{"as_of":"2026-08-04T13:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a5c53db6ee078813b8c5f0179d79649aadec885720d061b07be5bcc3eb7c00a8","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T20:15:46.454806Z","state":"measured"},{"denominator":64,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":64,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T15:33:59.591966Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-05-11T11:01:03.130467Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"2604.04442","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.04442","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","venue":"cs.CR","work_id":"701a30f4-d534-4daf-98eb-ef333c8c3614","year":2026},"citing_paper":{"arxiv_id":"2604.10316","last_updated":"2026-04-11T18:47:54Z","snapshot_observed_at":"2026-07-06T22:58:56.307161Z","submitted_at":"2026-04-11T18:47:54Z","title":"Comparative Analysis of Large Language Models in Healthcare","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T15:33:59.591966Z"},"links":{"cited_paper":"/paper/2604.04442","citing_paper":"/paper/2604.10316"},"observation_digest":"sha256:a1b7be160c2f62217764a4020d36ff8a68c4f16aa874087aa94fa26cabba51b3","observation_id":"0b6620da-54f7-4bb9-8f83-c7c4dc91ebab","resolution":{"observed_at":"2026-05-11T10:16:07.967349Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"2604.04442","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.04442","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","venue":"cs.CR","work_id":"701a30f4-d534-4daf-98eb-ef333c8c3614","year":2026},"citing_paper":{"arxiv_id":"2605.01739","last_updated":"2026-05-03T06:37:43Z","snapshot_observed_at":"2026-07-06T23:14:57.459903Z","submitted_at":"2026-05-03T06:37:43Z","title":"AgenticVM: Agentic AI for Adaptive Software Vulnerability Management","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T15:14:04.838666Z"},"links":{"cited_paper":"/paper/2604.04442","citing_paper":"/paper/2605.01739"},"observation_digest":"sha256:43d825fa5f3f872c7c6a78529eedece0832a649472f1af39d70bd7af61dbf81d","observation_id":"9a71d5eb-517d-41be-8640-2cfaf2e5d5da","resolution":{"observed_at":"2026-05-11T11:01:03.133579Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2604.04442/citation-record","integrity":"/paper/2604.04442/integrity","json":"/paper/2604.04442/citation-record.json","paper":"/paper/2604.04442"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.10667","last_updated":"2023-09-22T01:48:28Z","snapshot_observed_at":"2026-07-06T16:34:08.044974Z","submitted_at":"2023-09-22T01:48:28Z","title":"Enhancing Network Resilience through Machine Learning-powered Graph Combinatorial Optimization: Applications in Cyber Defense and Information Diffusion","version":1},"cited_work":{"arxiv_id":"2310.10667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.10667","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enhancing network resilience through machine learning- powered graph combinatorial optimization: Applications in cyber de- fense and information diffusion","venue":null,"work_id":"e24f1d3b-b247-434b-98ff-9f395639ce3a","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"cited_paper":"/paper/2310.10667","citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:4a4872e6af3d513d9823d6f7ee564bcec82af505aec3e8d489b960bb78c04e71","observation_id":"15c7da19-73b2-4192-ad9a-b2fab378bfa5","resolution":{"observed_at":"2026-05-10T22:05:48.383325Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Overview of smartphone security: Attack and defense techniques","venue":null,"work_id":"252913b3-add6-4677-9d38-c9e2c03566c5","year":2018},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:973b8dbfbcd917020637c9d02880379c03ec9446cbc38e21fa228b4f84d2ab23","observation_id":"0b4d6c27-9286-40dc-8bfb-f44c88d35d2f","resolution":{"observed_at":"2026-05-16T01:57:06.470972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Smart hpa: A resource-efficient horizontal pod auto-scaler for microservice archi- tectures","venue":null,"work_id":"7c6200d7-2c6b-4f88-a46a-a57c1cfc8498","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:a84d259885d8f8ae445dfd37be8cbe76f83580661801f3af974fcb7ff567076a","observation_id":"613a9ea7-c81d-4cfa-9dd9-9be03f6c7eaa","resolution":{"observed_at":"2026-05-16T01:57:06.493178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Towards resource-efficient reactive and proactive auto-scaling for microservice architectures","venue":null,"work_id":"1c684dde-5226-4144-b0dc-1e66dde5d159","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:97f0fe787f2465ba678d23ac7a81aa8c60a54a066fbacb59453f99ccaf41a8b3","observation_id":"f9a98530-30a7-45a7-a474-0f7884c50488","resolution":{"observed_at":"2026-05-16T01:57:06.483689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.05693","last_updated":"2025-06-06T02:48:23Z","snapshot_observed_at":"2026-07-06T21:37:42.063760Z","submitted_at":"2025-06-06T02:48:23Z","title":"Resilient Auto-Scaling of Microservice Architectures with Efficient Resource Management","version":1},"cited_work":{"arxiv_id":"2506.05693","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.05693","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Resilient auto-scaling of microservice architectures with efficient resource management","venue":null,"work_id":"7f9fc1a4-40b0-4584-b087-a762ef5edcf3","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"cited_paper":"/paper/2506.05693","citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:c1148ed5c2ba3803858bc2061b750ecfd53ada8ab322efe8c9bfd625e61d2c3e","observation_id":"1fd94993-38e4-4904-bcea-f4a003d6d565","resolution":{"observed_at":"2026-05-10T22:05:48.387772Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Regimefolio: A regime aware ml system for sectoral portfolio optimization in dynamic markets","venue":null,"work_id":"8c54d23a-8e3d-4271-9674-5a7efbaddf3a","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:8613ea47f08a21396cb458e2b4b13683a6b0e7d097761a5a4de9751f3fc3bd6d","observation_id":"1edf1fa4-0077-4c81-b45b-09561e549142","resolution":{"observed_at":"2026-05-16T01:57:06.564749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.17393","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3s-trader: A multi-llm framework for adaptive stock scoring, strategy, and selection in portfolio optimization","venue":null,"work_id":"2df28591-15c7-4fb8-86ca-ba6ebec9b6cb","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:3d0e7d463383a076b866874daebe9b5dbbba5d51982dcd15d57873835d7747e9","observation_id":"914512fc-adad-46b9-a59f-fb16cbf3d049","resolution":{"observed_at":"2026-05-10T22:05:48.413816Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.06105","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Australian bushfire intelligence with ai-driven environmental analytics","venue":null,"work_id":"f21a1317-ec8f-4197-8ffa-fa49312b9a54","year":2026},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:75aad90bc896617a070c9dd63a4056731a4de54787bba4e0caf0776c825881e9","observation_id":"e38abf92-43be-4104-83ca-7bbbbe98cad8","resolution":{"observed_at":"2026-05-10T22:05:48.419217Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A survey of security challenges in cloud-based SCADA systems","venue":null,"work_id":"1fd956db-acbb-4aac-9f3d-dac29174cdbb","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:6986ad84f51e0c15fe54498180f1deb75c603aa7901c08d8906f5b5d242bdee7","observation_id":"646edf28-5aa4-4c1c-8749-36dc999ade97","resolution":{"observed_at":"2026-05-16T01:57:06.566760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A survey on security issues in smart grids","venue":null,"work_id":"a89ded5d-6de4-4822-953f-4fec12bc07fe","year":2016},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:5b3e19be1703999176d2eee8b6026760c627fcbedda340756a586b003e43dc9e","observation_id":"5fb5c669-f9ec-4820-9baa-145a09f45efb","resolution":{"observed_at":"2026-05-16T01:57:06.546103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A review on c3i systems’ security: Vulnerabilities, attacks, and countermeasures","venue":null,"work_id":"f8b4f8d5-558d-4604-ba80-238b5e391082","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:cb92fbfb78d049d0331be7eedd8e658fc609711ae58c36b16c627672069d3a36","observation_id":"b6a812df-1503-44d1-8819-9db5792f3532","resolution":{"observed_at":"2026-05-16T01:57:06.562650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Microservice vulnerability analysis: A literature review with empirical insights","venue":null,"work_id":"ceb89575-8b76-4f73-a5b1-d462e52cee4d","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:0d3a63cba0ef233c5b72c030949252b05f9f946478c2e33edba068bdc24d8767","observation_id":"1ee6d2e7-e7d6-456a-a746-b819f785395a","resolution":{"observed_at":"2026-05-16T01:57:06.537873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Living off the land and fileless attack techniques","venue":null,"work_id":"fe8be3a0-05ab-4a5a-8fec-1b8bb4d070a4","year":2017},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:fdcf99b6dc33405594895bb98e15ff90fec066a3b1f58c4fdb2176383db72007","observation_id":"ad94cce7-ed7a-4e5c-b655-63190c42da80","resolution":{"observed_at":"2026-05-16T01:57:06.491036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A survey on advanced persistent threats: Techniques, solutions, challenges, and research opportunities","venue":null,"work_id":"62e75c46-fd91-4cf6-a8af-8931b2836aed","year":2019},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:d3793ccf219839894e5b5cfdb32c4e97c54f13c00ce78da02d7b7e4a6eac7a7b","observation_id":"390d71f0-1535-4c1b-9282-c3793c4389eb","resolution":{"observed_at":"2026-05-16T01:57:06.570806Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Chatnvd: Advancing cybersecurity vulnerability assessment with large language models","venue":null,"work_id":"869f1078-e9d1-47c8-8b01-2984f36d84fb","year":2026},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:e0eb5333a3fac6ed012e4b5f0b02f6e6695359531f5a58d075bc739f817e0be7","observation_id":"9c6c410f-272b-44c5-ab13-65aef5a9d801","resolution":{"observed_at":"2026-05-16T01:57:06.479529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Towards deep learning enabled cybersecurity risk assessment for microservice archi- tectures","venue":null,"work_id":"c651457d-2d71-47d9-8f71-23a33c8dc749","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:f8c52d5f4b562dd50cfa3b675cd888a48efaaa9363ad2b437d9ec393f50f2f8c","observation_id":"1073791f-0ea1-4564-989b-1efd31776a40","resolution":{"observed_at":"2026-05-16T01:57:06.466881Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Deep reinforcement learning for cyber security","venue":null,"work_id":"e41c8d07-6059-4387-b680-89bd8f09695e","year":2021},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:8e014b4903a7a074e5508044980cf4ec1613654461c912513c72971173dd59ef","observation_id":"1a27597a-2aaa-4905-ab1d-bfc913263ab0","resolution":{"observed_at":"2026-05-16T01:57:06.540146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Enhancing security and energy efficiency of cyber-physical systems using deep reinforcement learning","venue":null,"work_id":"dc7ff56f-176e-49be-bc8d-6af3d5a30df2","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:926c7cd18c41f513767c82e530507f2e26b6ce7f89f5b04850d38860dd53e5f4","observation_id":"f1866209-c913-4261-9951-2f9668f3f8a3","resolution":{"observed_at":"2026-05-16T01:57:06.485669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Kott, Ed.,Autonomous Intelligent Cyber Defense Agent (AICA), ser","venue":null,"work_id":"ec53a135-6843-4398-b82a-d1f65be54a47","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:1f2e961f9f62ffc07b61f9dc19eb8e580cc13489d1095a4158e4dd15ffea26d6","observation_id":"26c9e7b4-be44-419c-ad66-1e5e209f8fad","resolution":{"observed_at":"2026-05-16T01:57:06.558758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Optimizing cyber defense in dynamic active directories through re- inforcement learning","venue":null,"work_id":"0957a1db-d360-4b21-ac4d-c519715ab830","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:6ed2de073a33d44b872519c1009ad64e08b93bcf6dd3394a7029f3fafc0afcb2","observation_id":"16196020-a484-42a1-8191-3ac44a62a099","resolution":{"observed_at":"2026-05-16T01:57:06.556871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.12786","last_updated":"2025-05-27T05:00:23Z","snapshot_observed_at":"2026-08-02T03:46:01.180109Z","submitted_at":"2025-05-19T07:19:06Z","title":"Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks","version":2},"cited_work":{"arxiv_id":"2505.12786","doi":"10.48550/arxiv.2505.12786","metadata_source":"arxiv_reference","pith_arxiv_id":"2505.12786","snapshot_observed_at":"2026-07-10T12:15:01.137692Z","title":"Forewarned is forearmed: A survey on large language model-based agents in autonomous cyberattacks","venue":null,"work_id":"b0210baf-d12a-4bbe-8a9d-1c27861a5ecd","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"cited_paper":"/paper/2505.12786","citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:a8cae871e1cc20cae6421904f49eb9742e044eef7e02da6625ce2d982548484f","observation_id":"c3507f96-5ef9-4e24-9e63-65fa86fbdbd0","resolution":{"observed_at":"2026-05-10T22:05:48.403898Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-07-10T07:46:57.054151Z","title":"A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions","venue":null,"work_id":"00bd49a0-e653-40e2-94b5-bb271da4dc35","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:4125ad91e454ac158b686598d5bb31720d1a4f9dd9fd888ed3ab620134e18929","observation_id":"0eead18c-a3cc-42f5-905c-07dd1e0ced5f","resolution":{"observed_at":"2026-05-16T01:57:06.473366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Peeking inside the black-box: A survey on explainable artificial intelligence (xai)","venue":null,"work_id":"3f01faf3-a2b8-4505-bab1-0ea8d8740ddd","year":2018},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:1cd82aba9c3bd1e2b2b70168d2ee0e9e3565a44cd7ef4e0bed6649548b951b23","observation_id":"90f09be0-59b3-4448-9a75-38b33349dbfa","resolution":{"observed_at":"2026-05-16T01:57:06.507301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Practical black-box attacks against machine learning","venue":null,"work_id":"fd6b50ee-8644-4b30-a256-5786b2646da4","year":2017},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:4aae54cdbbc367748bb33d6a342f3270f8844aac0b85955f245785465fd9c44d","observation_id":"2194b677-d2e4-4766-ba55-483f2dfab3a7","resolution":{"observed_at":"2026-05-16T01:57:06.572722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Adversarial examples: A survey of attacks and defenses in deep learning-enabled cybersecurity systems","venue":null,"work_id":"f71c2ff3-4b63-4b97-bcb7-a27b0c3e5113","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:457959a046cf377205c7c6c5cbb1fdd968c3e46009cc81c55322f227575bd156","observation_id":"df12c636-ab70-46d5-8c0e-28b80396259f","resolution":{"observed_at":"2026-05-16T01:57:06.475299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Anomaly de- tection in vehicular networks using causality-aware graph convolutional networks (CA-GCN)","venue":null,"work_id":"8b5acacf-a559-4fe2-8be3-1cacb660e93f","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:def10d9f516baf92e1354817b1476e85fe24573dac1ceb3c405f0fddccb4c9e1","observation_id":"241635a6-72f8-47ea-a71a-cd5083caea4b","resolution":{"observed_at":"2026-05-16T01:57:06.495450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-07-11T02:57:49.358703Z","title":"Pearl,Causality: Models, Reasoning, and Inference, 2nd ed","venue":null,"work_id":"a22bc442-28e1-48ef-b8c2-8ac8ddff02cb","year":2009},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:3521b23eadba9c4037e108bc793e602d1c625101c6340e125458daa6177ff52a","observation_id":"a5d0a265-6a03-4baf-aa0f-692dd76565b2","resolution":{"observed_at":"2026-05-16T01:57:06.497417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.06936","last_updated":"2024-07-09T15:13:20Z","snapshot_observed_at":"2026-07-06T18:43:43.463452Z","submitted_at":"2024-07-09T15:13:20Z","title":"Robust Partial Least Squares Using Low Rank and Sparse Decomposition","version":1},"cited_work":{"arxiv_id":"2407.06936","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.06936","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Robust partial least squares using low rank and sparse decomposition","venue":null,"work_id":"6b00fbc1-2966-4a5b-85ee-21129a9029d5","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"cited_paper":"/paper/2407.06936","citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:bce2bccaa1146b61b786085e5d0111fb62c86c97d2e6a6cfe219d3d5e023dccb","observation_id":"056d45ed-19df-4084-a009-46f2feb4363a","resolution":{"observed_at":"2026-05-10T22:05:48.400394Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A comprehensive review of explainable AI in cybersecurity: Decoding the black box","venue":null,"work_id":"b8362ea7-e018-4c7b-823d-b99e4769c632","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:d05ddee9bd099d55afc20429befbc73f98c7c70503b684877a5c1525edba9418","observation_id":"68a77f97-e089-4cc0-af1f-d3f01ea49bce","resolution":{"observed_at":"2026-05-16T01:57:06.499392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Scalar: Self-calibrating adaptive latent attention representation learning","venue":null,"work_id":"60329d3e-0325-48f0-97a0-23167e197b1a","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:67c0eb8a2f0238bde47bd1af82ed54506e1c8547ae1c5d4ef7b5ae96af5e1c76","observation_id":"93d44442-fc0d-4970-96f7-1eece01156fe","resolution":{"observed_at":"2026-05-16T01:57:06.568795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"AutoGen: Enabling next-gen LLM applications via multi-agent conversation","venue":null,"work_id":"366958dd-523f-4030-b661-e4166976cf5f","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:56d3ce7e3f1a712cde32cb6d1798fce0073b15fc0a1b46aabb09d339adcefb2d","observation_id":"086091a2-4ac6-40cb-8efa-36a1b5c051ad","resolution":{"observed_at":"2026-05-16T01:57:06.515507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Intelligent multi-agent collaboration model for smart home IoT security","venue":null,"work_id":"a440c9f1-9f59-4f34-b4db-d579ff88b486","year":2018},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:e5850fda072bbc20fb5dd3ef48a28632d2807979849b0e7b16718a6455765eac","observation_id":"f2320438-29fa-4251-a729-0ce52246601b","resolution":{"observed_at":"2026-05-16T01:57:06.481700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2505.11710","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Co-evolutionary defence of active directory attack graphs via gnn-approximated dynamic pro- gramming","venue":null,"work_id":"7ea74118-909f-4914-8a99-18b3e531ad57","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:b67844c542c8744e0f5b3bd05306edb7606a23edcc759bfd7445226fa3192b74","observation_id":"578784f9-46b2-4d91-a9d0-705aee9c21fc","resolution":{"observed_at":"2026-05-10T22:05:48.423564Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.11708","last_updated":"2026-05-15T01:13:07Z","snapshot_observed_at":"2026-08-02T19:19:40.667325Z","submitted_at":"2025-05-16T21:29:55Z","title":"Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents","version":3},"cited_work":{"arxiv_id":"2505.11708","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.11708","snapshot_observed_at":"2026-07-01T09:45:40.126209Z","title":"Unveiling the black box: A multi-layer framework for explaining reinforcement learning-based cyber agents","venue":"cs.CR","work_id":"9576f100-5466-4ac0-8fda-c0458716d7bf","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"cited_paper":"/paper/2505.11708","citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:ce84e8334d85aadb6c81a676c69f3f6f9abee3d69ba26e2c7a0e074b3012ad32","observation_id":"0d9b9357-d1e6-4f9c-8083-e1502ab51f26","resolution":{"observed_at":"2026-05-20T00:00:19.842991Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A survey on immersive cyber situational awareness systems","venue":null,"work_id":"5971cbb3-6bd2-400d-99be-419ef5f2dc7a","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:14063ce96688cd5ed2d577de4121fb627ea04a0b18416aeb447745a3fc2616be","observation_id":"acc1bcf4-74bb-422f-9dfd-75a6a17fce39","resolution":{"observed_at":"2026-05-16T01:57:06.574630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Alpcan and T","venue":null,"work_id":"1967b4dc-5806-4043-a327-27a96a429972","year":2010},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:8a0db6920024362a3ce3ea96f0c79bbd42f9059c0fc357eb2a65615a3a54c5df","observation_id":"57a5959b-de79-456d-b03a-0a4704c3348f","resolution":{"observed_at":"2026-05-16T01:57:06.505264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Security and privacy for green IoT-based agriculture: Review, blockchain solu- tions, and challenges","venue":null,"work_id":"19530fa6-68c8-4c67-86bf-2086674e12f9","year":2020},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:6067675a84e749965720b2d941a4196312a0bc4d3a9c4b60d801f3b62a254bb3","observation_id":"3695d2fe-0bcf-40d8-8dee-048b16938486","resolution":{"observed_at":"2026-05-16T01:57:06.525612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Network intrusion detection: An optimized deep learning approach using big data analytics","venue":null,"work_id":"bb0a82cc-7015-4418-8493-18a886d724ee","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:7e95ee9a8f62286ee25909c0078d16e5221212734110f6b25c5de7a031183981","observation_id":"b1f1c5ca-1562-4a48-9d2e-6540febf81b2","resolution":{"observed_at":"2026-05-16T01:57:06.550597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A bidirectional LSTM deep learning approach for intrusion detection","venue":null,"work_id":"d73cf943-fd4e-4021-89a2-42012835ccb7","year":2021},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:911738bcf9de9832e55f2fdf6c2ce18e9a99d737fd0224f76d0b466794cfc9b6","observation_id":"a059daf5-6d79-4ff7-811c-a211137e7f9b","resolution":{"observed_at":"2026-05-16T01:57:06.533794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Dugat-LSTM: Deep learning based network intrusion detection system using chaotic optimization strategy","venue":null,"work_id":"6a7e66cf-bc53-4ebe-856d-7a2135679deb","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:746ba94791636c55ded1c21e53386c8b5199f9f4366a34845a1bf0821d5f0451","observation_id":"08de8c59-8b93-456d-8d78-2ad10019d35e","resolution":{"observed_at":"2026-05-16T01:57:06.535872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Spirtes, C","venue":null,"work_id":"feaa8fe3-6144-477a-81f1-868d8dd50217","year":2000},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:3c0a2703ec97dede987a49d4b6f477e599c755f19f9583f86eec9b6af262d5d4","observation_id":"eeb2ce17-4484-4000-bfe9-426d0746225c","resolution":{"observed_at":"2026-05-16T01:57:06.521681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Hybrid deep learning model using SPCAGAN augmentation for insider threat analysis","venue":null,"work_id":"19e47a86-dfe0-4e25-a3b3-9778223a2670","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:0edd4a35df5a750be6446b3cfb2f43ef236d43c86a1f9520ab806bd075d5723e","observation_id":"f31d3872-1abd-420e-9630-932dc24823c9","resolution":{"observed_at":"2026-05-16T01:57:06.531757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05487","last_updated":"2025-01-08T18:18:37Z","snapshot_observed_at":"2026-08-04T02:22:53.895809Z","submitted_at":"2025-01-08T18:18:37Z","title":"The Future of AI: Exploring the Potential of Large Concept Models","version":1},"cited_work":{"arxiv_id":"2501.05487","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05487","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The future of ai: Exploring the potential of large concept models","venue":null,"work_id":"e683d17b-6b2f-4efc-a5ac-33f32849c03c","year":2025},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"cited_paper":"/paper/2501.05487","citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:cb1089e1b5091400b3aa8f3304a71e0f4be1ea0828f130ba0f9b046c0c37af4c","observation_id":"708d9536-5477-485b-bf55-668721ef94b7","resolution":{"observed_at":"2026-05-10T22:05:48.407449Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"What skills do cybersecurity professionals need?","venue":null,"work_id":"0799a374-b8cc-42bf-be45-9121484a7715","year":2026},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:6cc6578f88049521eb7150027a03b7d05b366311c47a233102820dff5d72dcfe","observation_id":"b86649de-9927-40f4-b3d1-7fcedba759ce","resolution":{"observed_at":"2026-05-16T01:57:06.523664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Intrusion detection using hybridized meta-heuristic techniques with weighted XGBoost classifier","venue":null,"work_id":"a55795ef-c04e-4faf-b043-5cba86fe48c8","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:cbb73510f89530a6e57c9a512651967faa5cefcc9bd68cd935f6b030e663a8ff","observation_id":"bdc95a9a-18cc-49e5-ad64-822d0a716f90","resolution":{"observed_at":"2026-05-16T01:57:06.511391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A new intrusion detection system based on moth-flame optimizer algorithm","venue":null,"work_id":"d9066775-eaf7-43de-9abf-a58feb64e930","year":2022},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:919da1cd8cce57d9ae567424eaac2091f611dd4ea193f0dfa71ed314b6ab857d","observation_id":"b30c78f4-01f4-45b6-9f7f-0f529695351e","resolution":{"observed_at":"2026-05-16T01:57:06.513389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-07-09T15:06:19.237161Z","title":"Goodfellow, Y","venue":null,"work_id":"c617fc6d-6d4d-47b0-8ab5-51ab3d0996e9","year":2016},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:3e9133a88c5be3adaf18d8c0ce3cbffbaf2f86b96d6658f7a5666e4ea42bac20","observation_id":"404bf761-d937-4b7d-840e-0355f9a5044d","resolution":{"observed_at":"2026-05-16T01:57:06.509344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.09641","last_updated":"2024-12-09T08:20:20Z","snapshot_observed_at":"2026-07-06T20:06:13.565435Z","submitted_at":"2024-12-09T08:20:20Z","title":"Machine Learning Driven Smishing Detection Framework for Mobile Security","version":1},"cited_work":{"arxiv_id":"2412.09641","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.09641","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Machine learning driven smishing detection framework for mobile security","venue":null,"work_id":"ca8c9caa-cfe4-4be0-a57b-b736fb9a2622","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"cited_paper":"/paper/2412.09641","citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:b08060865ac7c99188fe786dfcc93fef859292a5f661c5d90e58d9665fbce0bb","observation_id":"38cefffa-9d30-4202-8097-09ef0235cabb","resolution":{"observed_at":"2026-05-10T22:05:48.391135Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Review of artificial intel- ligence for enhancing intrusion detection in the internet of things","venue":null,"work_id":"5a390bb0-0796-48c8-9fa8-9b901da2290c","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:dd322b388628b986c84ae06ee440daf9614764b5453d91908bb6a19bcffd43c2","observation_id":"d6a3bf45-fb28-41b5-a79f-4b871087e32a","resolution":{"observed_at":"2026-05-16T01:57:06.519788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability","venue":null,"work_id":"2dd0f24c-53ec-45cc-9130-cf93dfb15445","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:212578e0744b3defce2a19563c6e957ae84c71761298360eeb8a9d4cf0958408","observation_id":"c29cc42d-c3c2-47b4-ae23-1cabad66538c","resolution":{"observed_at":"2026-05-16T01:57:06.544124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"An improved random forest based on the classification accuracy and correlation measurement of decision trees","venue":null,"work_id":"ff520328-3db6-415c-85c6-22ee758d9183","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:54248496809a057271383ffa45683fa0ecf9c7222da311ee60e19622ae4d78ea","observation_id":"26c84f0b-bd66-4785-ae43-831ba540150b","resolution":{"observed_at":"2026-05-16T01:57:06.527690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Malware detection issues, challenges, and future directions: A survey","venue":null,"work_id":"5367e9e1-d392-4d94-b920-5e77442e6bdb","year":2022},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:43b5041121697acef2d936c1909d2614c6fe9952561e85e29de7ae327e4b1387","observation_id":"82b72f0a-e6da-4e46-93de-981b051a013e","resolution":{"observed_at":"2026-05-16T01:57:06.548460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Verified models and reference implementations for the TLS 1.3 standard candidate","venue":null,"work_id":"405e8c7d-87e3-4549-a6e6-77a037bb92de","year":2017},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:0ea29f7c153aa1a5ed34f1ce4099a93ed332d2a6af062e61fa331560658061d0","observation_id":"ea551b6f-a575-4d4d-8edb-f0c2e55ea4bf","resolution":{"observed_at":"2026-05-16T01:57:06.501419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Explanation in artificial intelligence: Insights from the social sciences","venue":null,"work_id":"b77255a4-59f3-45cf-9fa1-287eb8b57396","year":2019},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:2c79839a057cc104669160fc85b44f30d9766d370e16177c86323c035f1bb725","observation_id":"0c3e1a33-1be8-49dc-9d99-ee23fcca7a85","resolution":{"observed_at":"2026-05-16T01:57:06.469043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-07-11T00:57:45.150172Z","title":"Counterfactual explanations and algorithmic recourses for machine learning: A review","venue":null,"work_id":"b96545ce-2456-41eb-a013-6da71ebba243","year":2024},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:542d596410e67b3c201a156df245ddcec1d13306b4e26a8a9884c5e4eae7c266","observation_id":"d5f48d20-c0f8-4234-b1d0-a9062afa8960","resolution":{"observed_at":"2026-05-16T01:57:06.529762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Human-in-the-loop machine learn- ing: A state of the art","venue":null,"work_id":"9fe4451e-f88e-4029-ba6e-9ce9d991e4d1","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:35a1de7aa15f6f37c22a28b205f17cc2f029075b95c1f0af41d4a07d637d908f","observation_id":"852c2cda-8af0-4fda-b1ff-0779e2b01d7e","resolution":{"observed_at":"2026-05-16T01:57:06.503382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Shoham and K","venue":null,"work_id":"c4e0f6bd-5304-4c65-a840-f57a92bb0a1d","year":2008},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:6c4bd7c6bb864e5f4d5d2e245d6aa3fd03ce024806582662bfbdab1080b2a4bd","observation_id":"e37737d4-cee8-4458-9a77-d2d3424ba2b8","resolution":{"observed_at":"2026-05-16T01:57:06.541997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A survey and critique of multiagent deep reinforcement learning","venue":null,"work_id":"b330fce5-cd31-40ec-a688-a3c0b3cbe16d","year":2019},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:e547b63976ad6e4cc4f8c957fe4ee1677e9ef3eec09edba444118757c9421e8a","observation_id":"eabcfb8d-c690-4cd9-ba9a-aea41c57f82e","resolution":{"observed_at":"2026-05-16T01:57:06.560712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"a68fcfde-5450-49a3-bdda-63a02fab8a71","year":2014},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:e4debf8887ea40d4cc19a3a7b5da99105cdbe240e108e269dd26da5630af0f41","observation_id":"61d36f1c-5fcd-40b8-9fdf-4d56c54fd05e","resolution":{"observed_at":"2026-05-16T01:57:06.477397Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-07-05T15:31:17.500066Z","title":null,"venue":null,"work_id":"396cf763-d356-4205-961a-9823b9c3b152","year":2018},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:e972f99495e18b33b62c178eceb86c5ae54f284aa900d7b9dcdb7e07b06fd296","observation_id":"39da995d-5bfb-4d65-bf69-834358fc1d82","resolution":{"observed_at":"2026-05-16T01:57:06.517781Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"34e3bfe8-1b25-4cae-8d0f-7ab192ab57cb","year":1999},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:0e27b403bc2574785de096c02699b05cb1d1e4c1d9d43875a6e09c63d4f0076b","observation_id":"a30716f2-b0ee-4e6f-a766-b75f27dbced0","resolution":{"observed_at":"2026-05-16T01:57:06.554902Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"CICIoT2023: A real-time dataset and benchmark for large- scale attacks in IoT environment","venue":null,"work_id":"37941dc8-92e0-4ba8-b554-d2d56d7028e2","year":2023},"citing_paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-10T20:15:46.454806Z"},"links":{"citing_paper":"/paper/2604.04442"},"observation_digest":"sha256:e8665f0b61b1fb3e44e7fe83cefc73a5764826809986857585fb8b551a6d1a33","observation_id":"07813db4-903e-4ece-90f0-cdc8075dff51","resolution":{"observed_at":"2026-05-16T01:57:06.553031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.04442","last_updated":"2026-04-06T05:40:43Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T22:53:24.585766Z","submitted_at":"2026-04-06T05:40:43Z","title":"Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":10,"verified_fuzzy":49},"total_outbound_references":62},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 2 inbound Pith citation observations for arXiv:2604.04442."}