{"as_of":"2026-08-14T23:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0cdb0330d44b7a9aba96909e0110345bea94345aa63f82a487d172ef574125fc","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-08T20:23:09.706524Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.05957/citation-record","integrity":"/paper/2607.05957/integrity","json":"/paper/2607.05957/citation-record.json","paper":"/paper/2607.05957"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.420248Z","title":"Multi-robot system for autonomous cooperative counter-uas missions: Design, integration, and field testing,","venue":null,"work_id":"675aaa40-a36b-4ef8-9956-db4c37733404","year":2022},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:cd11bbfe75a58791942970ea8e7b46dd2e55d0789e6252fea874e18f3b29c120","observation_id":"07c481c7-f993-4d3a-9568-f79b5ebfe5b7","resolution":{"observed_at":"2026-07-08T20:25:37.422112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.405328Z","title":"A review of counter-uas technologies for cooperative defensive teams of drones,","venue":null,"work_id":"2b704c7d-b46f-4eb5-ae6f-d24e91c134b8","year":2022},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:add66be59bcee939b4d7fa1369bc34ede6be2604d346aba88368a5aaf36c4040","observation_id":"588f8f93-d186-4f97-92fd-2b428c5a7e5f","resolution":{"observed_at":"2026-07-08T20:25:37.406923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.397370Z","title":"Hartley and A","venue":null,"work_id":"c7b2e177-bf83-4811-bff0-9b54a8880345","year":2003},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:8a389bd6dbf3c6e710f5ff327f011eef6568ca72a41ecfd6438cee73f242d846","observation_id":"b190241e-7288-4fe9-9c8f-1021ed21c8a8","resolution":{"observed_at":"2026-07-08T20:25:37.398667Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.418060Z","title":"Pampc: Perception- aware model predictive control for quadrotors,","venue":null,"work_id":"a3d51701-267c-4135-9982-09124fa32cdb","year":2018},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:2303c0d77388ed7224998d98d51725c6f969349acfdddaad237915e5c1153291","observation_id":"9d23d4d4-15da-49e4-ae7a-917733c8f3ef","resolution":{"observed_at":"2026-07-08T20:25:37.419859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.424759Z","title":"Multi-agent reinforcement learning based drone guidance for n-view triangulation,","venue":null,"work_id":"031f7fcc-0c71-4709-ad29-f7c8e0725f03","year":2024},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:f5973ec5fd1557be3266852a279f346e664ed44f1d8a2b222e24b92df3068903","observation_id":"46c4ef69-1ea4-4188-b3a3-a063b0761be1","resolution":{"observed_at":"2026-07-08T20:25:37.426397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.422365Z","title":"Rainbow delay compensation: A multi-agent reinforcement learning framework for mitigating observation delays,","venue":null,"work_id":"fd35e0ab-6e70-4f66-98b6-b227239ea226","year":2025},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:b76472955dd138b964b25bae61ae97e18e218bfed792cb93c6f1609ff25537a3","observation_id":"723004a2-bc9e-4fd3-a126-b18d7887b141","resolution":{"observed_at":"2026-07-08T20:25:37.424019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.429081Z","title":"Addressing signal delay in deep reinforcement learning,","venue":null,"work_id":"ce543443-d74c-4549-ad8a-daea0e60ec10","year":2024},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:09d4f5a56434bc3b0e8eb026f56315d67465c70a61426c44f544fd2d096f891b","observation_id":"138e4cb8-ef35-400a-9cd8-4713636b2303","resolution":{"observed_at":"2026-07-08T20:25:37.430746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.427330Z","title":"Asymmetric DQN for partially observable reinforcement learning,","venue":null,"work_id":"83c0eff9-ec1b-4f45-ab2d-c33e61b15d1a","year":2022},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:43d2b863bf84bc43e289aec4b5f9069aaa939ac61f7304c36fe5f86b8baf73fb","observation_id":"4bfda48d-8756-4bcb-82e4-9905a4f141db","resolution":{"observed_at":"2026-07-08T20:25:37.428798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.413211Z","title":"Swarm-based counter uav defense system,","venue":null,"work_id":"35f6ba7d-b6f9-4a6a-9e89-6c4d483a5a18","year":2021},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:f9b7df1b2034c1137ed2164af31ed429484eb83842c705114bfb7c82310af597","observation_id":"cdfc1afb-5b81-4afd-afd2-d7f573c46dc1","resolution":{"observed_at":"2026-07-08T20:25:37.414816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.399522Z","title":"On onboard lidar-based flying object detection,","venue":null,"work_id":"42a25656-1a06-456f-b1f6-72a7f3f1a8ba","year":2025},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:b48bbe3264277dfee4ced4a747db8a0ef9a76c9e8510530a9ff9947b5951a3f8","observation_id":"48861734-23a1-4a24-af4c-53b86b534464","resolution":{"observed_at":"2026-07-08T20:25:37.401261Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.18689","last_updated":"2025-07-07T16:28:47Z","snapshot_observed_at":"2026-08-14T05:14:52.537828Z","submitted_at":"2025-06-23T14:28:30Z","title":"NOVA: Navigation via Object-Centric Visual Autonomy for High-Speed Target Tracking in Unstructured GPS-Denied Environments","version":2},"cited_work":{"arxiv_id":"2506.18689","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.18689","snapshot_observed_at":"2026-07-08T20:25:37.254305Z","title":"NOVA: Navigation via Object-Centric Visual Autonomy for High-Speed Target Tracking in Unstructured GPS-Denied Environments","venue":"cs.RO","work_id":"2d0bf9c0-773b-41d2-adfb-6ffbf54d28d1","year":2025},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"cited_paper":"/paper/2506.18689","citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:3735a23a611756a6914b2fcf6b9861af6c69c6b00d825fd44c424f2eeb9794db","observation_id":"aee93390-ed57-4bd1-98a0-5a9304d4e78a","resolution":{"observed_at":"2026-07-08T20:25:37.255893Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.403579Z","title":"Error modeling in stereo navigation,","venue":null,"work_id":"52272099-6673-4433-a6b0-9c5203e04754","year":1987},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:5ef813238ae04c5aa7e04da084f01305b4c2a457e9d318ead27acc442ddd71ab","observation_id":"73bb782e-60c2-4fd3-b942-8bd06a3c4373","resolution":{"observed_at":"2026-07-08T20:25:37.405067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.401493Z","title":"Propagation of uncertainty through stereo triangulation,","venue":null,"work_id":"4a5792e2-a898-46f5-b9c6-b652290d4657","year":2010},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:c31f929533585763e75a7e381fe398298287b1f5cc80756294f49d178043a124","observation_id":"700d710a-68ff-4484-877a-36e5926a8145","resolution":{"observed_at":"2026-07-08T20:25:37.402953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.01258","last_updated":"2020-08-05T14:52:00Z","snapshot_observed_at":"2026-08-07T14:29:02.002409Z","submitted_at":"2020-08-04T00:47:42Z","title":"Robust Uncertainty-Aware Multiview Triangulation","version":2},"cited_work":{"arxiv_id":"2008.01258","doi":null,"metadata_source":"pith","pith_arxiv_id":"2008.01258","snapshot_observed_at":"2026-07-08T20:25:37.251592Z","title":"Robust Uncertainty-Aware Multiview Triangulation","venue":"cs.CV","work_id":"8e3f9964-0e18-4649-b126-56ffcd547ac0","year":2020},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"cited_paper":"/paper/2008.01258","citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:327f96100c937830ef9c61a1908fc01d57d667b828790eec27aaef47a04abe81","observation_id":"ebb927cc-9a3c-41a7-b87c-7a2217253e9a","resolution":{"observed_at":"2026-07-08T20:25:37.252994Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.415572Z","title":"Deep reinforcement learning for aoi minimization in uav-aided data collection for wsn and iot applications: A survey,","venue":null,"work_id":"29db43c5-39a4-43a9-ba71-6f5f0eca381d","year":2024},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:c1aa2d68652ed577b6de64e935047aac56b68215012fb95f98cad7b1e44389b7","observation_id":"28b63e3d-0596-4d24-8538-eba65311e0ad","resolution":{"observed_at":"2026-07-08T20:25:37.417298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.409319Z","title":"Real-time status: How often should one update?","venue":null,"work_id":"99aa1591-700a-4740-8e44-a2afd0c7ae15","year":2012},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:dab1ac3fa3bcc9372060566f859ef0e142ab5c009be6ac3dfecdb25c42cb41b7","observation_id":"2daa5ae6-c74b-4f50-ad2c-5980eaf86829","resolution":{"observed_at":"2026-07-08T20:25:37.410782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.411072Z","title":"Age of correlated information-optimal dynamic policy scheduling for sus- tainable green iot devices: A multi-agent deep reinforcement learning approach,","venue":null,"work_id":"b0496f9c-76a5-456a-a902-fbfdc4a2cef0","year":2024},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:649b11abd72fcc911728d0eea0d3faf32d0c39199ea7a171caff78417cdf0fa7","observation_id":"43365685-8c33-4558-9a8c-d40a159bbe4b","resolution":{"observed_at":"2026-07-08T20:25:37.412749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:25:37.407294Z","title":"The surprising effectiveness of ppo in cooperative, multi- agent games,","venue":null,"work_id":"7cc44192-7e0a-4425-8f63-04d1319e04a5","year":2022},"citing_paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-08T20:23:09.706524Z"},"links":{"citing_paper":"/paper/2607.05957"},"observation_digest":"sha256:a5f61f8ca5d5d419f5e7e8d273a10c6aa199555f7483d97337a4e082fd4f39fc","observation_id":"a9350c02-e1c6-4331-91d3-7cce86edb94c","resolution":{"observed_at":"2026-07-08T20:25:37.408749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.05957","last_updated":"2026-07-07T07:58:13Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-09T05:04:24.303698Z","submitted_at":"2026-07-07T07:58:13Z","title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":2,"verified_fuzzy":16},"total_outbound_references":18},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.05957."}