{"as_of":"2026-08-08T22:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f4ebf0b24f0847ecf915291d3745fd809d06fcc6372cfa7cdf6a6fbf60b66bf5","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":"2026-08-07T11:32:08.495203Z","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":"2026-08-08T06:32:00.761636+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/2506.03205/citation-record","integrity":"/paper/2506.03205/integrity","json":"/paper/2506.03205/citation-record.json","paper":"/paper/2506.03205"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:11.094775Z","title":"C., & Bear, M","venue":null,"work_id":"2f4c349e-5b0b-4d50-ad4a-2e5293c7fcfc","year":1996},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:06.796269Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:45fa7114cd3ac7dc785ee7163e157f825fd5ab88056b67404d72d314de460fdc","observation_id":"f4b4a3c5-92fb-4c67-ae22-defef961f856","resolution":{"observed_at":"2026-08-07T11:32:11.173070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:10.912859Z","title":null,"venue":null,"work_id":"98d7f320-99ac-4bb6-a11a-bd9aa9776411","year":2019},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:06.924597Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:bd68f0603702e302ec8a83c727f16d67f12471d6554a9d8c1848c7fb8dc33607","observation_id":"f8502694-1a03-46ce-8085-f19df134f7f7","resolution":{"observed_at":"2026-08-07T11:32:11.004086Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:10.756240Z","title":"Y.-C., et al","venue":null,"work_id":"d05fbe77-a681-4702-9e9a-7711055830b4","year":2020},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.087596Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:5cafa3c2c7de97ff35e109f3990d94ce81c599ae9345253f520053ee918e57a6","observation_id":"e6925bba-672c-47ee-803d-49924b8a7f16","resolution":{"observed_at":"2026-08-07T11:32:10.833933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:10.602159Z","title":null,"venue":null,"work_id":"535988c9-1ea0-4c19-8be6-266fa7deead9","year":2008},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.200630Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:0317de88d74433c83a2569cbc0d03c34640c680f9f97d122faf65795306d8965","observation_id":"9f1d184d-004c-4d76-9f2b-eb435efb106b","resolution":{"observed_at":"2026-08-07T11:32:10.690320Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:10.416692Z","title":null,"venue":null,"work_id":"ca8db4e6-8e3f-4e44-bfe6-9d34b5e89a46","year":2018},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.313833Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:23f2e92440e3432f51fa94908f6334bde2d1bad878f173e70cf0398a64d85b37","observation_id":"d62d58f2-81bd-407f-8061-4c01c4d3628e","resolution":{"observed_at":"2026-08-07T11:32:10.465043Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:10.275106Z","title":null,"venue":null,"work_id":"80ad7a38-a64a-4a4b-8929-a8c5c470b1a4","year":2018},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.406718Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:b34fba8741e02186240684fc65780c10cfa95782b4877503295fd098fd9d763b","observation_id":"c41831ba-6289-4d36-8d0c-90e1af25eb18","resolution":{"observed_at":"2026-08-07T11:32:10.345559Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:10.111071Z","title":null,"venue":null,"work_id":"28b1b549-7797-4371-b9a2-455e2be18e05","year":1987},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.531126Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:df71fb2a8df2d8caef6fefde0980503e8ba8fe566321b097b89eafb7a8947615","observation_id":"c12df2f2-c8c2-48e3-9a1c-c098ea309b9d","resolution":{"observed_at":"2026-08-07T11:32:10.199917Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:09.988830Z","title":null,"venue":null,"work_id":"e2c04787-d784-436a-829c-d51af8d30400","year":2018},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.603841Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:abfdfd9f6b126f485a52dd3b2d2bb516b7d204fc15f2404e55ac64645227b6cd","observation_id":"78930aa0-f7d9-4b0a-b0a9-00cd5100abd6","resolution":{"observed_at":"2026-08-07T11:32:10.039019Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:09.768067Z","title":null,"venue":null,"work_id":"1b509193-bd5d-4557-bb92-e7bb325154c3","year":2017},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.707145Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:eaaf9585678d0d1cbd8ccdeda42f0bcbf5ee7e97e31663946d0c16e49f87e021","observation_id":"00747199-9d62-44cd-8e0d-25a210d131cc","resolution":{"observed_at":"2026-08-07T11:32:09.887790Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:07.802089Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.802089Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:6dabbaa0ccf5c99266f2bdd59341b15f1abf46688b80090482c8d3e8d442f138","observation_id":"a5c2f0b5-3271-4314-b388-675cc56c4bd0","resolution":{"observed_at":"2026-08-07T11:32:07.802089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:07.886641Z","title":"A., & Chuang, I","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.886641Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:24111320562fbd4890c4340b0f005d41dac7202d6d23b2299a50b8fd1a55ecdf","observation_id":"f0a2b05c-5866-480f-aff2-9a8a16525e43","resolution":{"observed_at":"2026-08-07T11:32:07.886641Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:09.538525Z","title":null,"venue":null,"work_id":"967ddf1c-580c-4e5c-9b1f-9040f9d8d5d2","year":2017},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:07.962329Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:b96a622c57d18c7fcd7d610e1f0acfac046d47feaae7a1beb91270cb9f0515ee","observation_id":"43ffaf55-bedb-4ff1-93d4-d645bdab4d29","resolution":{"observed_at":"2026-08-07T11:32:09.629961Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:09.319179Z","title":null,"venue":null,"work_id":"9bde1822-3fc7-4faa-be8f-3a20afabaebb","year":2023},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:08.057437Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:9098d106f3710217b27f200c783f07aaf85a015b6b88ac8a7ff58a8db390f156","observation_id":"4b962cc3-8428-4607-a8d8-6bee9655a94c","resolution":{"observed_at":"2026-08-07T11:32:09.418863Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-07T11:32:08.134988Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:08.134988Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:55a64ddf6e84eb7138bce292ed4a9faf01878131131ff16647236c35fbf4266f","observation_id":"033fda0f-513e-4e1a-8b39-389c6dd689a4","resolution":{"observed_at":"2026-08-07T11:32:08.134988Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.06300","last_updated":"2025-05-07T23:48:41Z","snapshot_observed_at":"2026-08-07T15:48:58.700212Z","submitted_at":"2025-05-07T23:48:41Z","title":"ARDNS-FN-Quantum: A Quantum-Enhanced Reinforcement Learning Framework with Cognitive-Inspired Adaptive Exploration for Dynamic Environments","version":1},"cited_work":{"arxiv_id":"2505.06300","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.06300","snapshot_observed_at":"2026-08-07T11:32:08.613091Z","title":"ARDNS-FN-Quantum: A Quantum-Enhanced Reinforcement Learning Framework with Cognitive-Inspired Adaptive Exploration for Dynamic Environments","venue":"cs.LG","work_id":"2e401087-c4be-4d81-a9cb-e08757230bce","year":2025},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:08.213612Z"},"links":{"cited_paper":"/paper/2505.06300","citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:bdcd9c28179f5f7f68fdf276a936a61a3c7675d1a816f6f4b94958fe75ad630b","observation_id":"d317e3c6-aae5-4607-b43d-1581744ed3fe","resolution":{"observed_at":"2026-08-07T11:32:08.664278Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:09.116007Z","title":"S., & Barto, A","venue":null,"work_id":"bd282018-0145-4547-8ac6-6f3659eab6df","year":2018},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:08.289506Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:f239c80f5ddcf6a5df46537019666eefa3d6051aa6756abf2528ba7c20894bfa","observation_id":"8981956d-2212-4550-a281-7ba18ba4d7b8","resolution":{"observed_at":"2026-08-07T11:32:09.209139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:08.915067Z","title":null,"venue":null,"work_id":"51525871-4ef8-4ac0-8f2b-4ff3540ab7f6","year":2002},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:08.393959Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:e78f7b0ded47937b6208931530d89fddd8fdf859e76693c529f079fc758b23f0","observation_id":"15dbc6ad-3b75-42cf-b28e-5ba50b962bc1","resolution":{"observed_at":"2026-08-07T11:32:09.003027Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:32:08.733076Z","title":null,"venue":null,"work_id":"a85b97e2-b530-4170-9586-7ba14c4e3b9e","year":2017},"citing_paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:32:08.495203Z"},"links":{"citing_paper":"/paper/2506.03205"},"observation_digest":"sha256:470d18e75feb0ab9939bee3ff071c035e149e5db9156d893241d39ebeb26889f","observation_id":"82fc7b2e-558c-4539-a65e-bb532892e489","resolution":{"observed_at":"2026-08-07T11:32:08.822253Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.03205","last_updated":"2025-06-02T20:43:33Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-07T11:25:22.917225Z","submitted_at":"2025-06-02T20:43:33Z","title":"Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":1,"verified_fuzzy":3},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2506.03205."}