{"as_of":"2026-08-09T10:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:28d93dc4abd59d5d6de78c47f1df0a9c5459bf6d917c93ff6d3ef62d16389bb9","coverage":[{"denominator":34,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":34,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T00:18:42.525591Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2608.01375/citation-record","integrity":"/paper/2608.01375/integrity","json":"/paper/2608.01375/citation-record.json","paper":"/paper/2608.01375"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T00:18:39.084246Z","title":"Smart grid cyber-physical attack and defense: A review,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.084246Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:7ff333ef8f675b03574b1397e2c991fe781691b02d778ab0c724fa748f5a94ff","observation_id":"6a763288-e677-4c90-b61e-7fdf4395a961","resolution":{"observed_at":"2026-08-06T00:18:39.084246Z","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":"2026-08-06T00:18:49.462792Z","title":"Analysis of the cyber attack on the Ukrainian power grid,","venue":null,"work_id":"bf8d03aa-1131-4847-97f2-dab7dcfa4743","year":2016},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.146961Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:f691505323340b6b13bd650de28c0220b5b4cc5d863e92edbe94e43c36d30dd8","observation_id":"66deb10a-2b50-4f6a-8bd3-4f1b454fe7d5","resolution":{"observed_at":"2026-08-06T00:18:49.641711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:49.209539Z","title":"Sandworm disrupts power in Ukraine using a novel attack against operational technology,","venue":null,"work_id":"67f10f16-44e7-4880-a424-bd4e0034e057","year":2023},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.256874Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:b4bc113eff7b5959b1c2bc46a645b625b3ce28f155f2d8f059bba2ea76ea205f","observation_id":"4aaafde4-6bc0-4cee-a24d-c3b0938558c7","resolution":{"observed_at":"2026-08-06T00:18:49.298537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:48.989609Z","title":"Missforest—non-parametric missing value imputation for mixed-type data,","venue":null,"work_id":"f65ec67c-475f-472b-8405-693a8606819b","year":2012},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.334041Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:5062145a7fc5a54119572216ebdc32b7a90b653c019cbbdd4aae17a73928fcac","observation_id":"56455ceb-0cb4-4534-87d4-068f93440fec","resolution":{"observed_at":"2026-08-06T00:18:49.108525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:48.686541Z","title":"GAIN: Missing data imputation using generative adversarial nets,","venue":null,"work_id":"dc1b5ea0-f89c-44a2-b618-8c50daf1faae","year":2018},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.427758Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:ae65c3fe9d67f3f68cd38310e095a0d4d8ca4c07e32f8b71b32cd023580acc51","observation_id":"e3ff6ed1-adab-48c8-9cfc-506e52297502","resolution":{"observed_at":"2026-08-06T00:18:48.829559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:39.539852Z","title":"Adding conditional control to text-to-image diffusion models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.539852Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:0904fd29f32e2c7d84b8cb1b49846cd37eb154ff720421a5b6fe52f1348e41d4","observation_id":"c7c5b904-1247-4cf0-8f9b-b37db2b58cc1","resolution":{"observed_at":"2026-08-06T00:18:39.539852Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05301","last_updated":"2021-03-21T11:42:08Z","snapshot_observed_at":"2026-08-09T03:23:21.309214Z","submitted_at":"2020-06-09T14:40:00Z","title":"VAEs in the Presence of Missing Data","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.05301","snapshot_observed_at":"2026-08-06T00:18:39.639799Z","title":"V AEs in the presence of missing data,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.639799Z"},"links":{"cited_paper":"/paper/2006.05301","citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:69b4428c1e690e5f438da34b4e79bfa5b3a7362e9e476ccdcf6e74beb3188d9c","observation_id":"1b230913-08a8-46d6-ac69-14b1aa660bb6","resolution":{"observed_at":"2026-08-06T00:18:39.639799Z","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":"2026-08-06T00:18:48.471204Z","title":"Pseudo-measurement enhancement in power distribution systems,","venue":null,"work_id":"25c0acfa-0f21-41ca-a3a8-b7e8308c3a36","year":2025},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.726939Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:c626c0d334a785ab17f2efcec463d2fb77dea0182765a89c2c916d47eba6a8bf","observation_id":"17a83ae7-f0f6-4cd7-939e-a4500e2bebea","resolution":{"observed_at":"2026-08-06T00:18:48.569136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:48.260872Z","title":"A learning-to-infer method for real- time power grid multi-line outage identification,","venue":null,"work_id":"b5d11630-799f-4306-94d6-3f22bcb19124","year":2020},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.802329Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:c396f668c63abf353185eda0fa53884e1bae52664f18c6085d01261266f2f118","observation_id":"7cfaaf83-799f-440c-8271-13a9c97df0b4","resolution":{"observed_at":"2026-08-06T00:18:48.378849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:47.962448Z","title":"Line outage detection using phasor angle measurements,","venue":null,"work_id":"eef62007-2afb-451f-bb5a-65b9cbbf9fc4","year":2008},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:39.951365Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:248a884e1f8f54b88b967bb49ab018255b0a92190006b2730f010cd10105d541","observation_id":"c2518aa1-17a6-4161-a7fb-69f56e58c124","resolution":{"observed_at":"2026-08-06T00:18:48.083243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:47.711605Z","title":"Dynamic detection of transmission line outages using hidden markov models,","venue":null,"work_id":"352edaac-2f32-4823-83ea-a3e9e3376419","year":2026},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.053141Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:77a1ea15567ba33d5b3c01434651382f673b635a5decc97ab95174af34cebb80","observation_id":"e9abcba2-1560-49a6-b4a7-d25a807f91b6","resolution":{"observed_at":"2026-08-06T00:18:47.839045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:47.434204Z","title":"Compressive system identification for multiple line outage detection in smart grids,","venue":null,"work_id":"cbde3d5d-1baa-46df-8fdd-08772efba28a","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.141006Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:6c01da4e41955ea9a9510e275ac2f1d88fe378e6a2cf91a2c656f47cca1665fe","observation_id":"89f9bfe7-484f-4068-92ef-9fbca98398ab","resolution":{"observed_at":"2026-08-06T00:18:47.537190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:47.193458Z","title":"Learning from future: Prediction-based data augmentation to enhance power grids fault detection,","venue":null,"work_id":"e54131e2-f194-4053-b740-0ffbf468b8af","year":2023},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.220919Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:57952b411063da3d7fe17b0b40fba8e799bfd8159791d66d7e8ed8b48d054c76","observation_id":"e95322dc-fa28-4413-9f0c-8e004c1d7783","resolution":{"observed_at":"2026-08-06T00:18:47.319030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:46.926304Z","title":"Hybrid CNN-LSTM approaches for identification of type and locations of transmission line faults,","venue":null,"work_id":"2f1e611e-55bc-44e3-a0da-355a531040a1","year":2022},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.345541Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:7117db9d4004fdc432e250b6e0448452abfee1d40eaf21d49219864919ca3d4a","observation_id":"38a1c390-06b5-42f1-aeb7-730d91c8cb17","resolution":{"observed_at":"2026-08-06T00:18:47.033542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:46.654016Z","title":"Design of a cost-effective deep convolutional neural network–based scheme for diagnosing faults in smart grids,","venue":null,"work_id":"00814773-fa6d-4390-8c4d-5dc8a317fa4e","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.477259Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:5151f661e6965dbe692c4abe50bbd598bedf66831d59c0bf6f3417e9756ed9db","observation_id":"fd7aba91-8dfb-45a8-b274-2ad6b4195636","resolution":{"observed_at":"2026-08-06T00:18:46.814634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:46.455388Z","title":"Distribution grid fault classifica- tion and localization using convolutional neural networks,","venue":null,"work_id":"8906147b-30d9-4d97-8571-196e8d6e49f8","year":2024},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.600709Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:d9ad00007688c40ff78c2161754e84a89d664dabe7ea4be9529f4efbd822af96","observation_id":"1d0b2bfa-a059-4014-b586-00cbcdcb4117","resolution":{"observed_at":"2026-08-06T00:18:46.528065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.08018","last_updated":"2022-01-20T06:36:35Z","snapshot_observed_at":"2026-08-09T09:05:59.023940Z","submitted_at":"2022-01-20T06:36:35Z","title":"Transfer Learning for Fault Diagnosis of Transmission Lines","version":1},"cited_work":{"arxiv_id":"2201.08018","doi":null,"metadata_source":"pith","pith_arxiv_id":"2201.08018","snapshot_observed_at":"2026-08-06T00:18:42.930511Z","title":"Transfer Learning for Fault Diagnosis of Transmission Lines","venue":"cs.LG","work_id":"cbb3468b-c33b-4ea7-aa3e-ed621d07a41d","year":2022},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.702973Z"},"links":{"cited_paper":"/paper/2201.08018","citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:bda62e09a75fdbf4dd6257fc32adfa6e99e3d62c94b28661e449484e08f0c3fa","observation_id":"d50554f3-3573-4a9b-867c-7c837f98ea52","resolution":{"observed_at":"2026-08-06T00:18:42.989177Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:46.229711Z","title":"Prediction-based data augmentation for smart grid line outage detection,","venue":null,"work_id":"39828f44-7b33-4d3c-9425-3f9a37a5a62d","year":2024},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.823013Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:0170827837bc14c54f485cc88349edee708c9cbee842525491595a93bff8fb53","observation_id":"ea975b01-528c-4dcc-8f6d-47c94a2a4294","resolution":{"observed_at":"2026-08-06T00:18:46.351511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:45.956248Z","title":"Detection of power grid disturbances and cyber-attacks based on machine learning,","venue":null,"work_id":"79897747-ce07-4f50-bbcd-b2db77c1a5f7","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:40.932523Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:abd567b5421fc2b937a293936a30de287c8f69d556931d2694b457c2411cfff9","observation_id":"2a03f5f3-e278-4f9f-8cbd-621154b7e9af","resolution":{"observed_at":"2026-08-06T00:18:46.050114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:45.675434Z","title":"A tri-level optimization model to mitigate coordinated attacks on electric power systems in a cyber-physical environment,","venue":null,"work_id":"249b58f2-7991-407b-a911-af5eb82898e7","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.036863Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:5ef661454003897a558da53239f94bfe51a38988016fb01654a19e5e6cf2984d","observation_id":"40e3147c-bae9-443f-9d35-bb531999403c","resolution":{"observed_at":"2026-08-06T00:18:45.828473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:45.446346Z","title":"Line failure detection after a cyber-physical attack on the grid using bayesian regression,","venue":null,"work_id":"180975b1-4e4c-45b2-9946-df3cb90eccd9","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.134027Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:f7051d5ea3c7a2c45bf373d2440790e20423f08d5923ca69aff76fcab6a6ed1c","observation_id":"94e7d136-3783-4db3-84c3-39049358535d","resolution":{"observed_at":"2026-08-06T00:18:45.530921Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:45.160124Z","title":"Line failure detection from pmu data after a joint cyber-physical attack,","venue":null,"work_id":"d3e86915-3c73-4820-80f1-02b67e4507ba","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.229524Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:ccb47da55a83bafc02f49460e528db57738d1284f4ee09c681c07bcd1d828b12","observation_id":"88b3a822-f27f-4908-b507-eeefc913742e","resolution":{"observed_at":"2026-08-06T00:18:45.315848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:44.989299Z","title":"React to cyber attacks on power grids,","venue":null,"work_id":"7d07d71c-dba5-40fe-8a48-9bcc27ff068f","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.307605Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:2306ef2df23062587c5f724b5e749cfdf61dac3a4b13967d89b181fd6c59f877","observation_id":"f200d262-ce9c-4b6b-8642-e6c2cd2d9818","resolution":{"observed_at":"2026-08-06T00:18:45.031029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2503.05797","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T00:18:42.733069Z","title":"Fault localization and state estimation of power grid under parallel cyber-physical attacks,","venue":null,"work_id":"a80fa7fa-febc-4749-95fb-1f3697c97bb8","year":2025},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.410349Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:2f367acc2ca2bcc354b467c59637c51b45bec02f9e5148e3673e2cea50cb44a5","observation_id":"79c99cc1-7127-4f16-ac12-288553a4385d","resolution":{"observed_at":"2026-08-06T00:18:42.811789Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:44.708301Z","title":"Prompt-to-prompt image editing with cross attention control,","venue":null,"work_id":"87e116a3-9c1e-42fb-a511-8707ec042455","year":2023},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.522550Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:0b83f11411e39b745a5cf1783d861a76507004f584c89ffbf620c0126d5e691c","observation_id":"191541cd-ac80-4301-8981-3ccd6357a43e","resolution":{"observed_at":"2026-08-06T00:18:44.883850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:44.458538Z","title":"Improving hurricane power outage prediction models through the inclusion of local environmental factors,","venue":null,"work_id":"be8386b1-ec2b-41cc-a7f3-0a313d885fb2","year":2018},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.628377Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:0f204d5d5cbce119fe44c52775c688dd41bfb6dcafa00fab5d36ad1b0f073299","observation_id":"776d5a14-2816-4cc2-a540-741959fb2d69","resolution":{"observed_at":"2026-08-06T00:18:44.571015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:44.140059Z","title":"Conditioning neural networks: A case study of electricity load forecasting,","venue":null,"work_id":"86ac7606-ce05-4672-96d0-9e720d9600a9","year":2018},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.735504Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:d8b64501e619de7cbe752f134c9b0cd93db938ba70bcf9c9067769ab3ad21f6d","observation_id":"109f0cb0-4c4d-4263-b44a-e3bd54bee8d4","resolution":{"observed_at":"2026-08-06T00:18:44.307012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:43.913987Z","title":"Safety- critical cyber-physical attacks: Analysis, detection, and mitigation,","venue":null,"work_id":"d32c6555-3a38-41fd-9455-859ffd194979","year":2016},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.849132Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:358498c7ecacd8d5b6b7368a2cc13102065db04d30212bdc87950a2754d3e7cb","observation_id":"942f46cf-862b-4f2d-a788-b73f9922657f","resolution":{"observed_at":"2026-08-06T00:18:44.021961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:43.655332Z","title":"False data injection attacks against state estimation in electric power grids,","venue":null,"work_id":"ce8590bf-9442-4d2d-ae0e-69ab419e9142","year":2011},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:41.962331Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:536099d4b916badd711c9ac6eafcb9e6343d2f6afd10dbb7e6b78e3e1e511b20","observation_id":"25d4c223-3169-41f7-9d1c-f88ef7322aa8","resolution":{"observed_at":"2026-08-06T00:18:43.779977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:43.543582Z","title":"Runtime semantic security analysis to detect and mitigate control- related attacks in power grids,","venue":null,"work_id":"88f47627-e44e-4167-bad9-5726a05d6bf4","year":2018},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:42.115797Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:e343a4d4bed0ec0857814fa481272366c8a180b6e669f1e74cb4cacaa04693ab","observation_id":"99367c6f-5aa1-4290-b5a4-1f448aca47cf","resolution":{"observed_at":"2026-08-06T00:18:43.604330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:43.406216Z","title":"Malicious data attacks on the smart grid,","venue":null,"work_id":"915f93f1-2f03-430c-8773-7840b468a63e","year":2011},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:42.191718Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:b4e0b2a0c4d48ebe619de0691c47e52828ab6ce9f569143b082758494a923419","observation_id":"8dc04486-19ae-4d1d-98a7-76a75f61bd6f","resolution":{"observed_at":"2026-08-06T00:18:43.469654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:43.274392Z","title":"Detecting target-area link-flooding ddos attacks using traffic analysis and supervised learning,","venue":null,"work_id":"3d0b4bd1-33b5-4cc8-8255-3087b8d2ad52","year":2019},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:42.343804Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:d8b5c0f36ec1943c6c9d02a6ad9b83f2d9891df9bf834dd598e761ee177158bb","observation_id":"ac945e8c-6dc7-46fc-b850-11fcfdb1a945","resolution":{"observed_at":"2026-08-06T00:18:43.345144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:43.136384Z","title":"MAT- POWER: Steady-state operations, planning, and analysis tools for power systems research and education,","venue":null,"work_id":"28ba6e8d-f1f7-4e1d-a67a-69673cdb399f","year":2011},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:42.420090Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:381bccaf29e1b35a6ea7c4df45f57082c1c57dfaec685cf64da3ad86bb5adb4b","observation_id":"8ad6e0c3-ddab-41b7-ba8a-8b8e16299683","resolution":{"observed_at":"2026-08-06T00:18:43.174814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T00:18:42.525591Z","title":"Grid structural characteristics as validation criteria for synthetic networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T00:18:42.525591Z"},"links":{"citing_paper":"/paper/2608.01375"},"observation_digest":"sha256:7ed899dce8b79aedc13174c709ac467089fec3bfab9d0b83b198e60994e39c2e","observation_id":"dfa4f121-d497-4d31-ac84-b1bad27151b7","resolution":{"observed_at":"2026-08-06T00:18:42.525591Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.01375","last_updated":"2026-08-02T16:54:28Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-09T03:23:43.799683Z","submitted_at":"2026-08-02T16:54:28Z","title":"AdaptoNet: Modular Foundation-Adaptive Neural Networks for Cyber-Physical Attack Detection in Power Grids"},"reference_resolution":{"displayed":34,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":2,"verified_fuzzy":28},"total_outbound_references":34},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2608.01375."}