{"as_of":"2026-08-13T10:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:39b4e215d685f4ee6cac1d38f61ebb9173ff312e24a305da4c25553fb4531e96","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T15:15:44.365553Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2411.14557/citation-record","integrity":"/paper/2411.14557/integrity","json":"/paper/2411.14557/citation-record.json","paper":"/paper/2411.14557"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:15:45.190386Z","title":"The continuation power flow: A tool for steady state voltage stability analysis,","venue":null,"work_id":"a4ead3e4-8459-47c2-80d7-d5cf3fab757f","year":1992},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.117561Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:200185491072624e8adad6f5a5e99fb695535e51d0fa6549a9ccc437eda47fe5","observation_id":"9511fa1f-aeda-46c9-9d14-43255fd9d92c","resolution":{"observed_at":"2026-08-12T15:15:45.195326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.177011Z","title":"Smart meter data privacy: A survey,","venue":null,"work_id":"8c27cd62-8980-4dd6-a6e3-513b4fbe3a8d","year":2017},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.122065Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:4ae12b7b17cff4ee9a46c7f46585e23d7a29b179dbb4be2b114ce41c03a1791f","observation_id":"b104506e-d403-48e6-b545-522193c1467a","resolution":{"observed_at":"2026-08-12T15:15:45.181203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.164915Z","title":"Private Memoirs of a Smart Meter,","venue":null,"work_id":"aaf93de4-d326-485e-98f5-a269fe64e1f5","year":2010},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.125954Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:c22e7c8be30d28f5b3e9d3f5a358384e69374c50f1f92a3ef785062aa81a4bf8","observation_id":"065ae08e-d36a-4404-bc37-5d416d6d8bc9","resolution":{"observed_at":"2026-08-12T15:15:45.168823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.152306Z","title":"Multimedia content identification through smart meter power usage profiles,","venue":null,"work_id":"4958bef1-cc99-4cfe-a292-ea8aa6973692","year":2012},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.129748Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:8af491bedfde94eef942f9f2e41ba6e902dd0a6483c854106b9cb3cc48e14643","observation_id":"150eaf25-2edf-4b0a-af3f-3d943499e01e","resolution":{"observed_at":"2026-08-12T15:15:45.156704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.139366Z","title":"Dynamic energy-consumption indi- cators for domestic appliances: environment, behaviour and design,","venue":null,"work_id":"a108c44e-dd57-46dd-a45a-b3c2817e9cd6","year":2003},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.134147Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:11d38b3aaecd81a907a70b1dac5f55ad99f89f54fa310d58297e2d978ae31dd3","observation_id":"31ea36ed-9480-490a-8de1-f115220a7947","resolution":{"observed_at":"2026-08-12T15:15:45.143794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.126016Z","title":"Security and privacy challenges in the smart grid,","venue":null,"work_id":"0462a3da-ed9f-497a-9dd9-4cace8bf46ba","year":2009},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.138259Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:b6ac7416c112c1c81cc38d2ddbeb7355e0ea299bdaa630dae1f633ceafb82a16","observation_id":"991f5ce3-79f6-430c-bce3-361882eed41f","resolution":{"observed_at":"2026-08-12T15:15:45.130657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.112756Z","title":"SOK: Privacy tech- nologies for smart grids – A survey of options,","venue":null,"work_id":"247a6214-59ac-4e31-a981-7a330f99586a","year":2012},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.143094Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:2a501cf7ec4a2fb8ca45e8bd121170363e21cb1fa5ad98c18f1064535e10cc12","observation_id":"4d2e46ab-9a8d-4f49-95d2-b4ab072dc682","resolution":{"observed_at":"2026-08-12T15:15:45.117056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.098086Z","title":"Essential regulatory requirements and recommendations for data handling, data safety, and consumer protection,","venue":null,"work_id":"3755faa9-2efe-4524-acdf-af37586eb493","year":2015},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.147397Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:e0e0bad05ff0bc5b03e4c7ac691a2e63cba94a109f6bf19332c0c0ac69899d83","observation_id":"fcb8349e-af59-4393-af16-526c0ce93116","resolution":{"observed_at":"2026-08-12T15:15:45.103621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.084344Z","title":"Nistir 7628 rev. 1: Guidelines for smart grid cybersecurity,","venue":null,"work_id":"5c0c0471-e1e0-41f5-b30c-b624282a2bc3","year":2014},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.151513Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:23ff036e873e97b25decc7acaedd5b7b68e7d2af6712d15e78c3be1a18e51adf","observation_id":"13d7d1c8-d214-4782-98bf-1a3fef5233db","resolution":{"observed_at":"2026-08-12T15:15:45.088821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.070420Z","title":"Zhu, Optimization of Power System Operation","venue":null,"work_id":"1167f104-008e-4369-ab8e-35bbcde61b5f","year":2015},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.155797Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:0dd074f5a6c4be0824fa109bda847d96a537a7717838caab6ec387ff9940010f","observation_id":"49015e36-a5ac-4d76-92b4-1d246545a1a3","resolution":{"observed_at":"2026-08-12T15:15:45.074649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.056519Z","title":"Opti- mal power flow: An introduction to predictive, distributed and stochastic control challenges,","venue":null,"work_id":"9062cb93-21d0-4ec3-a8e0-dfff07d92931","year":2018},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.160035Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:c9cf4fa107e93dde8d16ada691f144dc33ff111b27eb4515e2989b007be401e6","observation_id":"b1ba0c7b-0481-4e9a-b43e-653d8f2ee1ec","resolution":{"observed_at":"2026-08-12T15:15:45.061093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.043225Z","title":"Smart Grid Privacy via Anonymiza- tion of Smart Metering Data,","venue":null,"work_id":"a7027bb6-f125-4165-9120-4297b3b451e5","year":2010},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.165132Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:9ebcd72fa395f1572102e0a0414825f11cbea231beee3a3c8e8bcb244525850d","observation_id":"aa5c54ad-64e3-479f-bd8f-afa6ee9e7a95","resolution":{"observed_at":"2026-08-12T15:15:45.047043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.031054Z","title":"I Have a DREAM!(DiffeRentially privatE smArt Metering),","venue":null,"work_id":"45cfd0c1-2a18-4694-a6d9-d99e5e19b321","year":2011},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.170299Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:42e793d6b1dc85e8af46a416381bbab8437664de53e915251f55dbc76f8e6cf7","observation_id":"f47561e1-1de0-496c-8fd7-980f77915091","resolution":{"observed_at":"2026-08-12T15:15:45.034859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.018230Z","title":"Differentially private state estimation in distribution networks with smart meters,","venue":null,"work_id":"fedd9710-6f62-46c4-a013-3e88fa6c049b","year":2015},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.174470Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:db67548d65404b8230e3acea9e77691dfa9b808779a60d0288daa6a38eed3c3f","observation_id":"11e403a7-7b8f-4ca2-8e35-5991986f7638","resolution":{"observed_at":"2026-08-12T15:15:45.022571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:45.005319Z","title":"Differential privacy for power grid obfuscation,","venue":null,"work_id":"5a19a3a6-2b20-4d81-808c-945112f60f30","year":2020},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.178722Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:e4097d201f349ff9f82d137a04f45556b7629e52556ca9259e575c065e4a5ff1","observation_id":"1be51cc9-1dfb-4c82-a295-e981831b969c","resolution":{"observed_at":"2026-08-12T15:15:45.009691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.991867Z","title":"Preserving privacy of smart meter data in a smart grid environment,","venue":null,"work_id":"3ae7897a-bc70-48c2-af85-eca2630e7bf8","year":2021},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.183149Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:3eeb3962d8128c0b66c3eb8bdb8d556880d8f36f1b2983e90f2f1cbf420d0f4a","observation_id":"a7b8e1b7-2b57-407c-9fa4-f0cb4f558d80","resolution":{"observed_at":"2026-08-12T15:15:44.996189Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.978214Z","title":"Privacy-Preserving Probabilistic Voltage Forecasting in Local Energy Communities,","venue":null,"work_id":"f4d5352c-281c-4b46-b556-80ccfabdbd34","year":2023},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.187932Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:dc4745f174b81f1910c105fc1e1ad112bb2ad08a8c77f26edd5fff1a396c6810","observation_id":"2a8c5f70-4fa5-4603-bf83-aeaab38d0e49","resolution":{"observed_at":"2026-08-12T15:15:44.982554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.964599Z","title":"DPWGAN: High-Quality Load Profiles Synthesis with Differential Privacy Guarantees,","venue":null,"work_id":"71117f03-768d-4c17-8bf4-49730906330d","year":2022},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.192438Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:42e719c795110b653da3d86b4eb473ffdf5cafe74ad477859a1962186d5ad9fa","observation_id":"817d4fd1-b96e-46d1-aa30-c40ba9696e8f","resolution":{"observed_at":"2026-08-12T15:15:44.969078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.950572Z","title":"Privacy-Friendly Energy-Metering via Homomorphic Encryption,","venue":null,"work_id":"554a94fd-fa84-43d0-a628-ece65fab4cdd","year":2010},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.196747Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:5f58943d9de5389ced961957f398394b9104cb680daca54e4cd2384f293c29bb","observation_id":"73d2847e-1bfa-4a0c-9dd4-b715219499d0","resolution":{"observed_at":"2026-08-12T15:15:44.955428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.937544Z","title":"Secure Information Aggregation for Smart Grids using Homomorphic Encryption,","venue":null,"work_id":"8a6a75af-f641-4df5-ae0b-c20e9909178d","year":2010},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.200997Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:3e00674b2b85badeb01f310d56450155c67df263b44479b25dedbb729496a50f","observation_id":"f9a89b1b-d5f3-450b-81bb-322af2b69357","resolution":{"observed_at":"2026-08-12T15:15:44.941838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.924403Z","title":"Efficient and Privacy-Preserving Metering Protocols for Smart Grid Systems,","venue":null,"work_id":"b1ff5f7d-5f39-4602-955a-a9ac11f90d65","year":2016},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.205351Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:3174c98316c0ed83c9629f59311eaac5c0ca52508ad8f978e8e368003e86ac5b","observation_id":"cf220879-28f9-438b-817b-2bc199c3153c","resolution":{"observed_at":"2026-08-12T15:15:44.928911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.911172Z","title":"Privacy-preserving distributed eco- nomic dispatch of microgrids: A dynamic quantization-based consensus scheme with homomorphic encryption,","venue":null,"work_id":"2b6ae941-8870-479f-a761-f9a70335fd77","year":2022},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.209522Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:98a32f1ac3dd2df1168ed1c7ef19321bc3b3adaef63f378f05177971bc6b27d9","observation_id":"0b18e5b3-4779-49e4-9eae-d92571837e73","resolution":{"observed_at":"2026-08-12T15:15:44.915593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.898754Z","title":"Privacy-Preserving Distributed Optimal Power Flow with Partially Homomorphic Encryption,","venue":null,"work_id":"3efdb9bf-1b00-42ae-abeb-1430a8c592c2","year":2021},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.213536Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:e2585afd4849b25c41440d61103e41193527ff915b5f1536156e304298dc9e99","observation_id":"277359d9-2f19-48dd-8b38-1dbc304e029b","resolution":{"observed_at":"2026-08-12T15:15:44.902993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.886259Z","title":"Privacy- friendly forecasting for the smart grid using homomorphic encryption and the group method of data handling,","venue":null,"work_id":"57b6864c-043d-4716-96b0-3f8295ee7323","year":null},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.217790Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:2e891214799ae5c135ec4d98ed580039a0dbb5d284670ed44f3ae72d88f7cb32","observation_id":"d7e49824-713c-4a12-9bac-e5bfb0319e59","resolution":{"observed_at":"2026-08-12T15:15:44.890484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.871463Z","title":"A secure and privacy-preserving protocol for smart metering operational data collection,","venue":null,"work_id":"252f157d-2240-4240-8d12-a8760150fb41","year":2019},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.222016Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:12a640e91846b4f71bfd26c552465f7b76906714ac98a1c21440aa62004ba9a9","observation_id":"20936f0f-b74f-49d3-a204-57ec471363af","resolution":{"observed_at":"2026-08-12T15:15:44.876706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.857809Z","title":"Privacy-friendly aggrega- tion for the smart-grid,","venue":null,"work_id":"c29127df-472e-4177-ad97-7ea131961036","year":null},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.226432Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:dcd2eb676ef4aa3773a1b6246373c62a2ebae6b126189fd40c8640492fcc46f4","observation_id":"3bdd7d40-e4c5-4b2a-8bc3-cad47e293a42","resolution":{"observed_at":"2026-08-12T15:15:44.862178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.844772Z","title":"Smart meter aggregation via secret-sharing,","venue":null,"work_id":"53da25b8-0599-4f5e-bb43-c7ed4c237854","year":2013},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.230176Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:316b268e8fd932b4f1d7e27b679f60cc994ec52aa6c78d1c6fab8f9b9eeb6fb9","observation_id":"f9ad64d4-74c7-4fd8-b068-d061ac02921d","resolution":{"observed_at":"2026-08-12T15:15:44.849114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.830697Z","title":"Fully privacy-preserving distributed optimization in power systems based on secret sharing,","venue":null,"work_id":"048798fb-0ca1-4c4e-a340-ad9af5362fed","year":2022},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.233731Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:87dda3ca1b53eaca2fb9a5f12d6ed3ff41ba3e0a26bf6d7273e419cf4042c099","observation_id":"c594d1b2-4dd7-4039-ab68-ce64e58c7b0d","resolution":{"observed_at":"2026-08-12T15:15:44.835020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.817742Z","title":"Distributed optimization for integrated energy systems with secure multiparty com- putation,","venue":null,"work_id":"15db1c67-6885-4e50-93d3-5c898fe488e3","year":2023},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.237523Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:e26dc25950eeb8ccc6a0fc289d1a26decef87ff9afa127a48bc1ac87eb55b8a4","observation_id":"dd130c52-7009-4688-bf37-0493d1ebb158","resolution":{"observed_at":"2026-08-12T15:15:44.821951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.804278Z","title":"Bidi- rectional privacy-preserving network-constrained peer-to-peer energy trading based on secure multiparty computation and blockchain,","venue":null,"work_id":"61828f64-aa8f-4aab-b88c-2821e0e52f8c","year":2023},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.241338Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:3ee8bd9e2c98b897d60d76321f19f0338f727b65aa478fa6367f29aabf87482c","observation_id":"4477692d-9123-40f3-84b4-df44ae17e084","resolution":{"observed_at":"2026-08-12T15:15:44.809055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.791014Z","title":"An MPC-based privacy-preserving protocol for a local electricity trading market,","venue":null,"work_id":"f400db96-998b-4cf4-acf8-5dfb89f14b15","year":2016},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.245303Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:ed98f4b06788bca4b6577dd3aaaddf98e96909831d09131edfd7ef2f012bec71","observation_id":"a3b21086-6829-4101-b2b7-4705a3297d13","resolution":{"observed_at":"2026-08-12T15:15:44.795473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.778030Z","title":"Energy block- based peer-to-peer contract trading with secure multi-party computation 12 in nanogrid,","venue":null,"work_id":"a627ab56-bf49-4faa-bb9a-9c0f1b314be6","year":2022},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.248828Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:2f23d0749450695cb15acacd71573800f909f93403830950f044bf70528b19b0","observation_id":"ed40f741-f9dc-4688-a8c4-307f691104b9","resolution":{"observed_at":"2026-08-12T15:15:44.782210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.765513Z","title":"Universally composable security: A new paradigm for cryptographic protocols,","venue":null,"work_id":"10589826-a7bc-4397-9f46-55ae193b65ef","year":2001},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.252947Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:6d31de5f99a97ff6bd40b167422092b4fea67bd40487dc3503eb465a9f578038","observation_id":"ffb91269-6c95-4bfa-8885-2844f2ba82cb","resolution":{"observed_at":"2026-08-12T15:15:44.769715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.753454Z","title":"Efficient Multiparty Protocols Using Circuit Randomiza- tion,","venue":null,"work_id":"79975247-7238-49e9-a5d8-b363aa72112c","year":1991},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.257097Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:94617c7a0af7032f3316a8e4c45f2c053ff407540a15c2ef1814b18f9e3c2244","observation_id":"a7db757a-f31c-4485-a7fe-2eed40d53825","resolution":{"observed_at":"2026-08-12T15:15:44.757309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.738902Z","title":"Secure computation with fixed-point num- bers,","venue":null,"work_id":"a8414f4a-3b39-4389-838d-3c305228e587","year":2010},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.261910Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:c2f7e53e3b9bc2ccd7d8f677b238c78e508bbbd9185acbe68187903630f9b69d","observation_id":"4f3b8ae3-8520-4fde-9476-7a18b2f864f3","resolution":{"observed_at":"2026-08-12T15:15:44.744358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.723790Z","title":"Benchmarking Privacy Preserving Scientific Operations,","venue":null,"work_id":"485bcab3-c18f-49bb-876a-95aba84365ab","year":2019},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.266313Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:be888cbc6e13ccbfc0e61dd034d5c592b9d003b82afeb6d7d9592c08c0c8c37f","observation_id":"3fcbe0e8-38f9-4f38-835f-cd9a43128a78","resolution":{"observed_at":"2026-08-12T15:15:44.729377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.709504Z","title":"Overdrive: Making SPDZ great again,","venue":null,"work_id":"5b36aeae-a19b-4601-ae31-a1eec777acc5","year":2018},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.270555Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:af148ff77cd14bf2f9f62df9129ace713d755c30eabf312d2fa32d97ffe45f37","observation_id":"4e7008a9-dd08-484f-8503-5e105961dbe2","resolution":{"observed_at":"2026-08-12T15:15:44.713932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.694774Z","title":"MASCOT: Faster Malicious Arithmetic Secure Computation with Oblivious Transfer,","venue":null,"work_id":"8a145964-703f-4392-ae98-ec1561165b7d","year":2016},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.275552Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:7efaf00ac1d993f2486c167abaccde9ebcaf43ae69b6fb63a87090820abb4297","observation_id":"50ffa461-9a8e-44f1-9bdf-9f1b1275f008","resolution":{"observed_at":"2026-08-12T15:15:44.699559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.681070Z","title":"Completeness theorems for non-cryptographic fault-tolerant distributed computation (extended abstract),","venue":null,"work_id":"17a2f626-e6f4-4c92-8fe6-ee55fb978798","year":null},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.279804Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:46a5cd2aa902c4547914f73d326be03b24797a8bda2af744ea14778e2e0e69e4","observation_id":"baac48ac-fad7-4680-a484-5b3152df7693","resolution":{"observed_at":"2026-08-12T15:15:44.685617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.666971Z","title":"Multiparty unconditionally secure protocols (extended abstract),","venue":null,"work_id":"a07bff13-0485-408e-a4f6-9fb06e943b04","year":null},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.284124Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:fb424f150c02491a6bddf784719826654ef2e4b6f9e0ca6ca36887a4e589c394","observation_id":"c707163f-aea6-46af-9dbe-1ae739fc8d30","resolution":{"observed_at":"2026-08-12T15:15:44.671827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.652157Z","title":"On a comparison of Newton- Raphson solvers for power flow problems,","venue":null,"work_id":"902855ad-2b35-4d5e-8c63-ee23a8837084","year":2019},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.288397Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:9aeb4cdc80de589b4a5a01641f9e96c045ca703a3f04ebfded2cb985ebf99405","observation_id":"d7a6ea8a-12f3-4687-b65d-ca9c30b3cdfa","resolution":{"observed_at":"2026-08-12T15:15:44.657351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.638751Z","title":"Newton-raphson Method in Complex Form,","venue":null,"work_id":"90de065e-50f2-4558-9db6-473cef256e0c","year":1997},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.292499Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:f6cd2c9027851d843164b641e6e95ad747731bef4780c20f7aed846695dd588c","observation_id":"4245dd0e-c29c-402c-ba98-5f4a52f2ecce","resolution":{"observed_at":"2026-08-12T15:15:44.643221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:15:44.296581Z","title":"Nocedal and S","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.296581Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:f26883a2be5a10ed75ed043b9ea8e660e9188c20eb19cbbf4ed7a52a66d4b139","observation_id":"791658e2-82b8-4d9c-9be0-292d376ae0cb","resolution":{"observed_at":"2026-08-12T15:15:44.296581Z","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":"2026-08-12T15:15:44.615758Z","title":null,"venue":null,"work_id":"a3a89dfa-bff2-4741-9970-fc740686ff33","year":2007},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.300494Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:4fbabccd879d1b5cd231be118b1075d9dcf247fbbd4362acdbbced254de7fbd0","observation_id":"ff5b9212-f893-4e24-a003-ee01ef728c4a","resolution":{"observed_at":"2026-08-12T15:15:44.620042Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.602939Z","title":"Saad, Iterative Methods for Sparse Linear Systems","venue":null,"work_id":"bcb5a6d3-c0c1-4269-a653-7a126e0e0724","year":2003},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.304796Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:26d1c889a4e5c3d2f5ad309f6db58b0677778051bdcd5500fad8645ca9641ce3","observation_id":"5d80de4e-5878-478d-98fd-2187786d5edb","resolution":{"observed_at":"2026-08-12T15:15:44.607325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.589819Z","title":"A full proof of the BGW protocol for perfectly secure multiparty computation,","venue":null,"work_id":"dcea1406-e834-41d3-8f00-001b2a68dc98","year":2017},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.308757Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:aa596304fc5ad6e12c2a1d4c2edf4389a1f6cd7ffd01abae57a355f19e105a04","observation_id":"2f3c817b-2027-4c04-bf6f-7a34531ed46f","resolution":{"observed_at":"2026-08-12T15:15:44.594250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.576958Z","title":"ATLAS: efficient and scalable MPC in the honest majority setting,","venue":null,"work_id":"018af743-ba93-4408-9048-474e7e071875","year":2021},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.312955Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:fc66678ea01f46a48a29a5b37e6bd1c9a7b99044f7e337f1c68e6ed4a2b065d8","observation_id":"77e125ff-bfc2-4210-925e-1a37349c460e","resolution":{"observed_at":"2026-08-12T15:15:44.581230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.563532Z","title":"Universally composable efficient multiparty computation from threshold homomorphic encryption,","venue":null,"work_id":"d57f4690-b1ff-4679-9dec-4e26b095476c","year":2003},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.317119Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:738667104ce9d544b69aef265e00873e66a5412fd4cd9e8a7eb37494bceff009","observation_id":"b46804b3-fb9a-46a4-99a2-066f4d37e3bc","resolution":{"observed_at":"2026-08-12T15:15:44.568075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.550196Z","title":"Fast large-scale honest-majority MPC for malicious adversaries,","venue":null,"work_id":"7e1db4f6-5b77-4d53-9a6d-2f52c2a82b73","year":2023},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.321449Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:b787eca669e985719758244df0449246f2eb8006e0c268733ecd2a452c9e050d","observation_id":"d468ba3b-d1d1-43e0-b4c4-4d9bfde6fab6","resolution":{"observed_at":"2026-08-12T15:15:44.554674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.537541Z","title":"SPD Z2k : Efficient MPC mod 2k for Dishonest Majority,","venue":null,"work_id":"a9b6315b-27a3-4335-98c1-894637bff03d","year":2018},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.325464Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:5d9a3ff4419e647bbf08bfd8b8b680230ec5b66379cfca9ebee1c55c5c8c19d4","observation_id":"cd873903-4e5c-4d12-acdf-35a26d9c08e4","resolution":{"observed_at":"2026-08-12T15:15:44.541635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.524190Z","title":"Cramer, I","venue":null,"work_id":"e3c2b306-c259-49bd-8789-6302e30f0c7b","year":2015},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.329687Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:47f4d0388798c3020aa9b03e883c964e9a8d1412bb7df2accb5f22ffaacc949c","observation_id":"7ffa13d3-f0f2-4d97-9898-f1af86dbd6e7","resolution":{"observed_at":"2026-08-12T15:15:44.528278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.511323Z","title":"Simbench – A Benchmark Dataset of Electric Power Systems to Compare Innovative Solutions Based on Power Flow Analysis,","venue":null,"work_id":"5eb5de0a-7e04-4781-8350-bfddb0a3047a","year":2020},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.333837Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:2978aac2b89c364ed918853005c2cfad8e6e8c801f89f587484f7c09ddfe93bf","observation_id":"563e44a0-179c-4433-b2a8-342bdd9fc768","resolution":{"observed_at":"2026-08-12T15:15:44.515292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.499254Z","title":"MP-SPDZ: A versatile framework for multi-party computa- tion,","venue":null,"work_id":"b9ef0233-6a8e-47e2-98ee-28d35cd5a628","year":2020},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.338242Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:864f8c0cc36b62edd165c638758ac0a76d51dc65b19f1ca62db88bae9dedd60d","observation_id":"1e16d544-9bea-4e6e-9ee2-746b8cccd18c","resolution":{"observed_at":"2026-08-12T15:15:44.502993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.485619Z","title":"Improved primitives for MPC over mixed arithmetic-binary circuits,","venue":null,"work_id":"3b7dfb43-2c07-44d8-8ae2-116b35dd65da","year":2020},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.342316Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:b4ba56340be8cc0e19baaa0e7f7ec3b9fa4cbbd77f3b7cf8ea57df879a76bcd6","observation_id":"23ab09e4-2bd2-4281-b31e-d0ca5b29eba9","resolution":{"observed_at":"2026-08-12T15:15:44.490369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.470028Z","title":"An introduction to secret-sharing-based secure mul- tiparty computation,","venue":null,"work_id":"8b20f9e4-6800-4d62-8c63-3b6a36293a63","year":2022},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.346344Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:de45ea8138ddd3711961503f7f78d270fc7600da87ce92722620d41afcf8e975","observation_id":"a8908860-b013-46df-9519-b49e20bb6195","resolution":{"observed_at":"2026-08-12T15:15:44.475317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.454365Z","title":"Secure quantized training for deep learning,","venue":null,"work_id":"5d523715-dba1-4c0b-bc90-a52ef6f074a1","year":2022},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.350834Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:800a83d729f0493f699862eb76a254121a8097e39eacdc9c89fab7e90e0ad562","observation_id":"21511a1d-7d7e-44f0-853f-7bbdf1b3ad71","resolution":{"observed_at":"2026-08-12T15:15:44.459237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.439351Z","title":"Flexibility service market for active congestion management of distribution networks using flexible energy resources of microgrids,","venue":null,"work_id":"ae48c9d3-b3c2-4d1a-96eb-169f4848e78b","year":2017},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.354579Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:fc294ba1506101f9d6c181088837bffa71528085fff18d6a5cc76434b7097f22","observation_id":"e168a267-1df8-4605-8f00-10d56b1129c2","resolution":{"observed_at":"2026-08-12T15:15:44.444047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.425687Z","title":"Distribution-level flexibility market for congestion management,","venue":null,"work_id":"9a4c3c13-c95c-4e37-9da5-007e6e79df26","year":2018},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.358352Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:007c4388f921497c839adcf0abd8a3dadc631df087f452a9d50b489c364c8666","observation_id":"6186cb69-f949-4321-9119-b67d5401fe62","resolution":{"observed_at":"2026-08-12T15:15:44.430116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.410792Z","title":"The holomorphic embedding load flow method,","venue":null,"work_id":"5d9b2e45-f165-4cc7-b694-560462d5e99a","year":2012},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.362047Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:bce8bc3c46dc2a278bc585359d5ced1f52b5d445097dab7c93ef9e2f04bb0dc8","observation_id":"30a676c4-d6bc-4869-8167-fed2ed33448c","resolution":{"observed_at":"2026-08-12T15:15:44.416137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T15:15:44.395228Z","title":null,"venue":null,"work_id":"ae73d487-f9a4-4b9e-ae26-00b1d56bcfd3","year":1997},"citing_paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:44.365553Z"},"links":{"citing_paper":"/paper/2411.14557"},"observation_digest":"sha256:2a08e4ba448af675b21933159ec64cf7abda8ef087ca76578c1d8a7e50f21420","observation_id":"08dc6b22-2089-475d-959b-402faf3582af","resolution":{"observed_at":"2026-08-12T15:15:44.400872Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.14557","last_updated":"2024-11-21T20:04:16Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-12T15:06:46.949039Z","submitted_at":"2024-11-21T20:04:16Z","title":"Privacy-Preserving Power Flow Analysis via Secure Multi-Party Computation"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":57},"total_outbound_references":60},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2411.14557."}