{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:H4SA2COPQIB34DCGHX6L7RIHXB","short_pith_number":"pith:H4SA2COP","canonical_record":{"source":{"id":"2012.08604","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-15T20:41:24Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"bd351f37910909c7577360cccc16c13b4ea5298c769f39f6902350231849a4d2","abstract_canon_sha256":"d076b73e14ebfe4997c80851fc87c96135dd5d3149ebea1294e3fe62b679ca32"},"schema_version":"1.0"},"canonical_sha256":"3f240d09cf8203be0c463dfcbfc507b8518c74f329ee192962223b07fdaf43b6","source":{"kind":"arxiv","id":"2012.08604","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.08604","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"arxiv_version","alias_value":"2012.08604v1","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.08604","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"pith_short_12","alias_value":"H4SA2COPQIB3","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"pith_short_16","alias_value":"H4SA2COPQIB34DCG","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"pith_short_8","alias_value":"H4SA2COP","created_at":"2026-07-05T02:00:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:H4SA2COPQIB34DCGHX6L7RIHXB","target":"record","payload":{"canonical_record":{"source":{"id":"2012.08604","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-15T20:41:24Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"bd351f37910909c7577360cccc16c13b4ea5298c769f39f6902350231849a4d2","abstract_canon_sha256":"d076b73e14ebfe4997c80851fc87c96135dd5d3149ebea1294e3fe62b679ca32"},"schema_version":"1.0"},"canonical_sha256":"3f240d09cf8203be0c463dfcbfc507b8518c74f329ee192962223b07fdaf43b6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:00:01.224879Z","signature_b64":"ixq0GJ1/RySVQBF4s3WNqRxEaRyq13it+afXhhgQ17z7nIiSwrRw7dKhRs/aKfq+K/qB5v77+54NQ36uhyuGCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3f240d09cf8203be0c463dfcbfc507b8518c74f329ee192962223b07fdaf43b6","last_reissued_at":"2026-07-05T02:00:01.224404Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:00:01.224404Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2012.08604","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":"2026-07-05T02:00:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wAfJMkINLip/g6zIA+nj5BeczcSuv866AH+WiqflUFLVd/VkxkPc580DJUszh+vhuLRHBQw2zoyBft4LC7RPBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:04:57.237585Z"},"content_sha256":"6c18fe8b3da92d8fd76d78536321aa8869c46ad31925c1955d993ec7eff80391","schema_version":"1.0","event_id":"sha256:6c18fe8b3da92d8fd76d78536321aa8869c46ad31925c1955d993ec7eff80391"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:H4SA2COPQIB34DCGHX6L7RIHXB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.LG","authors_text":"Dimitris N. Metaxas, Hui Qu, Lohendran Baskaran, Qi Chang, Shaoting Zhang, Tong Zhang, Yikai Zhang, Zhennan Yan","submitted_at":"2020-12-15T20:41:24Z","abstract_excerpt":"As deep learning technologies advance, increasingly more data is necessary to generate general and robust models for various tasks. In the medical domain, however, large-scale and multi-parties data training and analyses are infeasible due to the privacy and data security concerns. In this paper, we propose an extendable and elastic learning framework to preserve privacy and security while enabling collaborative learning with efficient communication. The proposed framework is named distributed Asynchronized Discriminator Generative Adversarial Networks (AsynDGAN), which consists of a centraliz"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.08604","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/2012.08604/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":"2026-07-05T02:00:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HIrsbmuGKPGcNG6mYWJ6S6LqEeYUkgDgBGCmkWJFDugqeYMasJGzeTqXfbF6DBpTJgtFnOg389ZbPEDctr+RBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:04:57.237981Z"},"content_sha256":"9b442b170d8fc67b5fe03e8ea4a74291a47cbeb12dacb6df88caa33bdd5120f7","schema_version":"1.0","event_id":"sha256:9b442b170d8fc67b5fe03e8ea4a74291a47cbeb12dacb6df88caa33bdd5120f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H4SA2COPQIB34DCGHX6L7RIHXB/bundle.json","state_url":"https://pith.science/pith/H4SA2COPQIB34DCGHX6L7RIHXB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H4SA2COPQIB34DCGHX6L7RIHXB/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":"2026-07-07T14:04:57Z","links":{"resolver":"https://pith.science/pith/H4SA2COPQIB34DCGHX6L7RIHXB","bundle":"https://pith.science/pith/H4SA2COPQIB34DCGHX6L7RIHXB/bundle.json","state":"https://pith.science/pith/H4SA2COPQIB34DCGHX6L7RIHXB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H4SA2COPQIB34DCGHX6L7RIHXB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:H4SA2COPQIB34DCGHX6L7RIHXB","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":"d076b73e14ebfe4997c80851fc87c96135dd5d3149ebea1294e3fe62b679ca32","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-15T20:41:24Z","title_canon_sha256":"bd351f37910909c7577360cccc16c13b4ea5298c769f39f6902350231849a4d2"},"schema_version":"1.0","source":{"id":"2012.08604","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.08604","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"arxiv_version","alias_value":"2012.08604v1","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.08604","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"pith_short_12","alias_value":"H4SA2COPQIB3","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"pith_short_16","alias_value":"H4SA2COPQIB34DCG","created_at":"2026-07-05T02:00:01Z"},{"alias_kind":"pith_short_8","alias_value":"H4SA2COP","created_at":"2026-07-05T02:00:01Z"}],"graph_snapshots":[{"event_id":"sha256:9b442b170d8fc67b5fe03e8ea4a74291a47cbeb12dacb6df88caa33bdd5120f7","target":"graph","created_at":"2026-07-05T02:00:01Z","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/2012.08604/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As deep learning technologies advance, increasingly more data is necessary to generate general and robust models for various tasks. In the medical domain, however, large-scale and multi-parties data training and analyses are infeasible due to the privacy and data security concerns. In this paper, we propose an extendable and elastic learning framework to preserve privacy and security while enabling collaborative learning with efficient communication. The proposed framework is named distributed Asynchronized Discriminator Generative Adversarial Networks (AsynDGAN), which consists of a centraliz","authors_text":"Dimitris N. Metaxas, Hui Qu, Lohendran Baskaran, Qi Chang, Shaoting Zhang, Tong Zhang, Yikai Zhang, Zhennan Yan","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-15T20:41:24Z","title":"Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.08604","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":"sha256:6c18fe8b3da92d8fd76d78536321aa8869c46ad31925c1955d993ec7eff80391","target":"record","created_at":"2026-07-05T02:00:01Z","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":"d076b73e14ebfe4997c80851fc87c96135dd5d3149ebea1294e3fe62b679ca32","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2020-12-15T20:41:24Z","title_canon_sha256":"bd351f37910909c7577360cccc16c13b4ea5298c769f39f6902350231849a4d2"},"schema_version":"1.0","source":{"id":"2012.08604","kind":"arxiv","version":1}},"canonical_sha256":"3f240d09cf8203be0c463dfcbfc507b8518c74f329ee192962223b07fdaf43b6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3f240d09cf8203be0c463dfcbfc507b8518c74f329ee192962223b07fdaf43b6","first_computed_at":"2026-07-05T02:00:01.224404Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:00:01.224404Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ixq0GJ1/RySVQBF4s3WNqRxEaRyq13it+afXhhgQ17z7nIiSwrRw7dKhRs/aKfq+K/qB5v77+54NQ36uhyuGCg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:00:01.224879Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.08604","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6c18fe8b3da92d8fd76d78536321aa8869c46ad31925c1955d993ec7eff80391","sha256:9b442b170d8fc67b5fe03e8ea4a74291a47cbeb12dacb6df88caa33bdd5120f7"],"state_sha256":"6e524068f99bfe14bc72bae05c2bb8dd636f37ef71dfaeaf0ab4f3d38ee921b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L1LGZGKZ6NKZLIfxzKyj1BskTHyNuuHAIRlKzUSJpGlCVuFY82oWAcxKLCfUBq3CDtCJCTbfBzVdCCCi+I7aAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T14:04:57.239946Z","bundle_sha256":"5bcbedfd6b1df73fdba743a0ff536ac4e015dee8649a3947cc6007decc2ec0aa"}}