFWZJDJ6GVXN45PZ","bundle":"https://pith.science/pith/4PL5HXLDTDWFWZJDJ6GVXN45PZ/bundle.json","state":"https://pith.science/pith/4PL5HXLDTDWFWZJDJ6GVXN45PZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4PL5HXLDTDWFWZJDJ6GVXN45PZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4PL5HXLDTDWFWZJDJ6GVXN45PZ","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":"1375d47784f64321e85cf544ae83f5e884d2bdc68fc9adb05e9e8342b70b88a2","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-03-28T15:33:28Z","title_canon_sha256":"b28741d2960207f8f5443203e9143d4424504eb8f103d3a42818a8a86cb02f7d"},"schema_version":"1.0","source":{"id":"2503.22531","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.22531","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"2503.22531v1","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.22531","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"4PL5HXLDTDWF","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"pith_short_16","alias_value":"4PL5HXLDTDWFWZJD","created_at":"2026-07-05T10:41:06Z"},{"alias_kind":"pith_short_8","alias_value":"4PL5HXLD","created_at":"2026-07-05T10:41:06Z"}],"graph_snapshots":[{"event_id":"sha256:fe35cd71e5bb5fda066789fe7a92bee39b45e3fd940b3cf07cd111a57f93a26e","target":"graph","created_at":"2026-07-05T10:41:06Z","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/2503.22531/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent studies have shown that diffusion models produce superior synthetic images when compared to Generative Adversarial Networks (GANs). However, their outputs are often non-deterministic and lack high fidelity to the ground truth due to the inherent randomness. In this paper, we propose a novel High-fidelity Brownian bridge model (HiFi-BBrg) for deterministic medical image translations. Our model comprises two distinct yet mutually beneficial mappings: a generation mapping and a reconstruction mapping. The Brownian bridge training process is guided by the fidelity loss and adversarial train","authors_text":"Carri Glide-Hurst, Ming Dong, Nicholas Summerfield, Peiyong Wang, Qisheng He","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-03-28T15:33:28Z","title":"Deterministic Medical Image Translation via High-fidelity Brownian Bridges"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.22531","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:bc8fe09ea7d085b6fca3d1c79f0b3c8b8e3ea18450f868af8595be9adb7741d8","target":"record","created_at":"2026-07-05T10:41:06Z","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":"1375d47784f64321e85cf544ae83f5e884d2bdc68fc9adb05e9e8342b70b88a2","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-03-28T15:33:28Z","title_canon_sha256":"b28741d2960207f8f5443203e9143d4424504eb8f103d3a42818a8a86cb02f7d"},"schema_version":"1.0","source":{"id":"2503.22531","kind":"arxiv","version":1}},"canonical_sha256":"e3d7d3dd6398ec5b65234f8d5bb79d7e540a01ebb95f08c504001834103bea88","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3d7d3dd6398ec5b65234f8d5bb79d7e540a01ebb95f08c504001834103bea88","first_computed_at":"2026-07-05T10:41:06.284842Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:41:06.284842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yjBUuY4pGM8FTzX/kU4mnDRcAOU+O291KyPbEF7OxjQyR0SisOppFgRw8ChozIaaG9/lA2byrHqEuc+bBBWLDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:41:06.285308Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.22531","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bc8fe09ea7d085b6fca3d1c79f0b3c8b8e3ea18450f868af8595be9adb7741d8","sha256:fe35cd71e5bb5fda066789fe7a92bee39b45e3fd940b3cf07cd111a57f93a26e"],"state_sha256":"29c712f2db93523ca016811de19f825afa205c7aa9ac6b9dc04f8e932b3dd689"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ffeNZ9nWcxNOu19AVZD8i/VGmoUtQjB4gdacHUXXukNf+HT3RZspEB9VWW3prr5FjQ8HOC7xiulXR3Cz5uH1Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T09:45:17.039698Z","bundle_sha256":"34f7f6c5498cb2954d3ad5d052477923fd06ab8a07766a373a9972a96ddf4d9e"}}