{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5FCFP7JCCAYNKBDEA5RA2FOJPT","short_pith_number":"pith:5FCFP7JC","canonical_record":{"source":{"id":"2301.12617","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-30T02:26:42Z","cross_cats_sorted":["cs.AI","cs.DC","cs.NI"],"title_canon_sha256":"8a62b3b1681144f513648447a1b3f86b9f638765a64a69d7ca6b722329b86a18","abstract_canon_sha256":"f9f5d787ad19f9e916fa5b4f3cd05de14bd212aca882d14310733148939429d0"},"schema_version":"1.0"},"canonical_sha256":"e94457fd221030d5046407620d15c97cde39cde84d1915b767693a3c304a564b","source":{"kind":"arxiv","id":"2301.12617","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.12617","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"arxiv_version","alias_value":"2301.12617v1","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.12617","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"pith_short_12","alias_value":"5FCFP7JCCAYN","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"pith_short_16","alias_value":"5FCFP7JCCAYNKBDE","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"pith_short_8","alias_value":"5FCFP7JC","created_at":"2026-07-05T05:36:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5FCFP7JCCAYNKBDEA5RA2FOJPT","target":"record","payload":{"canonical_record":{"source":{"id":"2301.12617","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-30T02:26:42Z","cross_cats_sorted":["cs.AI","cs.DC","cs.NI"],"title_canon_sha256":"8a62b3b1681144f513648447a1b3f86b9f638765a64a69d7ca6b722329b86a18","abstract_canon_sha256":"f9f5d787ad19f9e916fa5b4f3cd05de14bd212aca882d14310733148939429d0"},"schema_version":"1.0"},"canonical_sha256":"e94457fd221030d5046407620d15c97cde39cde84d1915b767693a3c304a564b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:36:55.841871Z","signature_b64":"14yrNzRwZKUZMPIY2vGDPSt9RB3d1C3yyodZwgMhg5L0mTxzOXpgupcA2BGg9Z5ZW/8IDae2hsqFMmyC+jPvAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e94457fd221030d5046407620d15c97cde39cde84d1915b767693a3c304a564b","last_reissued_at":"2026-07-05T05:36:55.841446Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:36:55.841446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.12617","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":"2026-07-05T05:36:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5My8HOB9WspOyLWiVZy07kgVJ67EV3ft70YRnOhbTOHwBCPJtUjXNVSHvcbhbJB4x6oY64dU33rqOkdycyssBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T23:02:02.677977Z"},"content_sha256":"a5fa63f386c7f584c0c18edc6bb99b669f6bba4ac7035856a7743faa4381d6d2","schema_version":"1.0","event_id":"sha256:a5fa63f386c7f584c0c18edc6bb99b669f6bba4ac7035856a7743faa4381d6d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5FCFP7JCCAYNKBDEA5RA2FOJPT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.DC","cs.NI"],"primary_cat":"cs.LG","authors_text":"Elina Kontio, Esa Alhoniemi, Mohammad Ayyaz Azeem, Mojtaba Jafaritadi, Muhammad Irfan Khan, Suleiman A. Khan","submitted_at":"2023-01-30T02:26:42Z","abstract_excerpt":"In federated learning (FL), the global model at the server requires an efficient mechanism for weight aggregation and a systematic strategy for collaboration selection to manage and optimize communication payload. We introduce a practical and cost-efficient method for regularized weight aggregation and propose a laborsaving technique to select collaborators per round. We illustrate the performance of our method, regularized similarity weight aggregation (RegSimAgg), on the Federated Tumor Segmentation (FeTS) 2022 challenge's federated training (weight aggregation) problem. Our scalable approac"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.12617","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/2301.12617/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":"2026-07-05T05:36:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rptlpxnG9TKso6gDCRDz4aPUvoFf9gaIrVjRap1aQ5/3TBnqZpnCJMeac1OSTN8l3NvzG60xgFCSlB/JRog7Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T23:02:02.678359Z"},"content_sha256":"996a434d19c79b159d6f6cf16f46f61288b736f9dbf5dd84aa48e34319d8724c","schema_version":"1.0","event_id":"sha256:996a434d19c79b159d6f6cf16f46f61288b736f9dbf5dd84aa48e34319d8724c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5FCFP7JCCAYNKBDEA5RA2FOJPT/bundle.json","state_url":"https://pith.science/pith/5FCFP7JCCAYNKBDEA5RA2FOJPT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5FCFP7JCCAYNKBDEA5RA2FOJPT/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":"2026-08-18T23:02:02Z","links":{"resolver":"https://pith.science/pith/5FCFP7JCCAYNKBDEA5RA2FOJPT","bundle":"https://pith.science/pith/5FCFP7JCCAYNKBDEA5RA2FOJPT/bundle.json","state":"https://pith.science/pith/5FCFP7JCCAYNKBDEA5RA2FOJPT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5FCFP7JCCAYNKBDEA5RA2FOJPT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5FCFP7JCCAYNKBDEA5RA2FOJPT","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":"f9f5d787ad19f9e916fa5b4f3cd05de14bd212aca882d14310733148939429d0","cross_cats_sorted":["cs.AI","cs.DC","cs.NI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-30T02:26:42Z","title_canon_sha256":"8a62b3b1681144f513648447a1b3f86b9f638765a64a69d7ca6b722329b86a18"},"schema_version":"1.0","source":{"id":"2301.12617","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.12617","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"arxiv_version","alias_value":"2301.12617v1","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.12617","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"pith_short_12","alias_value":"5FCFP7JCCAYN","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"pith_short_16","alias_value":"5FCFP7JCCAYNKBDE","created_at":"2026-07-05T05:36:55Z"},{"alias_kind":"pith_short_8","alias_value":"5FCFP7JC","created_at":"2026-07-05T05:36:55Z"}],"graph_snapshots":[{"event_id":"sha256:996a434d19c79b159d6f6cf16f46f61288b736f9dbf5dd84aa48e34319d8724c","target":"graph","created_at":"2026-07-05T05:36:55Z","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/2301.12617/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In federated learning (FL), the global model at the server requires an efficient mechanism for weight aggregation and a systematic strategy for collaboration selection to manage and optimize communication payload. We introduce a practical and cost-efficient method for regularized weight aggregation and propose a laborsaving technique to select collaborators per round. We illustrate the performance of our method, regularized similarity weight aggregation (RegSimAgg), on the Federated Tumor Segmentation (FeTS) 2022 challenge's federated training (weight aggregation) problem. Our scalable approac","authors_text":"Elina Kontio, Esa Alhoniemi, Mohammad Ayyaz Azeem, Mojtaba Jafaritadi, Muhammad Irfan Khan, Suleiman A. Khan","cross_cats":["cs.AI","cs.DC","cs.NI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-30T02:26:42Z","title":"Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.12617","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:a5fa63f386c7f584c0c18edc6bb99b669f6bba4ac7035856a7743faa4381d6d2","target":"record","created_at":"2026-07-05T05:36:55Z","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":"f9f5d787ad19f9e916fa5b4f3cd05de14bd212aca882d14310733148939429d0","cross_cats_sorted":["cs.AI","cs.DC","cs.NI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-30T02:26:42Z","title_canon_sha256":"8a62b3b1681144f513648447a1b3f86b9f638765a64a69d7ca6b722329b86a18"},"schema_version":"1.0","source":{"id":"2301.12617","kind":"arxiv","version":1}},"canonical_sha256":"e94457fd221030d5046407620d15c97cde39cde84d1915b767693a3c304a564b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e94457fd221030d5046407620d15c97cde39cde84d1915b767693a3c304a564b","first_computed_at":"2026-07-05T05:36:55.841446Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:36:55.841446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"14yrNzRwZKUZMPIY2vGDPSt9RB3d1C3yyodZwgMhg5L0mTxzOXpgupcA2BGg9Z5ZW/8IDae2hsqFMmyC+jPvAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:36:55.841871Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.12617","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a5fa63f386c7f584c0c18edc6bb99b669f6bba4ac7035856a7743faa4381d6d2","sha256:996a434d19c79b159d6f6cf16f46f61288b736f9dbf5dd84aa48e34319d8724c"],"state_sha256":"d3a42ffff8d86758b6b1a47a705faedc36b9d342e65fd2cb511d0e05ddddd31e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BZHEDOgCSS/TpAsQCrlZsCaReNTqRjX3LWHzynS/fX36FFgMujK2JjHeI1h6AIcsLQpwFkAO919z8EE6tx+TAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T23:02:02.680686Z","bundle_sha256":"2e410800cd41f249372f03613fcfadd3fcee7cd77602d8f6c04e77f978473938"}}