{"as_of":"2026-08-14T11:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:72c941f3d6cec9b681ca5233b1815a0ce3c2f253936f18e87bfe92b4ab5e03ea","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T11:57:34.278440Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2601.04930/citation-record","integrity":"/paper/2601.04930/integrity","json":"/paper/2601.04930/citation-record.json","paper":"/paper/2601.04930"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.018031Z","title":"Deep Learning with Differential Privacy","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.018031Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:49e7bbff9ad0fafd7703efe4f03dcb368a0d12767ac963444add9d5b463ad007","observation_id":"9080e265-2574-48b4-b5f0-ff3736bea012","resolution":{"observed_at":"2026-08-03T11:57:34.018031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.070657Z","title":"Prio+: Privacy pre- serving aggregate statistics via boolean shares","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.070657Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:3f16128bcf0406e30bd802539d2968738bf7308cfd7e1de5015ac7dfc1664aaf","observation_id":"821b71a1-c386-4249-86a0-ed6168e08682","resolution":{"observed_at":"2026-08-03T11:57:34.070657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.100614Z","title":"Flchain: A blockchain for auditable federated learning with trust and incentive","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.100614Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:1377add32a98e9639426836115be91365b03d7233ffc65fa7453453989cafe03","observation_id":"d551fea1-43c0-4341-8ed2-3f44b21fc14e","resolution":{"observed_at":"2026-08-03T11:57:34.100614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.105331Z","title":"Secure single-server aggregation with (poly) logarithmic overhead","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.105331Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:fc37d96892a7f8201d08406d2bfb22c2e801fed4c7a52d3d030441231f244db3","observation_id":"2488c569-235b-480b-9118-a80f8c35aa98","resolution":{"observed_at":"2026-08-03T11:57:34.105331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.110380Z","title":"Asynchronous secure computation","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.110380Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:328bf3551d7f0f65af7bdf0740727a91d73e58a36d9924d4f2ce4360dce55e32","observation_id":"c8eab9fb-2a86-4858-8b30-6852df15a89c","resolution":{"observed_at":"2026-08-03T11:57:34.110380Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.114849Z","title":"Fantastyc: Blockchain-based federated learning made secure and practical","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.114849Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:0b81446c689b17a39ee223b205c4212fed7866692431c83f797c9a38d01e0f89","observation_id":"9a0e47e9-8781-4ef0-9a26-be047addec8e","resolution":{"observed_at":"2026-08-03T11:57:34.114849Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.119876Z","title":"Practical Secure Aggregation for Privacy-Preserving Machine Learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.119876Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:82d541f94c9ef6eebc94466e23128b21649a4f28fa690bdedf26e677fc17f550","observation_id":"7df3e844-26fe-4d6e-a0e6-57e5c3453a96","resolution":{"observed_at":"2026-08-03T11:57:34.119876Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.124094Z","title":"Lightweight, Maliciously Secure Verifiable Function Secret Sharing","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.124094Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:154e00c30102be9ed1e38c5319ba1dc615ec2bb8d6fc4cd3c320152fe27d9968","observation_id":"918dddd8-5de7-492d-9366-d29dd5327a90","resolution":{"observed_at":"2026-08-03T11:57:34.124094Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.128238Z","title":"Practical byzantine fault tolerance","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.128238Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:76c6dd6bdedf69acc561fc441a0992f5bdf5bce4fac65e2ff225aea1a8451f69","observation_id":"49c4d0f5-80ca-4f8d-aeac-c43f87038651","resolution":{"observed_at":"2026-08-03T11:57:34.128238Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.132876Z","title":"Homomorphic Secret Sharing with Veri- fiable Evaluation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.132876Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:721cef09f9f96ee291b94f1ce94941f185aec53a0d10af9b181668bc94bd9182","observation_id":"5969802c-61e2-4f75-aac1-337b2dff9c5e","resolution":{"observed_at":"2026-08-03T11:57:34.132876Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.137525Z","title":"Prio: Private, robust, and scalable computation of aggre- gate statistics","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.137525Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:0682d3d6bb299436873937fe7d7e843535d7f67f0fc0425bfb0f8c700d8fe8fb","observation_id":"6cbb4692-045d-4bb7-9285-e1e370535812","resolution":{"observed_at":"2026-08-03T11:57:34.137525Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.142983Z","title":"Cryp- toNets: applying neural networks to encrypted data with high throughput and accuracy","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.142983Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:a0ade995449b5a0f9df11810c6070c1b5be87c8fbda7287e9384a5457f9b12ae","observation_id":"73671f2c-c006-470d-b76f-1b8d50024d8f","resolution":{"observed_at":"2026-08-03T11:57:34.142983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.147699Z","title":"BEAT: Asynchronous BFT Made Practical","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.147699Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:39a2f0ecd041ab09bb60aa27bfc58c4bbc6703f80a6947e72f38a116768ddab8","observation_id":"64cbaa41-2e32-4844-a62f-0ce6829a20a8","resolution":{"observed_at":"2026-08-03T11:57:34.147699Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.151971Z","title":"Differential Privacy","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.151971Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:7c5cac8e23468389e2811c586e41820d3ab984ec61b923e161c755d3918e83aa","observation_id":"9a87cffe-11c0-4839-8069-9bcd2fbecd45","resolution":{"observed_at":"2026-08-03T11:57:34.151971Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.12840","last_updated":"2019-04-29T17:42:25Z","snapshot_observed_at":"2026-07-06T07:49:17.886466Z","submitted_at":"2019-04-29T17:42:25Z","title":"SEALion: a Framework for Neural Network Inference on Encrypted Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.12840","snapshot_observed_at":"2026-08-03T11:57:34.156533Z","title":"van Elsloo, G","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.156533Z"},"links":{"cited_paper":"/paper/1904.12840","citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:43bad841f83636865f7f80c6d20ae79755e0547d2f33533f9c3f7c91fcd6fe90","observation_id":"3436a4be-399c-4ed2-b3f8-e3b7ef1969da","resolution":{"observed_at":"2026-08-03T11:57:34.156533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.161345Z","title":"Impossibility of Distributed Consensus with One Faulty Process","venue":null,"work_id":null,"year":1985},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.161345Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:6363aa8a7069545e4aa479159e9f4a2d4acd40758dec9f59c0aa2bbe0a2c9a85","observation_id":"f2a77421-fcfb-4cf9-bbd2-1e2770f65f7e","resolution":{"observed_at":"2026-08-03T11:57:34.161345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.12377","last_updated":"2024-12-12T18:16:23Z","snapshot_observed_at":"2026-08-14T11:10:02.873974Z","submitted_at":"2024-11-19T09:53:28Z","title":"Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.12377","snapshot_observed_at":"2026-08-03T11:57:34.165445Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.165445Z"},"links":{"cited_paper":"/paper/2411.12377","citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:e793307787007bf0254123de2557399a597b83f8825201d653c8b40dde7bd046","observation_id":"ce364021-0b8a-4cf9-b95c-ec525c77f02c","resolution":{"observed_at":"2026-08-03T11:57:34.165445Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.170283Z","title":"Differential privacy and byzantine resilience in sgd: Do they add up?","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.170283Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:2ba5ceb64bd84f3685395eece1ef0001277100e8df47b3b927b86b3ec353b7d7","observation_id":"fd89c0dd-d32e-472c-9616-f5af4505b3a4","resolution":{"observed_at":"2026-08-03T11:57:34.170283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.174831Z","title":"V eri fl: Communication- efficient and fast verifiable aggregation for federated learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.174831Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:c4b002f25fb4c0c42ad9f789d0d5de3db609b0f74af79ebb98bd242d68776643","observation_id":"09577d2c-a471-4614-a1f1-cb20ea38420c","resolution":{"observed_at":"2026-08-03T11:57:34.174831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08398","last_updated":"2024-04-12T11:07:10Z","snapshot_observed_at":"2026-08-13T00:32:01.066099Z","submitted_at":"2024-04-12T11:07:10Z","title":"Multi-Agent eXperimenter (MAX)","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.08398","snapshot_observed_at":"2026-08-03T11:57:34.179158Z","title":"G¨ urcan.Multi-Agent eXperimenter (MAX)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.179158Z"},"links":{"cited_paper":"/paper/2404.08398","citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:06a79a7f5f981bf6ef9becf027d71862f5cde1d10feac042e0ec331e810d1d00","observation_id":"6824cb63-ce02-46d1-94f8-b84823a71d0f","resolution":{"observed_at":"2026-08-03T11:57:34.179158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.183740Z","title":"Cheater-identifiable homomorphic secret sharing for outsourcing computations","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.183740Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:c41b6b7ce4a62b86caa5071b6a2422e30de82fe7e554bbf4b2fb59dd31e6b7d6","observation_id":"e7cc4f23-87c8-4869-84ec-fce0f720eb41","resolution":{"observed_at":"2026-08-03T11:57:34.183740Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.187851Z","title":"An Enciphering Scheme Based on a Card Shuffle","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.187851Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:4c816331c7a84da4eb5982a41d63d3b44516080b0f7bbc298ec3dcc761c2f266","observation_id":"ea769c71-026f-4b7f-b793-856d3a3c5ac0","resolution":{"observed_at":"2026-08-03T11:57:34.187851Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.191866Z","title":"Constant-Size Commitments to Polynomials and Their Applications","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.191866Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:99356bca079bc8dd77f69121b2fde1c2e88ac465107cd20dc7538c91afb7cde9","observation_id":"e5561006-e577-4ed3-b2aa-c456872fec8e","resolution":{"observed_at":"2026-08-03T11:57:34.191866Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.195957Z","title":"Blockchained on-device federated learning","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.195957Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:f51e8ec63b89b4eb5c3ea245d50fe895f8d191b4c2aff54449359a4aa4f79099","observation_id":"e44f81b8-4558-4a21-bff7-3bae0f3e6246","resolution":{"observed_at":"2026-08-03T11:57:34.195957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.200134Z","title":"Byzantine quorum systems","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.200134Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:8cb9db37607cc467acdfbf073aebf4bb86af0f833b8c04ab5ce65aae58fd82a6","observation_id":"36803cdb-4b40-44bd-aef6-6be5065dfd13","resolution":{"observed_at":"2026-08-03T11:57:34.200134Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.204208Z","title":"Communication- Efficient Learning of Deep Networks from Decentralized Data","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.204208Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:5f0354f34968dd572cd8e222bea902af3678fb00d0c7b8228fad610b97e44112","observation_id":"b52b442d-edfe-4a04-84fa-6ed18cc8b14b","resolution":{"observed_at":"2026-08-03T11:57:34.204208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2008.00742","last_updated":"2021-12-01T15:54:22Z","snapshot_observed_at":"2026-08-06T00:58:26.584037Z","submitted_at":"2020-08-03T09:44:07Z","title":"Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.00742","snapshot_observed_at":"2026-08-03T11:57:34.208640Z","title":"Collaborative learning as an agreement problem","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.208640Z"},"links":{"cited_paper":"/paper/2008.00742","citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:43c171a5428b5d55755dfb798386763b3c70aa232e3ddbf5af074f0f03a155f8","observation_id":"2ae3770c-24d6-4e69-bc5c-8a3d6fdf58fe","resolution":{"observed_at":"2026-08-03T11:57:34.208640Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.213413Z","title":"Genuinely distributed byzantine machine learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.213413Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:58f633266af84b74d67a0337779726e2eef71dd75b048d55ea9ba8f1725ccb37","observation_id":"29dd5c40-93ec-4a0c-b915-765cf0be324a","resolution":{"observed_at":"2026-08-03T11:57:34.213413Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.218060Z","title":"R´ enyi Differential Privacy","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.218060Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:7ae69c7937d4e6e8fef1c1bb0a228db93fb3fc39c8a6725791d090d76af721d1","observation_id":"be20a9af-b2fc-4a55-8dee-edf860077963","resolution":{"observed_at":"2026-08-03T11:57:34.218060Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.222759Z","title":"Non-Interactive and Information-Theoretic Secure Verifiable Secret Sharing","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.222759Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:f7c8b69db22ae5608dfce277e6fa4aa5209480cc1fb9ef9c612e58cca4f9d5e4","observation_id":"8999a4d4-4f37-4f49-a5f6-2220ec6a3eab","resolution":{"observed_at":"2026-08-03T11:57:34.222759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.227006Z","title":"Elsa: Secure aggregation for federated learning with malicious actors","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.227006Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:e083af8e8ab3ea346565d394027a0755d143c1e002e65ac756a27b0cc8f1e543","observation_id":"30c4c26c-85f1-4ecd-bf13-9eca35244396","resolution":{"observed_at":"2026-08-03T11:57:34.227006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.231098Z","title":"On lattices, learning with errors, random linear codes, and cryptography","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.231098Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:d14aa078d40cc308e4e279af7cc56ddeaa1b9c1421e51b08446954b5e49ab872","observation_id":"0e6fbbcf-0418-4c72-8688-a2b9b7e9421f","resolution":{"observed_at":"2026-08-03T11:57:34.231098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.235138Z","title":"An accurate, scalable and verifiable protocol for fed- erated differentially private averaging","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.235138Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:6c6df5fab0a1591d43ae58534d6e7214d86b38340c5d002d49d0e4eae34dd65e","observation_id":"e3bdfcf0-ed95-413f-84ed-69acb3c8c359","resolution":{"observed_at":"2026-08-03T11:57:34.235138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.239926Z","title":"How to share a secret","venue":null,"work_id":null,"year":1979},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.239926Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:a2a155fc2e3f87ef7a85ebd255bba6f9d5597899ce90de965b47d163797e68aa","observation_id":"f0793a01-7608-4359-b172-b00365848a76","resolution":{"observed_at":"2026-08-03T11:57:34.239926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.243977Z","title":"Biscotti: A blockchain system for private and secure federated learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.243977Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:28b191f726ed9726bba105f28c12fc275f928e7e73946ce60a8bc0acd5ad9746","observation_id":"078dc876-af87-4376-917f-731edac6260f","resolution":{"observed_at":"2026-08-03T11:57:34.243977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.248619Z","title":"Practical threshold signatures","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.248619Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:b2d9fa626fb0be935a952de2a695065102e5d3a61ac6764f27425354895dbfc3","observation_id":"b723d079-d017-4c4a-9328-16d5755841db","resolution":{"observed_at":"2026-08-03T11:57:34.248619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.253246Z","title":"Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.253246Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:4f63267673b78e166e751af413458b7788dbc60fbe8c2b62b2d46d4d3d2dec4a","observation_id":"cd160e5c-8d71-452b-a494-04bb77b5be34","resolution":{"observed_at":"2026-08-03T11:57:34.253246Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.257286Z","title":"A flexible and scalable malicious secure aggregation protocol for federated learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.257286Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:3be19f7475af2ddb5f011731010fe7d50fd2ee5135cfaa0ac124488dc10cad44","observation_id":"174ea9b2-8b04-4466-b5b0-d2119731d335","resolution":{"observed_at":"2026-08-03T11:57:34.257286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.261491Z","title":"Sum It Up: Verifiable Additive Homomorphic Secret Sharing","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.261491Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:3e69936498453ba787462a882aca2b396e9be99a6e233b8ad95f6d7c5fdad48b","observation_id":"94d0f93f-04a7-46ab-a3c0-a8a9c158d608","resolution":{"observed_at":"2026-08-03T11:57:34.261491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.266414Z","title":"VerifyNet: Secure and verifiable federated learn- ing","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.266414Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:e72b864bad53fab8930125c3944d86b51fbfe63e8dbb7eefdfbf06dff6dfc1b9","observation_id":"51d04516-2b37-45ee-8c32-edc784b20943","resolution":{"observed_at":"2026-08-03T11:57:34.266414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.270370Z","title":"Privacy risk in machine learning: Ana- lyzing the connection to overfitting","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.270370Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:948e524c933a76064de13d488f4247f07ba413ab00a202bcd206ff58e012a47e","observation_id":"2d359de4-37fc-4bb4-ab6d-1c13c4a323ab","resolution":{"observed_at":"2026-08-03T11:57:34.270370Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.274568Z","title":"See through gradients: Image batch recovery via gradinversion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.274568Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:ea33e2ac295ec8e9e8ac6851fe9f3836459033930b12b7900292100ff236e34c","observation_id":"9c361cdf-6361-42b9-b66c-6d285d54bf1d","resolution":{"observed_at":"2026-08-03T11:57:34.274568Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:57:34.278440Z","title":"Deep leakage from gradients","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T11:57:34.278440Z"},"links":{"citing_paper":"/paper/2601.04930"},"observation_digest":"sha256:e00f4b3d220fc57591bb0bbe0233405501e6306e8cc80aa2d97437991a57d737","observation_id":"8a295311-bdae-4a4f-8d28-1a6cb00d7957","resolution":{"observed_at":"2026-08-03T11:57:34.278440Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2601.04930","last_updated":"2026-06-30T10:12:41Z","latest_version":2,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-09T03:00:01.245986Z","submitted_at":"2026-01-08T13:27:53Z","title":"Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":43,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":43},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2601.04930."}