{"as_of":"2026-08-16T03:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b753d060e05ceb785df983d400b3fa155d4948fbdcea53218b35945e138d2d97","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:37:13.780831Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/1908.08649/citation-record","integrity":"/paper/1908.08649/integrity","json":"/paper/1908.08649/citation-record.json","paper":"/paper/1908.08649"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.295473Z","title":"Distributed inference with Byzantine data: State-of-the-art review on data falsification attacks,","venue":null,"work_id":"317d70b7-adb3-4c7e-9598-bde5db773bad","year":2013},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.620888Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:dadcc81c99aca215d6acb69e56947a28cf61aca56aee69ac5d74640a2e472f99","observation_id":"e7b1d1cb-1fab-48f0-b10b-0e7387f4ed41","resolution":{"observed_at":"2026-08-14T11:37:14.299570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.283250Z","title":"The Internet of Things: Secure distributed inference,","venue":null,"work_id":"a630b799-39a3-4dd8-b42e-7ba6ae7bbd52","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.626523Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:217dc097b03099a5acbb6f4c41e9774d2ee200a94d3ee12651f0bca41f1ded66","observation_id":"e0e5c590-70f6-45dd-a555-7f05ae0f62a6","resolution":{"observed_at":"2026-08-14T11:37:14.287366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.271770Z","title":"Approaches to secure inference in the Internet of Things: Performance bounds, algorithms, and effective attacks on IoT sensor networks,","venue":null,"work_id":"61b5765e-75b2-498e-aec4-6c482720e37f","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.630954Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:4cf2a9ce973f965ce42bd644bdd38aae25ffac8a378b88032abedd325512bc33","observation_id":"8853d3fc-1218-42d1-b3a5-321c2319de64","resolution":{"observed_at":"2026-08-14T11:37:14.275920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.01821","last_updated":"2015-11-05T17:28:35Z","snapshot_observed_at":"2026-08-15T22:35:47.674366Z","submitted_at":"2015-11-05T17:28:35Z","title":"Fault-Tolerant Distributed Optimization (Part IV): Constrained Optimization with Arbitrary Directed Networks","version":1},"cited_work":{"arxiv_id":"1511.01821","doi":null,"metadata_source":"pith","pith_arxiv_id":"1511.01821","snapshot_observed_at":"2026-08-14T11:37:13.938054Z","title":"Fault-Tolerant Distributed Optimization (Part IV): Constrained Optimization with Arbitrary Directed Networks","venue":"cs.DC","work_id":"80b52faa-0df7-4173-9b7d-dc4c2c7b4843","year":2015},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.635159Z"},"links":{"cited_paper":"/paper/1511.01821","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:7c7e5ef22eab9cb4f0b6472af44c6d806f67af170a84c733911e047d464c0e5d","observation_id":"adb68daa-b141-49e9-b3fc-0a6e23c04ce5","resolution":{"observed_at":"2026-08-14T11:37:13.942318Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.259845Z","title":"The Byzantine generals problem,","venue":null,"work_id":"0d784305-a473-4555-87d3-c70461443fa6","year":1982},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.642442Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:4b6da095d4dbbf2454010f43d57fb3d14aa6b07180b78faff59377c987ba3c9b","observation_id":"abde0f87-b5ea-4be3-8232-3e9d4b37e77f","resolution":{"observed_at":"2026-08-14T11:37:14.263820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.247618Z","title":"Distributed inference with M-ary quantized data in the presence of Byzantine attacks,","venue":null,"work_id":"2a9f335a-a7a6-4477-9881-fbe3315a4398","year":2014},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.647184Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:b8ba7a85bd1ddbf37587eac80ce2fc03b1e3a5d8613315a7f5c04a0ff347f931","observation_id":"eb157878-639d-411f-8de6-e443d2191a7c","resolution":{"observed_at":"2026-08-14T11:37:14.251443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.235759Z","title":"Distributed Bayesian detection in the presence of Byzantine data,","venue":null,"work_id":"72ea7a84-71f1-4fae-a34b-169fd663232e","year":2015},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.651521Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:8724c259e4fcc7c14d1fcfd8adc5059990db6f910550ed351043ab1cd0542aa6","observation_id":"746e4113-0ebb-4aee-9ee3-f22654cc0c76","resolution":{"observed_at":"2026-08-14T11:37:14.239908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.222561Z","title":"Audit bit based distributed Bayesian detection in the presence of Byzantines,","venue":null,"work_id":"1104de76-a7d2-4587-89dc-3219796774a7","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.655111Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:68d8f3eda731deafd69bb817c30ad7bcc181668e9c57bfe98527db416ac7651f","observation_id":"b28094b1-31d1-4667-8f7e-8d1821e18ebd","resolution":{"observed_at":"2026-08-14T11:37:14.227824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.208195Z","title":"Distributed detection in tree networks: Byzantines and mitigation techniques,","venue":null,"work_id":"99af4d4f-f25e-4fe5-8d85-32ce77f6082d","year":2015},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.658794Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:26e8550447a1de8220b34f7f59ca9bc64e82654e622094c70b556ffdde95bc76","observation_id":"da1bba20-d8c7-4745-b87c-fe06e4e9ece5","resolution":{"observed_at":"2026-08-14T11:37:14.213250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.195920Z","title":"Compressed sensing for networked data,","venue":null,"work_id":"0aa36324-8c6b-4956-ae30-908fbbf4f2c8","year":2008},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.662375Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:a890cd2f044b21b9b551356898c958036497594e792c7c6f0f8ee179618687ce","observation_id":"84e46f91-87d2-4c1c-8aeb-db8656aab1b6","resolution":{"observed_at":"2026-08-14T11:37:14.200808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.184347Z","title":"Localization in wireless sensor networks: Byzantines and mitigation techniques,","venue":null,"work_id":"aeed3ee5-28a9-4f08-b668-d5e28b0621c0","year":2013},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.666768Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:a79ce87d53ad571d94034e1c9499312c5b5db00669b7e4bbe77c1347f3736e2a","observation_id":"bf5034fe-623e-404d-ae25-fae0bba0e1e1","resolution":{"observed_at":"2026-08-14T11:37:14.188444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.03936","last_updated":"2019-03-10T06:26:01Z","snapshot_observed_at":"2026-08-14T17:04:44.423711Z","submitted_at":"2019-03-10T06:26:01Z","title":"Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.03936","snapshot_observed_at":"2026-08-14T11:37:13.670632Z","title":"Fall of empires: Breaking Byzantine-tolerant SGD by inner product manipulation,","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.670632Z"},"links":{"cited_paper":"/paper/1903.03936","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:4f778d8353d23877fc104ad000349868d86dc4248927fbd7ae15ec02d2e606da","observation_id":"692e6362-6286-488e-b648-876672d1f055","resolution":{"observed_at":"2026-08-14T11:37:13.670632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.11815","last_updated":"2021-11-21T19:04:57Z","snapshot_observed_at":"2026-08-05T22:36:46.924843Z","submitted_at":"2019-11-26T20:10:04Z","title":"Local Model Poisoning Attacks to Byzantine-Robust Federated Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.11815","snapshot_observed_at":"2026-08-14T11:37:13.675396Z","title":"Local model poisoning attacks to Byzantine-robust federated learning,","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.675396Z"},"links":{"cited_paper":"/paper/1911.11815","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:7aa6fadcfefb3b080f20417fde59586e23737ca454c7033a6e35e34ef9c37ce1","observation_id":"f344c2c6-e7cf-4859-acf5-a7e900dbc015","resolution":{"observed_at":"2026-08-14T11:37:13.675396Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.172935Z","title":"A little is enough: Circumventing defenses for distributed learning,","venue":null,"work_id":"edabddb9-bf79-4f6b-be59-cf69ad8af0d7","year":2019},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.679433Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:2dd24ad198c1e4542bf9c367dcd02651f20b143c8b246ddf65cbc13122df6859","observation_id":"408dd420-c8c6-455c-bc30-f1637159c567","resolution":{"observed_at":"2026-08-14T11:37:14.176873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.161289Z","title":"Byzantine-robust distributed learning: Towards optimal statistical rates,","venue":null,"work_id":"6e0a6d41-8216-4285-b832-d61a4037a274","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.682703Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:a757932f2f63eb4167725600d72195aa3a4ee3fff744764cff2c7222b441df7a","observation_id":"551e8e43-9082-44d6-ac20-85096fe1c9eb","resolution":{"observed_at":"2026-08-14T11:37:14.166030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.148966Z","title":"Distributed statistical machine learning in adversarial settings: Byzantine gradient descent,","venue":null,"work_id":"6c8ef790-577c-41d1-bc67-ee238e4ab616","year":2017},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.686880Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:447326618e4ed4f8ef7cc57e7c9b67e97f098eef68f8c2f4e48c03ac7cb95fb5","observation_id":"eeaed2b0-f842-4126-973e-e5e2bf2fb6fa","resolution":{"observed_at":"2026-08-14T11:37:14.153348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.137225Z","title":"Machine learning with adversaries: Byzantine tolerant gradient descent,","venue":null,"work_id":"97e688aa-da7d-4125-9cef-f638381c2ec1","year":2017},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.690749Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:295a85f7ec421993f52d44fdc2cec504045a3aaee59c5e19711c4a9c9673969a","observation_id":"b5da4a3f-5219-43eb-9301-97cc9d4ca7ff","resolution":{"observed_at":"2026-08-14T11:37:14.140961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.125896Z","title":"The hidden vulnerability of distributed learning in Byzantium,","venue":null,"work_id":"11aa1f98-0724-4fd9-a29a-47f96803ffed","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.694803Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:8bb9d9cc7972e449d5028bdccacdd09d63fe7d5762274fe43777b8f2eabec0da","observation_id":"8cf6366c-60be-4f24-870d-91c70a2bb4dc","resolution":{"observed_at":"2026-08-14T11:37:14.129821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.04374","last_updated":"2021-02-05T16:44:25Z","snapshot_observed_at":"2026-08-14T16:37:04.714910Z","submitted_at":"2019-05-05T16:41:25Z","title":"Fast and Robust Distributed Learning in High Dimension","version":2},"cited_work":{"arxiv_id":"1905.04374","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.04374","snapshot_observed_at":"2026-08-14T11:37:13.895642Z","title":"Fast and Robust Distributed Learning in High Dimension","venue":"cs.DC","work_id":"69ad66d3-0d97-4010-b927-dea10e49a9f1","year":2019},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.698854Z"},"links":{"cited_paper":"/paper/1905.04374","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:00c024356c87bf4631c13eb27ad95ea353d65dca4904100a44eae479227c44e7","observation_id":"fc66d2a8-e124-4359-a8c4-ccbd1adff089","resolution":{"observed_at":"2026-08-14T11:37:13.902079Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.10032","last_updated":"2019-05-18T00:52:06Z","snapshot_observed_at":"2026-08-15T22:29:05.465187Z","submitted_at":"2018-05-25T08:33:24Z","title":"Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.10032","snapshot_observed_at":"2026-08-14T11:37:13.702602Z","title":"Zeno: Byzantine-suspicious stochastic gradient descent,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.702602Z"},"links":{"cited_paper":"/paper/1805.10032","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:3b3728471880fb4c3fd4ba15bd759dd18fc1842b43b8d17c0a964755e8a6657b","observation_id":"b49beb3c-4cb4-4d3c-a264-c63339ee0a76","resolution":{"observed_at":"2026-08-14T11:37:13.702602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.07020","last_updated":"2021-05-09T17:42:44Z","snapshot_observed_at":"2026-08-14T17:01:13.216795Z","submitted_at":"2019-03-17T03:02:32Z","title":"Zeno++: Robust Fully Asynchronous SGD","version":5},"cited_work":{"arxiv_id":"1903.07020","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.07020","snapshot_observed_at":"2026-08-14T11:37:13.862123Z","title":"Zeno++: Robust Fully Asynchronous SGD","venue":"cs.LG","work_id":"22a478ab-3f85-447c-a044-19b19ee0057f","year":2019},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.707094Z"},"links":{"cited_paper":"/paper/1903.07020","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:a8593a8731e57102504d997a1106090e669f4467d7d2c2baa110e0279e335a7e","observation_id":"dc1e6005-1534-4a6b-8c26-3eb95a9688b0","resolution":{"observed_at":"2026-08-14T11:37:13.868372Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.10116","last_updated":"2018-03-23T20:08:04Z","snapshot_observed_at":"2026-08-15T22:33:57.606953Z","submitted_at":"2018-02-27T19:06:15Z","title":"Generalized Byzantine-tolerant SGD","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.10116","snapshot_observed_at":"2026-08-14T11:37:13.710906Z","title":"Generalized Byzantine-tolerant SGD,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.710906Z"},"links":{"cited_paper":"/paper/1802.10116","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:c0c0fef71340f7ef19c121d7cf9b4efec67f6cb8c8c6e96c94941b5548166e1a","observation_id":"6b50202b-3744-4233-a1c8-131bb3a556c4","resolution":{"observed_at":"2026-08-14T11:37:13.710906Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.114966Z","title":"RSA: Byzantine-robust stochastic aggregation methods for distributed learning from heterogeneous datasets,","venue":null,"work_id":"443b7e12-585c-497a-b016-96217e343299","year":2019},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.714823Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:00165117b8da90202218df89f7b031c96e273262c2097f48726bef3f7d862608","observation_id":"1b9d23f5-760a-4b7b-926f-cdaa0222ebe7","resolution":{"observed_at":"2026-08-14T11:37:14.118758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.05291","last_updated":"2019-02-22T19:55:48Z","snapshot_observed_at":"2026-08-14T18:15:53.973316Z","submitted_at":"2018-10-11T23:50:32Z","title":"signSGD with Majority Vote is Communication Efficient And Fault Tolerant","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.05291","snapshot_observed_at":"2026-08-14T11:37:13.718689Z","title":"signSGD with majority vote is communication efficient and Byzantine fault tolerant,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.718689Z"},"links":{"cited_paper":"/paper/1810.05291","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:903eeedb6cd8ea78e41975abf8cf73f78a1c30bff5f8b5d80f487d188cfd1f66","observation_id":"65c17432-f4a4-459a-b00b-9a1cca05c7b8","resolution":{"observed_at":"2026-08-14T11:37:13.718689Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.104421Z","title":"Byzantine stochastic gradient descent,","venue":null,"work_id":"e5597480-2ccd-43b8-b46b-fef4b3e93e49","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.722520Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:2965781b3d06a9565f3420d388610e1bbfed0061871806c3730937310c52a52f","observation_id":"653955b4-b374-4628-b3c8-5c9e61380249","resolution":{"observed_at":"2026-08-14T11:37:14.107985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.093560Z","title":"Resilient asymptotic consensus in robust networks,","venue":null,"work_id":"e30e3669-0606-4a83-bc0f-09d32a2b94f3","year":2013},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.726070Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:80100a2bcd90ad76a29ca5bd13e13ff4b7bab8856b33c6f06489c2473fb1d56a","observation_id":"00f06e40-d9a0-4f0b-a9cb-10a7caff1d4f","resolution":{"observed_at":"2026-08-14T11:37:14.097533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1203.1888","last_updated":"2012-03-08T19:00:19Z","snapshot_observed_at":"2026-08-15T04:16:52.607761Z","submitted_at":"2012-03-08T19:00:19Z","title":"Matrix Representation of Iterative Approximate Byzantine Consensus in Directed Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1203.1888","snapshot_observed_at":"2026-08-14T11:37:13.729970Z","title":"Matrix representation of iterative approximate Byzantine consensus in directed graphs,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.729970Z"},"links":{"cited_paper":"/paper/1203.1888","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:b06eb4f1f8a813d5743b5e7c03413c058b5adb17b9f700232ba6a458c2272a1c","observation_id":"10a8a927-8c94-421a-9d99-64905162644b","resolution":{"observed_at":"2026-08-14T11:37:13.729970Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.082459Z","title":"Approximate Byzantine consensus in faulty asynchronous networks,","venue":null,"work_id":"47ad2315-c956-47f4-a199-2e3ebdf5454c","year":2015},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.734943Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:308e819db299f553e716ab847bf66ba369e4e696f01fc1e5cbe1a46c32d51cb0","observation_id":"636bb234-b7f7-429f-a22f-a1ecef1c7c3e","resolution":{"observed_at":"2026-08-14T11:37:14.086306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.069659Z","title":"Stochastic and deterministic fault detection for randomized gossip algorithms,","venue":null,"work_id":"4c9ac8f8-b2af-409b-922e-1ce6cf409fa5","year":2017},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.738829Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:8a19b5ba4664e015f193f922c06692e22c29a321f04633065054ba4704881d8f","observation_id":"7cab1076-d80d-422b-a5e3-1d6175a0cb18","resolution":{"observed_at":"2026-08-14T11:37:14.074310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.056345Z","title":"An adaptive deviation-tolerant secure scheme for distributed cooperative spectrum sensing,","venue":null,"work_id":"e57699f4-b8a7-4923-be3a-ed4401586b9b","year":2012},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.743344Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:cd42791b169b4960673eb79f9a1f1d3f1623b3733466a8a60c30e8c0a96d28c2","observation_id":"fc87e9f0-a9b5-4382-896c-462e1f9fcb4e","resolution":{"observed_at":"2026-08-14T11:37:14.060953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.044510Z","title":"Byzantine-resilient locally optimum detection using collaborative autonomous networks,","venue":null,"work_id":"91ecb1b6-351c-4079-843c-3b304fe064c5","year":2017},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.747347Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:959338e1db8f60cea40c4143003790c0fb04733e425293d6ddb25e47cc9632de","observation_id":"615af1a1-41c9-41b4-b8f7-e24015566176","resolution":{"observed_at":"2026-08-14T11:37:14.048440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.033396Z","title":"Data falsification attacks on consensus-based detection systems,","venue":null,"work_id":"b60af640-5724-4ead-96ff-2b55fe4bd860","year":2017},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.751043Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:2a9f7596b17e4849197f38ba7d69f1876c17d54d4735e76f757ad45a3da6234b","observation_id":"1260788f-f07a-41ed-b92c-773a8789e81b","resolution":{"observed_at":"2026-08-14T11:37:14.037320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.021943Z","title":"Resilient distributed parameter estimation in heterogeneous time-varying networks,","venue":null,"work_id":"cea1c1d0-ff3c-4ee2-bf7b-038331155d3e","year":2014},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.754303Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:11e96931f91b1652dd4a958b88e7ba9677c964d0727d5e19ab352b523f09aa9a","observation_id":"05735766-8a29-4bec-901b-129aac0321d4","resolution":{"observed_at":"2026-08-14T11:37:14.026023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:14.010214Z","title":"Resilient distributed estimation: Sensor attacks,","venue":null,"work_id":"9d194580-fd1c-4612-ba59-e86e261ac519","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.757824Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:a35cc1820ff6ac40a32880e0cc3ae35c158e6597371d6fbced2e8b119e52ee05","observation_id":"290d8f36-d4f5-4050-ab2c-da512b1eae44","resolution":{"observed_at":"2026-08-14T11:37:14.014264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:13.997903Z","title":"Resilient distributed estimation: Exponential convergence under sensor attacks,","venue":null,"work_id":"0d803cb5-88ba-46d8-ad0a-123520812e68","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.761472Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:6d8d40fe344e55f7ffac9075b2ce10fbe9633d3d06e754b6a021cedc264fd228","observation_id":"23f3f07b-f63b-490d-be28-14d9568f537d","resolution":{"observed_at":"2026-08-14T11:37:14.002446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:13.986843Z","title":"Resilient distributed estimation through adversary detection,","venue":null,"work_id":"e3d7745b-600e-4dcd-90e1-45fb2c669e94","year":2018},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.764942Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:1402d3432d91528bf57841dce45f699a05f7bb9d8ab6e0d4eb1c3f58afd674f5","observation_id":"edea064e-9ef5-45b1-8a48-1edf9cab2e83","resolution":{"observed_at":"2026-08-14T11:37:13.990737Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:13.974732Z","title":"Distributed subgradient methods for multi-agent optimization,","venue":null,"work_id":"2516f2a9-decf-41ef-9635-7819abbde4f1","year":2009},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.768904Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:c42d5b977d244f9b503d57d9dbbf415e4e2879bbcb30273b4dce69a05b573866","observation_id":"54a03559-4346-4a91-9f2c-b16b274d69a3","resolution":{"observed_at":"2026-08-14T11:37:13.979111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:13.962105Z","title":"Distributed optimization under adversarial nodes,","venue":null,"work_id":"64c4633f-39f3-4308-9368-72ae0c87c902","year":2019},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.772843Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:cdbd0fec1a28c081527b7e059ad4b8e4006230ef6699e8a84b25b1067ad6f93a","observation_id":"63258b4e-b872-4e71-a53e-1cb7b4b33c35","resolution":{"observed_at":"2026-08-14T11:37:13.965925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:37:13.950623Z","title":"ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning,","venue":null,"work_id":"aeea0608-9ef0-4569-bce4-a3fc23ab5694","year":2019},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.776571Z"},"links":{"citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:2933137edfbe64a60721b12c04681381945d02b49f0832a91dba781d78de196b","observation_id":"535d37b7-8d32-4ceb-a577-5903890ffad5","resolution":{"observed_at":"2026-08-14T11:37:13.954594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.08098","last_updated":"2022-06-15T02:06:56Z","snapshot_observed_at":"2026-08-15T21:29:34.120925Z","submitted_at":"2019-08-21T19:49:56Z","title":"BRIDGE: Byzantine-resilient Decentralized Gradient Descent","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.08098","snapshot_observed_at":"2026-08-14T11:37:13.780831Z","title":"BRIDGE: Byzantine-resilient decentralized gradient descent,","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T11:37:13.780831Z"},"links":{"cited_paper":"/paper/1908.08098","citing_paper":"/paper/1908.08649"},"observation_digest":"sha256:8ed5438a213539661d57931d10f1745732e92573fdd5b42c4b8a515377740f5e","observation_id":"79d74b4d-d304-4ffe-ba79-aad40d71a466","resolution":{"observed_at":"2026-08-14T11:37:13.780831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"1908.08649","last_updated":"2020-06-02T02:21:10Z","latest_version":3,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-15T22:34:52.369333Z","submitted_at":"2019-08-23T03:23:49Z","title":"Adversary-resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":3,"verified_fuzzy":30},"total_outbound_references":40},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:1908.08649."}