{"as_of":"2026-08-07T22:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:285eff96973f235f9c356adc2e0b106563b314553f21debf1d630967df1de02c","coverage":[{"denominator":114,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:29:06.583136Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2507.05640/citation-record","integrity":"/paper/2507.05640/integrity","json":"/paper/2507.05640/citation-record.json","paper":"/paper/2507.05640"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:28:54.477532Z","title":"Submission category by year, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:54.477532Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:ee63784dbce5fe81c083defd4d576a2278d70c64a547796b54515a3c10170c7b","observation_id":"47874d6e-1b0d-441b-80d7-468959282daf","resolution":{"observed_at":"2026-08-06T19:28:54.477532Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T19:28:54.571807Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:54.571807Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:3e5ff27f913a997cfe668859b440b24f65782088f123dda42d664c2631f959c2","observation_id":"3e586911-16c4-4a1f-857c-8ac8e7ed0f25","resolution":{"observed_at":"2026-08-06T19:28:54.571807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19437","last_updated":"2025-02-18T17:26:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-27T04:03:16Z","title":"DeepSeek-V3 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19437","snapshot_observed_at":"2026-08-06T19:28:54.699055Z","title":"Deepseek-v3 technical report.arXiv preprint arXiv:2412.19437, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:54.699055Z"},"links":{"cited_paper":"/paper/2412.19437","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:0500f811e62c1ab1bdb701c40644ab75ab5359446c6218a964ffa40fd80f1581","observation_id":"aef7f91a-65cc-4150-8594-4c040cdd55b4","resolution":{"observed_at":"2026-08-06T19:28:54.699055Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.06435","last_updated":"2024-10-17T01:10:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-12T20:01:52Z","title":"A Comprehensive Overview of Large Language Models","version":10},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.06435","snapshot_observed_at":"2026-08-06T19:28:54.802113Z","title":"A comprehensive overview of large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:54.802113Z"},"links":{"cited_paper":"/paper/2307.06435","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:af075534f327de209994cf66d47761a6a29ee1a9770b7490bbba207a6c5f0d53","observation_id":"75a30db5-8d24-4cbc-809d-c65bfbcfa639","resolution":{"observed_at":"2026-08-06T19:28:54.802113Z","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":"2026-08-06T19:28:54.942279Z","title":"Welcome to the era of chatgpt et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:54.942279Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:19ef8b1f4e468b432e93335ffde1fb03cb6693717e15edc860841d6c30b8d57a","observation_id":"2608a315-f770-45a6-ac9c-d160ce2bc401","resolution":{"observed_at":"2026-08-06T19:28:54.942279Z","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":"2026-08-06T19:28:55.069667Z","title":"A survey of sustainability in large language models: Applications, economics, and challenges","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.069667Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:c11ebb608b741f1a07f557c108a94cca38c20f0faf3f2dd1eb8a5d9f7b3f6ef2","observation_id":"f4ace579-341d-4c84-acc5-6c248a373a2a","resolution":{"observed_at":"2026-08-06T19:28:55.069667Z","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":"2026-08-06T19:28:55.145618Z","title":"Randomized algorithms.ACM Computing Surveys (CSUR), 28(1):33–37, 1996","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.145618Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:6c856c5356bf9799c88adce6e2650805b71856f57aed781db6ab86906709136a","observation_id":"83c69f43-08dd-43c2-8ae7-6a1b358c4e6f","resolution":{"observed_at":"2026-08-06T19:28:55.145618Z","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":"2026-08-06T19:28:55.251591Z","title":"Randomized algorithms for matrices and data.Foundations and Trends® in Machine Learning, 3(2):123–224, 2011","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.251591Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:f717aac33ac68b384e8a663accac48ff4b6d3ba8b29bd61d411dba559f20994b","observation_id":"9bfc7952-ff1f-4894-abdc-3dbf2c9d2e92","resolution":{"observed_at":"2026-08-06T19:28:55.251591Z","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":"2026-08-06T19:28:55.321305Z","title":"A survey of randomized algorithms for training neural networks.Information Sciences, 364:146–155, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.321305Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:a258ecd1a773cba923e111052124c544180742638398194686d0c39bc558960e","observation_id":"2bb2de9a-70f6-4d78-933e-0fa69fe16b5b","resolution":{"observed_at":"2026-08-06T19:28:55.321305Z","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":"2026-08-06T19:28:55.408039Z","title":"Springer, 2001","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.408039Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:186717df6a88014aab9f8542a0b45592f1fd28b59c1875d1342dabd01028a22f","observation_id":"fd565960-88a7-47f2-91d2-dc6fba4775ea","resolution":{"observed_at":"2026-08-06T19:28:55.408039Z","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":"2026-08-06T19:28:55.549142Z","title":"Cambridge university press, 2011","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.549142Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:4755f499a55b5909663d089633deb312d11ae6b9fc098bcf176811729c7b5a5f","observation_id":"92daab2b-0bdc-449f-a647-970f45264257","resolution":{"observed_at":"2026-08-06T19:28:55.549142Z","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":"2026-08-06T19:28:55.657996Z","title":"Which problems have strongly exponential complexity?Journal of Computer and System Sciences, 63(4):512–530, 2001","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.657996Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:4c9e524a94ffee4aba3fd4e19546d008d11659d003d838ff03c3af4b9ec3315f","observation_id":"fb2a3af8-6698-4be3-b370-293493a7ba63","resolution":{"observed_at":"2026-08-06T19:28:55.657996Z","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":"2026-08-06T19:28:55.772225Z","title":"Computer architecture and amdahl’s law.Computer, 46(12):38–46, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.772225Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:aa4e655946b37724fe69d8a8983d8a2a06a00c598f2125ec79d191fca394b0fe","observation_id":"e6d2fad3-2f29-4433-bf92-6cc7a90b5fa0","resolution":{"observed_at":"2026-08-06T19:28:55.772225Z","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":"2026-08-06T19:28:55.917785Z","title":"Amdahl’s law in the multicore era.Computer, 41(7):33–38, 2008","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:55.917785Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:6994261dcbc714c537fb51cb53e531449488bf93cccd9012470193c101341bbf","observation_id":"f981da73-4c8c-48df-b25b-d724fb97aea6","resolution":{"observed_at":"2026-08-06T19:28:55.917785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-08-06T19:28:56.067732Z","title":"Qwen3 technical report.arXiv preprint arXiv:2505.09388, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.067732Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:c76d52e04acecbfb8d57a3112c668778ab11d2096c5be7bbede1b1ad6d44edb4","observation_id":"fb9d4329-ae76-4d40-a902-c0f0c0cd12ca","resolution":{"observed_at":"2026-08-06T19:28:56.067732Z","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":"2026-08-06T19:28:56.188295Z","title":"Num- ber 47","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.188295Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:26cc268e71f4065ca62799ff66a1942cc724c6535a70ee806da213df3b5c1d85","observation_id":"2ae1c116-09a3-4f05-a8b0-57f1f85bcd50","resolution":{"observed_at":"2026-08-06T19:28:56.188295Z","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":"2026-08-06T19:28:56.311380Z","title":"Expressive power of parametrized quantum circuits.Physical Review Research, 2(3):033125, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.311380Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:105ebc638fd41e0b7a9aa965a628844ae94e1b6ea463c4cdedc774a118c16203","observation_id":"b1f41c29-cb30-463f-92f4-f9fab0de217d","resolution":{"observed_at":"2026-08-06T19:28:56.311380Z","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":"2026-08-06T19:28:56.385100Z","title":"Expressivity of quantum neural networks.Physical Review Research, 3(3):L032049, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.385100Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:686edabfb7e4dd9f35d8834a7f9e884a1910cf867e5c70a9fdf7a15c4abb5043","observation_id":"8b982939-e200-4994-a14a-70096cb8e5f6","resolution":{"observed_at":"2026-08-06T19:28:56.385100Z","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":"2026-08-06T19:28:56.512189Z","title":"The power of quantum neural networks.Nature Computational Science, 1(6):403–409, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.512189Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:0abc54bdc76bcdd34e91270ba83ff1346063df65e1a52a7f8ed1ba26bab24ef2","observation_id":"dbf84965-8eee-434b-9f59-c47bda8716d5","resolution":{"observed_at":"2026-08-06T19:28:56.512189Z","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":"2026-08-06T19:28:56.649982Z","title":"High-expressibility quantum neural networks using only classical resources","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.649982Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:8c243c6c46b1617d49ab1905fd3550927f8f4891a9c8c7bc08525248cd122743","observation_id":"e8a18e70-5a0f-49af-b15d-761ecf522025","resolution":{"observed_at":"2026-08-06T19:28:56.649982Z","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":"2026-08-06T19:28:56.752233Z","title":"A new model for learning in graph domains","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.752233Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:4cdf0d63849c0fd3f6a58777203e1a53068c09a55bbd65b6a49dd8dc252dd9e3","observation_id":"43a377ad-c364-4a52-8771-51c885a14d71","resolution":{"observed_at":"2026-08-06T19:28:56.752233Z","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":"2026-08-06T19:28:56.900874Z","title":"Graph neural networks for ranking web pages","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:56.900874Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:da1edf39450a1371bd7113efada3bf392822350cff15e08d23e5b3b19bb381a0","observation_id":"f39f2539-348e-454b-abb9-933def688039","resolution":{"observed_at":"2026-08-06T19:28:56.900874Z","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":"2026-08-06T19:28:57.017034Z","title":"The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.017034Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:37078aa9e0d3a6c68fb72979727f3494dfe898dae89a74eaef678794147f2c94","observation_id":"91187175-abfe-4e55-acd2-f9a3b4cb5eb2","resolution":{"observed_at":"2026-08-06T19:28:57.017034Z","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":"2026-08-06T19:28:57.146989Z","title":"Learning skillful medium- range global weather forecasting.Science, 382(6677):1416–1421, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.146989Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:33b5f7fc9fec5d3bda8363df46dbc80e6043ae4a0a1664937e9d2f8b3fa46c2e","observation_id":"f5506199-69b6-4d64-baec-b341f573f706","resolution":{"observed_at":"2026-08-06T19:28:57.146989Z","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":"2026-08-06T19:28:57.245815Z","title":"A gentle intro- duction to graph neural networks.Distill, 6(9):e33, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.245815Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:d9928cdc61e59f02899d755975ab2f838442b05f6edd71aeb104de2dd41b6b83","observation_id":"490182fe-8fac-479c-9475-d60c44c6d68f","resolution":{"observed_at":"2026-08-06T19:28:57.245815Z","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":"2026-08-06T19:28:57.403173Z","title":"Graph neural networks: A review of methods and applications.AI open, 1:57–81, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.403173Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:b9e427d779823b871e11319309d5b498267dde860dd58d25e12f7ab5657f635a","observation_id":"d41b0dc2-820e-47c9-8d78-e548c38a3b62","resolution":{"observed_at":"2026-08-06T19:28:57.403173Z","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":"2026-08-06T19:28:57.549491Z","title":"Graph neural networks: Taxonomy, advances, and trends.ACM Transactions on Intelligent Systems and Technology (TIST), 13(1):1–54, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.549491Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:8e8a628601b24b95fdb1bb3925b35346b3d5801ee7c91689308d09a59ead2276","observation_id":"791710ca-27a6-424f-8cac-4ddc0b6787f5","resolution":{"observed_at":"2026-08-06T19:28:57.549491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-06T19:28:57.641641Z","title":"Semi-supervised classification with graph convolutional networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.641641Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:e4308935b8a114fa93ef9efc41b524f12f41f71cc5d4a6039f01b0468052cc3b","observation_id":"da580746-a4d9-451c-85de-903818c1c28e","resolution":{"observed_at":"2026-08-06T19:28:57.641641Z","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":"2026-08-06T19:28:57.750957Z","title":"Inductive representation learning on large graphs","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.750957Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:9b38ee88468f17f37dc0eeaaf1b361c983140c6f35f5fc3d9c335581342ce159","observation_id":"43b2f5b1-2fca-4720-9040-6f8e450bff95","resolution":{"observed_at":"2026-08-06T19:28:57.750957Z","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":"2026-08-06T19:28:57.885912Z","title":"Graph attention networks.stat, 1050(20):10–48550, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:57.885912Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:f9fc75ceaa88d9847b63114461f11cd9b0fb388a8c7ccaef5abc43a853f15688","observation_id":"29938043-4965-47bd-be64-70191b2d0034","resolution":{"observed_at":"2026-08-06T19:28:57.885912Z","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":"2026-08-06T19:28:58.018009Z","title":"Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 2002","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.018009Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:1629b418e1889bf67dbdbc4d5c89a94c78a48fb0172a24b6483913f7f4f070c8","observation_id":"37003093-1bb4-4e1a-942c-a0da819a2a1d","resolution":{"observed_at":"2026-08-06T19:28:58.018009Z","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":"2026-08-06T19:28:58.112545Z","title":"Deep learning.nature, 521(7553):436–444, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.112545Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:a8266b9b36449de5f262875ce09b0d185c3ec39c0351960e30f42a514998a59e","observation_id":"40b731f8-704c-4346-89d8-a696375210ae","resolution":{"observed_at":"2026-08-06T19:28:58.112545Z","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":"2026-08-06T19:28:58.222753Z","title":"Convolutional neural networks on graphs with fast localized spectral filtering.Advances in neural information processing systems, 29, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.222753Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:080d8a5b4d548d9cdd6da7c5f64fec5d1addc5d6b013eac5ba9913d45eedd460","observation_id":"3f2def16-ed1e-4ada-a69b-9a1972201ab7","resolution":{"observed_at":"2026-08-06T19:28:58.222753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6203","last_updated":"2014-05-21T16:27:09Z","snapshot_observed_at":"2026-07-06T03:31:33.797310Z","submitted_at":"2013-12-21T04:25:53Z","title":"Spectral Networks and Locally Connected Networks on Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6203","snapshot_observed_at":"2026-08-06T19:28:58.357143Z","title":"Spectral networks and locally con- nected networks on graphs.arXiv preprint arXiv:1312.6203, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.357143Z"},"links":{"cited_paper":"/paper/1312.6203","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:82a54041a59dda39967ba77a4d5bff8788d60163a57e7506b4ada77e714d63fe","observation_id":"3cd85dc5-f540-412a-b3c7-9bfd1d1f6853","resolution":{"observed_at":"2026-08-06T19:28:58.357143Z","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":"2026-08-06T19:28:58.458555Z","title":"Understanding convolutions on graphs.Distill, 6(9):e32, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.458555Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:b702bf139ae2f6f7ce83402204ce17b43741f1966ed4c240c450f989ee56a6d3","observation_id":"dacddc4f-066d-4b4e-94e9-a876875a8793","resolution":{"observed_at":"2026-08-06T19:28:58.458555Z","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":"2026-08-06T19:28:58.573150Z","title":"Simplifying graph convolutional networks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.573150Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:b050882279f45a7f48fc28c6ba670a5ee81e0e46b910f5f7a0e25c7cdf587b0f","observation_id":"c509403b-ce0b-4a67-a00f-75e86d217313","resolution":{"observed_at":"2026-08-06T19:28:58.573150Z","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":"2026-08-06T19:28:58.705153Z","title":"Graph signal processing for machine learning: A review and new perspectives.IEEE Signal processing magazine, 37(6):117–127, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.705153Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:ea8733312274af9d273f918c3516c220ad9f65fd95d30debd6de82f64228323d","observation_id":"4d2afeac-d5bc-4eda-9d3c-6f06a8050745","resolution":{"observed_at":"2026-08-06T19:28:58.705153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.06660","last_updated":"2023-09-07T04:09:04Z","snapshot_observed_at":"2026-08-07T20:12:05.984047Z","submitted_at":"2020-12-11T22:09:14Z","title":"Understanding Spectral Graph Neural Network","version":4},"cited_work":{"arxiv_id":"2012.06660","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.06660","snapshot_observed_at":"2026-08-06T19:29:10.066092Z","title":"Understanding Spectral Graph Neural Network","venue":"math.SP","work_id":"b91fef1d-82e6-4789-9eaa-b102441e2a18","year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.851981Z"},"links":{"cited_paper":"/paper/2012.06660","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:0edbba66a9afeef2ee7a8af911fa3268b8628a48fd6830ad5301dd4fc7171971","observation_id":"11477a8f-ce17-4ea8-8abb-5a851cb85901","resolution":{"observed_at":"2026-08-06T19:29:10.173448Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:28:58.938408Z","title":"Graphs, convolutions, and neural networks: From graph filters to graph neural networks.IEEE Signal Processing Magazine, 37(6):128– 138, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:58.938408Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:21c56f79df7b38f0ab438593ab5b36b29a3878f00088cd99821b6ea6010ffed3","observation_id":"0d36ee5f-02d2-4ace-8847-bd97ba1f0f3e","resolution":{"observed_at":"2026-08-06T19:28:58.938408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.05631","last_updated":"2023-02-11T09:16:46Z","snapshot_observed_at":"2026-07-06T14:50:44.713808Z","submitted_at":"2023-02-11T09:16:46Z","title":"A Survey on Spectral Graph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.05631","snapshot_observed_at":"2026-08-06T19:28:59.076692Z","title":"A survey on spectral graph neural networks.arXiv preprint arXiv:2302.05631, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.076692Z"},"links":{"cited_paper":"/paper/2302.05631","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:3e8c6711b64e68ee36dd5ecdcf325df044a3c2b910ccfc26c280e1a1337f149a","observation_id":"9b1e8ef1-128a-472e-b498-1ed4edadeffa","resolution":{"observed_at":"2026-08-06T19:28:59.076692Z","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":"2026-08-06T19:28:59.201005Z","title":"Taylornet: A novel approach for spectral filter learning on graph data.Neurocomputing, 605:128358, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.201005Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:b68e62ffafdbc549a893da875ed7d7b927e16874ad8aa7ecdb64928bec73aaf5","observation_id":"064bfd65-0430-43fa-b8f4-008ec517d1dd","resolution":{"observed_at":"2026-08-06T19:28:59.201005Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"quant-ph/0602174","last_updated":"2006-05-29T17:31:52Z","snapshot_observed_at":"2026-07-07T07:21:53.622782Z","submitted_at":"2006-02-21T19:41:05Z","title":"Universal quantum circuit for n-qubit quantum gate: A programmable quantum gate","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"quant-ph/0602174","snapshot_observed_at":"2026-08-06T19:28:59.338810Z","title":"Universal quantum circuit for n-qubit quantum gate: A programmable quantum gate.arXiv preprint quant-ph/0602174, 2006","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.338810Z"},"links":{"cited_paper":"/paper/quant-ph/0602174","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:a0ab89257c77456d293e16028d708c889c59b22f602b4b585ba6ebc7b4472856","observation_id":"12f3e16f-4834-4598-9f63-f1921dafc9a8","resolution":{"observed_at":"2026-08-06T19:28:59.338810Z","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":"2026-08-06T19:28:59.419606Z","title":"Universal programmable quantum circuit schemes to emulate an operator.The Journal of chemical physics, 137(23), 2012","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.419606Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:6902382258483c8e33090ddb6a299a49ecb5329944e5e96088f3f3df9399927d","observation_id":"f2382976-6cae-4d5d-bab1-97dc80af3d5e","resolution":{"observed_at":"2026-08-06T19:28:59.419606Z","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":"2026-08-06T19:29:21.070000Z","title":"A universal quantum circuit scheme for finding complex eigenvalues.Quantum information processing, 13:333–353, 2014","venue":null,"work_id":"fc6d340b-07af-4bb5-af29-823590f1dec4","year":2014},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.510627Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:0121af6b934fbdd21d641ed25e2c60802fdc082e2e79b21b630b819910e185d4","observation_id":"583fad1d-ea9e-4b3e-bc52-9ee9abacda5a","resolution":{"observed_at":"2026-08-06T19:29:21.255003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:20.765259Z","title":"Parameterized quantum circuits as machine learning models.Quantum science and technology, 4(4):043001, 2019","venue":null,"work_id":"c5556e37-9556-46aa-8d85-85ea7f91e22b","year":2019},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.654234Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:9556e27ce85ef8892e0a90333eb93f43ae711f491a935be909a49dade282ae1c","observation_id":"1ca8fbee-650d-4c0f-9b14-ef552e1c5ef8","resolution":{"observed_at":"2026-08-06T19:29:20.905220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:28:59.745071Z","title":"A variational eigenvalue solver on a photonic quantum processor","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.745071Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:7936dcd6671c654a06d970f0fd1303bb901834f9973d19b061081ae25740fef0","observation_id":"e0126aa0-50a3-496c-9407-0a6d7fa6910e","resolution":{"observed_at":"2026-08-06T19:28:59.745071Z","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":"2026-08-06T19:29:20.488957Z","title":"The theory of varia- tional hybrid quantum-classical algorithms.New Journal of Physics, 18(2):023023, 2016","venue":null,"work_id":"5d1a1c46-631c-499d-8537-43fd93b2d0ca","year":2016},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.848712Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:92912df990d5446078ebd0ffee80da7a89d43e266195e7614a98cdc1e425d074","observation_id":"52eca766-2619-464d-b7b2-b1ac04be178c","resolution":{"observed_at":"2026-08-06T19:29:20.606683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.06199","last_updated":"2017-03-17T21:17:04Z","snapshot_observed_at":"2026-07-06T05:34:12.023454Z","submitted_at":"2017-03-17T21:17:04Z","title":"Quantum Algorithms for Fixed Qubit Architectures","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.06199","snapshot_observed_at":"2026-08-06T19:28:59.966783Z","title":"Quantum algorithms for fixed qubit architectures.arXiv preprint arXiv:1703.06199, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:59.966783Z"},"links":{"cited_paper":"/paper/1703.06199","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:a170d19077e479caca509fdc7f80fe0085ae058a6f23c19317a18a7592ca9bb5","observation_id":"98b00c53-162e-4962-9169-eddf5381e36c","resolution":{"observed_at":"2026-08-06T19:28:59.966783Z","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":"2026-08-06T19:29:20.155125Z","title":"Natural parametrized quantum circuit.Physical Review A, 106(5):052611, 2022","venue":null,"work_id":"8d4e8c6d-cf4f-4096-92ac-41e2d9dc16e3","year":2022},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:00.084104Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:bcc336ccf7e64e8f7985293016e702a768dacc9a9eb13ae285cc8a42382c98f3","observation_id":"0a5485f3-ba38-4771-9c5d-372474057ed1","resolution":{"observed_at":"2026-08-06T19:29:20.294714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.06524","last_updated":"2024-08-12T22:53:14Z","snapshot_observed_at":"2026-07-06T18:59:56.199338Z","submitted_at":"2024-08-12T22:53:14Z","title":"From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.06524","snapshot_observed_at":"2026-08-06T19:29:00.250939Z","title":"From graphs to qubits: A critical review of quantum graph neural networks.arXiv preprint arXiv:2408.06524, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:00.250939Z"},"links":{"cited_paper":"/paper/2408.06524","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:e5e4ab2b89f5fca80ee2fcdf968d0c31b0d314799f30933e547545e73ac4659e","observation_id":"173fb40e-fafe-4440-a84f-d55ae5af3321","resolution":{"observed_at":"2026-08-06T19:29:00.250939Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.00892","last_updated":"2023-02-02T05:53:31Z","snapshot_observed_at":"2026-08-03T21:43:23.839236Z","submitted_at":"2023-02-02T05:53:31Z","title":"Quantum Graph Learning: Frontiers and Outlook","version":1},"cited_work":{"arxiv_id":"2302.00892","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.00892","snapshot_observed_at":"2026-08-06T19:29:09.771052Z","title":"Quantum Graph Learning: Frontiers and Outlook","venue":"cs.LG","work_id":"0af2172c-3483-46aa-97e2-1edbcad19516","year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:00.354537Z"},"links":{"cited_paper":"/paper/2302.00892","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:c73d15efd7e81ee03da648284a743d5ff11b6faf33ad79cae1c8d3a99b39077c","observation_id":"7868bbe0-aa23-4baf-aa34-fd88849d74dc","resolution":{"observed_at":"2026-08-06T19:29:09.874821Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:19.893837Z","title":"How can we naturally order and organize graph laplacian eigenvectors? In2018 IEEE Statistical Signal Processing Workshop (SSP), pages 483–487","venue":null,"work_id":"2c1d1d2e-dfe3-4c55-91b9-8c84ac6d3f0d","year":2018},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:00.464136Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:02578482dcb7d7753c424fa549098eef3852c7d42a2affbac26f551d4fb6008e","observation_id":"9c076224-1ff5-4b78-8e9c-8747455da550","resolution":{"observed_at":"2026-08-06T19:29:19.999670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:19.683087Z","title":"The discrete cosine transform.SIAM review, 41(1):135–147, 1999","venue":null,"work_id":"33022ce2-a910-43fe-bd43-252f0b58a64b","year":1999},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:00.605369Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:1050fe8ff789189e642c9153e2a296b7f0cb07b54d260c3db8e2207e487a383f","observation_id":"17263624-a07d-4bf2-b4cb-87f34eb72a3f","resolution":{"observed_at":"2026-08-06T19:29:19.792274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.01023","last_updated":"2025-05-02T05:40:34Z","snapshot_observed_at":"2026-08-07T15:57:10.524747Z","submitted_at":"2025-05-02T05:40:34Z","title":"Quantum Simulations Based on Parameterized Circuit of an Antisymmetric Matrix","version":1},"cited_work":{"arxiv_id":"2505.01023","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.01023","snapshot_observed_at":"2026-08-06T19:29:09.541842Z","title":"Quantum Simulations Based on Parameterized Circuit of an Antisymmetric Matrix","venue":"quant-ph","work_id":"dd8349b9-cd7a-4516-b521-59899dd48e5a","year":2025},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:00.753258Z"},"links":{"cited_paper":"/paper/2505.01023","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:8dfbf43951105a3bf44f00ad647aabeabb64755c6b14654f7e53fb37adc0addb","observation_id":"c1622c89-e8d2-4a80-9343-e01fa17b9cc6","resolution":{"observed_at":"2026-08-06T19:29:09.632535Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:00.896965Z","title":"American Mathematical Soc., 1997","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:00.896965Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:0f379dc15ea08aa6f13488b26ebc8cb2498d91759c76983a1dc09e8c58cc2d68","observation_id":"155b6204-b756-4c7c-b43f-840e6e683fe3","resolution":{"observed_at":"2026-08-06T19:29:00.896965Z","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":"2026-08-06T19:29:19.456401Z","title":"Laplacian matrices of graphs: a survey.Linear algebra and its applications, 197:143–176, 1994","venue":null,"work_id":"f60c7787-c306-49ee-80c5-3522cc7287ec","year":1994},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:01.026986Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:643a5fc2f359156367df3c12974394557d2bea6de81773fc5a5bb106665675dc","observation_id":"8055a775-e6b0-4fe8-85c5-f922a88d7993","resolution":{"observed_at":"2026-08-06T19:29:19.545033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:19.244448Z","title":"Algorithms, graph theory, and linear equations in laplacian matrices","venue":null,"work_id":"f5c31faf-ff51-4056-abc5-88c3ea2d27f6","year":2010},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:01.135353Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:133bbe11695b40a750f27b4000ead62ecf8ba84ba13006404c42a88f5b78fba8","observation_id":"4766bee0-5e97-43ea-b5fc-6bba43eabe21","resolution":{"observed_at":"2026-08-06T19:29:19.328185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:01.252217Z","title":"A tutorial on spectral clustering.Statistics and computing, 17:395–416, 2007","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:01.252217Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:cc6d34510aead50d3fbc61508e82864ebe66b9908a74747823a4da346cc7d224","observation_id":"383cdcc7-8a5d-4480-9cf6-2616870c623b","resolution":{"observed_at":"2026-08-06T19:29:01.252217Z","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":"2026-08-06T19:29:18.984271Z","title":"Quantum spectral clustering through a biased phase estimation algorithm.TWMS Journal of Applied and Engineering Mathematics, 10(1):24–33, 2017","venue":null,"work_id":"c360debb-b102-4e69-9cdd-485f6a0df3db","year":2017},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:01.365154Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:af20f22d5ce1ed8a0e480cc63a906123d564179867214a7372bf0cf6c0455e48","observation_id":"f23b0351-2079-4102-81cf-c4415d279f7e","resolution":{"observed_at":"2026-08-06T19:29:19.085085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:18.726074Z","title":"Convergence of laplacian eigenmaps.Advances in neural information processing systems, 19, 2006","venue":null,"work_id":"9de7918c-7858-460a-8bd1-1708f4aef8e5","year":2006},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:01.511972Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:c9dfeedb1baf4fa9ef28ea98989542be330a171628ee76666a31448c816e894d","observation_id":"66d2905c-7d27-4c17-b05a-eafd9e1c21b7","resolution":{"observed_at":"2026-08-06T19:29:18.819116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:18.470096Z","title":"Manifold learning: What, how, and why.Annual Review of Statistics and Its Application, 11(1):393–417, 2024","venue":null,"work_id":"eccb2b06-da55-45d4-9972-173d67269dab","year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:01.699949Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:58f5847bdf16a7eeb9a1e6535bf5976a7e3235a224729e12becf17ba9b49a000","observation_id":"e3382ba6-d272-474b-acd8-9eb7d9d44281","resolution":{"observed_at":"2026-08-06T19:29:18.608687Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:18.241310Z","title":"A user guide to low-pass graph signal pro- cessing and its applications: Tools and applications.IEEE Signal Processing Magazine, 37(6):74–85, 2020","venue":null,"work_id":"0e2df3f0-05e0-4cf9-a81f-b04bf780608c","year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:01.852704Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:2d5fd43b2bdb9912b3d14bf7730514c0b26bfc776ebd9a9e4e24fdba49026736","observation_id":"946643ba-a64c-4cec-9a8c-a0d061dcdcc1","resolution":{"observed_at":"2026-08-06T19:29:18.349622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.08458","last_updated":"2015-12-02T18:06:03Z","snapshot_observed_at":"2026-07-06T04:37:52.737823Z","submitted_at":"2015-11-26T17:45:01Z","title":"An Introduction to Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.08458","snapshot_observed_at":"2026-08-06T19:29:02.000903Z","title":"An introduction to convolutional neural networks.arXiv preprint arXiv:1511.08458, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.000903Z"},"links":{"cited_paper":"/paper/1511.08458","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:fa020ed5974b2a51f9e35f314b36649bc908ab53bfebc95b4102523066cce64f","observation_id":"86b7c5bd-ded1-409c-a38f-c2ebf2a7840b","resolution":{"observed_at":"2026-08-06T19:29:02.000903Z","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":"2026-08-06T19:29:18.008864Z","title":"Introduction to convolutional neural networks.National Key Lab for Novel Software Technology","venue":null,"work_id":"581a4944-0a81-4d07-b326-9c429c1c4c78","year":2017},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.129735Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:8a77ed1484ee5765676f9abb99ae908146c0c466c8f9528b89b589f2f7a352cd","observation_id":"717fae10-8ccd-41a2-a71d-51465dbfb7e7","resolution":{"observed_at":"2026-08-06T19:29:18.117100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:02.305240Z","title":"A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 33(12):6999–7019, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.305240Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:e29a295ac79bb69f4a73030075405b5d4babd05f5495f6a90631c1721bbbf875","observation_id":"c97d06e5-4483-485b-9bd7-92fad0f95d36","resolution":{"observed_at":"2026-08-06T19:29:02.305240Z","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":"2026-08-06T19:29:17.763393Z","title":"Review of lightweight deep convolutional neural networks.Archives of Computational Methods in Engineering, 31(4):1915–1937, 2024","venue":null,"work_id":"cc7b29be-9d2b-4ee6-a68f-e52de7b53224","year":1915},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.468321Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:f8f3e0a9ef4c51e5ce505e220d4a7041aaa6fdb8bf8a5f96743d38aaa019949a","observation_id":"f2c5282a-1168-4702-b41b-216abbaca773","resolution":{"observed_at":"2026-08-06T19:29:17.873827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:17.627638Z","title":"Convolutional neural networks on graphs with chebyshev approximation, revisited.Advances in neural information processing systems, 35:7264–7276, 2022","venue":null,"work_id":"5ed88199-ea97-4bdd-a0c6-fd762a96e464","year":2022},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.567934Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:d78a1f5fe9cc9d2dda914d6e7cdf331524e64e30bdf4274e65912b42c82671f4","observation_id":"94b2236d-1916-428a-a656-8dae472071a0","resolution":{"observed_at":"2026-08-06T19:29:17.691458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:17.392562Z","title":"Graph neural network, chebnet, graph convolutional network, and graph autoencoder: Tutorial and survey","venue":null,"work_id":"0728ddba-cb3e-4913-a0ad-b754d87cce61","year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.687322Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:1c222f02938f5bc24356b788f3d4e1ecef3806774d44a6b4494c8a5da364534b","observation_id":"da38fcc2-d478-41e4-88b0-b0ff9da0f54c","resolution":{"observed_at":"2026-08-06T19:29:17.511773Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:17.148246Z","title":"Spectral representations for convolutional neural networks.Advances in neural information processing systems, 28, 2015","venue":null,"work_id":"36bc6b4f-8b69-4ddc-be70-b88556d1cd86","year":2015},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.827661Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:db6fe8c58d26fb64e0a3ec2150e1840b1291f2ee2bfaaea2d110e5ba7b251b66","observation_id":"c3232043-ae35-43d8-b877-7719532245e8","resolution":{"observed_at":"2026-08-06T19:29:17.240188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:16.934423Z","title":"On the stability of polynomial spectral graph fil- ters","venue":null,"work_id":"6d08b667-52e1-4a11-894f-4292c131c7f8","year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:02.931991Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:4d3fb58ed4105f3b48f0143b6149902f05241d8a507558c2ffa59153e3708414","observation_id":"f62c29c3-7f25-492c-8b15-ef84397e97b6","resolution":{"observed_at":"2026-08-06T19:29:17.028877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:03.055762Z","title":"JHU press, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.055762Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:8f7c6696101edb99f3ab7cf3aace32baa03ce935e5cd14759c3953482061253c","observation_id":"87ddc19c-8f98-48c3-a255-ba86b3d01631","resolution":{"observed_at":"2026-08-06T19:29:03.055762Z","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":"2026-08-06T19:29:16.642408Z","title":"Wavelets on graphs via spectral graph theory.Applied and Computational Harmonic Analysis, 30(2):129–150, 2011","venue":null,"work_id":"798cbca2-70c1-40b9-8e89-6bb62deabbe2","year":2011},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.155698Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:98b21af9a28287b563842d7886fed898a5e94cf91a608c135fc1ee9252e5ebd3","observation_id":"b7a8c060-ad7f-402e-aff9-7f7fc5209db4","resolution":{"observed_at":"2026-08-06T19:29:16.770470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:16.353903Z","title":"Revisiting convolutional neural network on graphs with polynomial approximations of laplace–beltrami spectral filtering.Neural Computing and Applications, 33:13693–13704, 2021","venue":null,"work_id":"fb48dbc8-fd9d-4043-afc6-92503f5ca6a6","year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.299582Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:838086bc193a2f2ce4efcb4a005ebe0fdf8440e855380b0170b4d1ad3ea135c6","observation_id":"b9dcf73d-43a6-41d8-a4df-2f36fde1c22a","resolution":{"observed_at":"2026-08-06T19:29:16.503564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:16.041887Z","title":"Quantum convolutional neural networks.Nature Physics, 15(12):1273–1278, 2019","venue":null,"work_id":"4b6b32c6-d83b-48a7-82f7-f092c9395208","year":2019},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.459444Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:25434e13e03843483987ba6cc8a9a014e893381df8dd9d03119316932cd032a5","observation_id":"5e5fb737-656e-45f2-9f11-8d6a23f67a75","resolution":{"observed_at":"2026-08-06T19:29:16.192030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:15.835599Z","title":"A tutorial on quantum convolutional neural networks (qcnn)","venue":null,"work_id":"0402040b-c575-4e07-b16d-15fbd8e3b47a","year":2020},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.553633Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:036214c94d6af42a30ddf024422737935f8ceb6f08951229c008177f319d1671","observation_id":"bed9a070-e90d-477f-8d8a-bee8f95b41a4","resolution":{"observed_at":"2026-08-06T19:29:15.903228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:15.625565Z","title":"Quantum convo- lutional neural networks for high energy physics data analysis.Physical Review Research, 4(1):013231, 2022","venue":null,"work_id":"ef7ae82e-a2bf-4ecd-9491-a8782cbfb9e0","year":2022},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.659537Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:940c1593488c2f8677ed73b831b0cd320dbb4a7ad91eb086f7a65612a76c28a5","observation_id":"c0b69124-175a-4e55-9c7e-6b6826a8f97a","resolution":{"observed_at":"2026-08-06T19:29:15.716653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:15.397990Z","title":"Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases.Nature communications, 13(1):4144, 2022","venue":null,"work_id":"a7545448-bad6-4908-80ac-302c8c9002d3","year":2022},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.776037Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:99e8a5cead304d354abdcb5ee9b95ea6dfb96c4eebdd1a794530c565b1b94889","observation_id":"7d24ce8e-da40-4926-a70b-ff910026e28e","resolution":{"observed_at":"2026-08-06T19:29:15.497299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:15.163530Z","title":"What can we learn from quantum convolutional neural networks?Advanced Quantum Technologies, page 2400325, 2023","venue":null,"work_id":"89baa01f-50ee-482b-8804-2f9b16f6bd60","year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.895661Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:5ef6ac842bb003d3fbaea89e88e265847d6ac36b9ec5f9c0ff1ed428f3877b1a","observation_id":"1b0ec24c-1074-4d24-8591-8d728f439a1e","resolution":{"observed_at":"2026-08-06T19:29:15.276885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:14.898238Z","title":"Hybrid quantum-classical convolutional neural networks.Science China Physics, Mechanics & Astronomy, 64(9):290311, 2021","venue":null,"work_id":"1902b29a-bd89-4948-86c9-56b1900587d9","year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:03.984931Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:553b91241536bdb12cdd4d11295076a8e5e8e48c3963c072a5ad71334ddd9ee7","observation_id":"990abaf9-69a2-431e-992d-324989ad212a","resolution":{"observed_at":"2026-08-06T19:29:15.013168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:14.658664Z","title":"Quantum convolutional neural networks for multi-channel supervised learning.Quantum Machine Intelligence, 5(2):41, 2023","venue":null,"work_id":"ce73f98d-b927-4fee-a8fe-6d603df32e39","year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.099449Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:be0f22b18b49f582b9dccb1cf55df31bb22c00880e0ed336d2f4ca8aa6f22113","observation_id":"4647e3fa-d919-4a16-a7dd-6593510e3174","resolution":{"observed_at":"2026-08-06T19:29:14.776065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:14.446649Z","title":"Classical-to-quantum convolutional neural network transfer learning.Neurocomputing, 555:126643, 2023","venue":null,"work_id":"173887a9-4d65-40fe-ad43-838e2eefa232","year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.254437Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:74b4ad4ebccd99670b26ca14037abe929ec43161232abda4ad637440bff0cbf9","observation_id":"d8ead58d-b166-4d1a-8e37-b0b529777048","resolution":{"observed_at":"2026-08-06T19:29:14.547372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:14.214340Z","title":"Quantum convolutional neural network based on variational quantum circuits.Optics Communications, 550:129993, 2024","venue":null,"work_id":"0150c9d9-d725-4804-9b1a-13aef90b93ac","year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.348500Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:73574c6762125b7ebf7474d2ae3cf786dc55f1602c4e5aa0573bd289b4390350","observation_id":"3d9cc071-16a8-4942-bb09-917c0a25be47","resolution":{"observed_at":"2026-08-06T19:29:14.303342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.01117","last_updated":"2019-11-04T10:34:46Z","snapshot_observed_at":"2026-07-06T08:34:27.100900Z","submitted_at":"2019-11-04T10:34:46Z","title":"Quantum Algorithms for Deep Convolutional Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.01117","snapshot_observed_at":"2026-08-06T19:29:04.480697Z","title":"Quantum algorithms for deep convolutional neural networks.arXiv preprint arXiv:1911.01117, 2019","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.480697Z"},"links":{"cited_paper":"/paper/1911.01117","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:bb15767b464d4920d7eb9280869bf9771bb7d6fd8d95a09c384f6671188bfeb4","observation_id":"5ed28cec-c950-47e3-9fb9-78d38c3aee32","resolution":{"observed_at":"2026-08-06T19:29:04.480697Z","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":"2026-08-06T19:29:13.986326Z","title":"Quantum optical convolutional neural network: a novel image recognition framework for quantum computing.IEEE access, 9:103337–103346, 2021","venue":null,"work_id":"d2470282-61d2-4e75-8441-82068aab71f7","year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.600792Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:e4a5598687eb63823e83ba6989fc91d30a5063a7fb13d0245eb3ce1737bcd24d","observation_id":"256b39bc-bc06-4eec-b633-b834d51142b1","resolution":{"observed_at":"2026-08-06T19:29:14.089003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.12739","last_updated":"2026-02-20T19:42:27Z","snapshot_observed_at":"2026-07-06T19:04:52.658000Z","submitted_at":"2024-08-22T21:46:19Z","title":"Quantum Convolutional Neural Networks are Effectively Classically Simulable","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.12739","snapshot_observed_at":"2026-08-06T19:29:04.694639Z","title":"Quantum convolutional neural networks are (effectively) classically simulable.arXiv preprint arXiv:2408.12739, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.694639Z"},"links":{"cited_paper":"/paper/2408.12739","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:a80b47b37e3fb857c4a74193d67c523ce096b4c3ce8150881fa00326fa5e4715","observation_id":"715f99e6-e8ff-41b4-83d8-12ca2dfa06ee","resolution":{"observed_at":"2026-08-06T19:29:04.694639Z","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":"2026-08-06T19:29:13.761976Z","title":"Efficient classical simulation of random shallow 2d quantum circuits.Physical Review X, 12(2):021021, 2022","venue":null,"work_id":"8ee5266d-367a-4f83-bff0-f8afc3b7ac56","year":2022},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.795645Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:4722d646472dc77ed899a928ae075fc4c9180f3746bba974cab2c6a7e2a6b230","observation_id":"bcba1630-4212-4f33-8ed2-8eec593a773c","resolution":{"observed_at":"2026-08-06T19:29:13.861294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.12264","last_updated":"2019-09-26T17:19:16Z","snapshot_observed_at":"2026-07-06T08:24:58.301676Z","submitted_at":"2019-09-26T17:19:16Z","title":"Quantum Graph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.12264","snapshot_observed_at":"2026-08-06T19:29:04.948196Z","title":"Quantum graph neural networks.arXiv preprint arXiv:1909.12264, 2019","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:04.948196Z"},"links":{"cited_paper":"/paper/1909.12264","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:4ecdb361ea60103781cbe3e2e46910e3e29124646ce6ff34f049914efe66d655","observation_id":"9670067a-a888-4d8b-ba1e-dd0cf22c06ee","resolution":{"observed_at":"2026-08-06T19:29:04.948196Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1411.4028","last_updated":"2014-11-14T19:57:57Z","snapshot_observed_at":"2026-07-06T04:00:38.324755Z","submitted_at":"2014-11-14T19:57:57Z","title":"A Quantum Approximate Optimization Algorithm","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1411.4028","snapshot_observed_at":"2026-08-06T19:29:05.082070Z","title":"A quantum approximate optimization algorithm","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:05.082070Z"},"links":{"cited_paper":"/paper/1411.4028","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:27f1e7cd121bba04c371f8b8dd69801094b5f270c7d449678c113b8eebcf5946","observation_id":"7ee1cf21-d779-44dd-aac4-5d152d9c1f0a","resolution":{"observed_at":"2026-08-06T19:29:05.082070Z","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":"2026-08-06T19:29:05.217938Z","title":"From the quantum approximate optimization algorithm to a quantum alternating operator ansatz.Algorithms, 12(2):34, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:05.217938Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:bbb4066b2e010fa9e69cbb8c61832c702927f649a6d6afbe9e00378e6c965cdc","observation_id":"ca86fc88-c336-4662-ba84-56c4249043da","resolution":{"observed_at":"2026-08-06T19:29:05.217938Z","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":"2026-08-06T19:29:13.487133Z","title":"Quantum-based subgraph convolutional neural networks.Pattern Recognition, 88:38–49, 2019","venue":null,"work_id":"6eb936db-5fc3-4c02-b3cc-54d742d314cf","year":2019},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:05.370011Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:4dca5348d5750380c0020eb6792518f25016baaf5aca7deed5af27ec779dc010","observation_id":"75666890-3800-4b67-914b-a4136129360e","resolution":{"observed_at":"2026-08-06T19:29:13.598980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:13.269652Z","title":"On the design of quantum graph convolutional neural network in the nisq-era and beyond","venue":null,"work_id":"8d459c56-b63f-4d4d-b2b3-86b8e1c03c64","year":2022},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:05.544920Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:cd0b1b58236b9d2137f4706f0ffee8580b78bbe37c56b09fd26e1c0f885da847","observation_id":"cda199e5-13a1-41dd-b779-770af9e1b41e","resolution":{"observed_at":"2026-08-06T19:29:13.366382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:13.077895Z","title":"A quantum spatial graph convolu- tional neural network model on quantum circuits.IEEE Transactions on Neural Networks and Learning Systems, 2024","venue":null,"work_id":"46878d6f-4de8-4144-b601-ebce860105eb","year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:05.640206Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:ee7148e56f0fa10ed0b98c73da5175fa3066d163dd353e0519a6664badd13c84","observation_id":"44b9d395-a971-4d8f-819a-01dba320920a","resolution":{"observed_at":"2026-08-06T19:29:13.168907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:12.873006Z","title":"Financial fraud detection using quantum graph neural networks.Quantum Machine Intelligence, 6(1):7, 2024","venue":null,"work_id":"d6f93eec-c02f-4a12-a3c6-619d19788ea0","year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:05.753424Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:fa9892ba17462414e7ffe0f66d3808482f6a9e4a43f3b3212dbb02dadbca5c77","observation_id":"f49304a0-ee64-4bc4-a23e-3f797fdc33b5","resolution":{"observed_at":"2026-08-06T19:29:12.961278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:12.607727Z","title":"Quantum graph neural network models for materials search.Materials, 16(12):4300, 2023","venue":null,"work_id":"37dbf644-1b72-4262-933f-660199b41961","year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:05.881296Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:845ec3523eeac23f62ab3e6b9794d8a2db78897d0f18ef3a53311d3580aa14b7","observation_id":"2eb94d19-5fd7-4f93-942a-4de1e129d921","resolution":{"observed_at":"2026-08-06T19:29:12.725927Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T19:29:12.384749Z","title":"A unifying primary framework for qgnns from quantum graph states.The European Physical Journal Special Topics, pages 1–10, 2024","venue":null,"work_id":"d63f0a1f-12a8-4b14-bbf5-d4e555feda09","year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:06.004160Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:dd0b04ed6532c591996e1f7da069e11f5f32b5d7698ce2e12d9080c652ffcfb2","observation_id":"4609e3b4-87f7-48dc-9c76-dd875cc3ecf9","resolution":{"observed_at":"2026-08-06T19:29:12.506759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07174","last_updated":"2024-12-06T11:06:54Z","snapshot_observed_at":"2026-08-07T18:11:12.626536Z","submitted_at":"2024-04-10T17:17:05Z","title":"Ground state-based quantum feature maps","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07174","snapshot_observed_at":"2026-08-06T19:29:06.124469Z","title":"Ground state-based quantum feature maps.arXiv preprint arXiv:2404.07174, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:06.124469Z"},"links":{"cited_paper":"/paper/2404.07174","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:a510ba6c861f08d6174e845bbe87aac0c425a97b9b9654d1a3ccfc581f321dc9","observation_id":"23982e64-c6e3-4408-acee-97f439cc03a0","resolution":{"observed_at":"2026-08-06T19:29:06.124469Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.19461","last_updated":"2026-04-28T03:02:55Z","snapshot_observed_at":"2026-07-06T21:46:53.087123Z","submitted_at":"2025-06-24T09:40:10Z","title":"Iterative Quantum Feature Maps","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.19461","snapshot_observed_at":"2026-08-06T19:29:06.250765Z","title":"Iterative quantum feature maps.arXiv preprint arXiv:2506.19461, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:06.250765Z"},"links":{"cited_paper":"/paper/2506.19461","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:05cce7c2adaf14343aa400d2466e6a563870e58da6a865ee463a802a06679d4d","observation_id":"3c00298b-130b-49c0-a2bd-667b58f87444","resolution":{"observed_at":"2026-08-06T19:29:06.250765Z","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":"2026-08-06T19:29:12.176318Z","title":"Efficient quantum feature extraction for cnn-based learning","venue":null,"work_id":"17c3707a-2e46-44dd-93f4-477564c1e3e8","year":2023},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:06.353931Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:1ec203cb014198ff2e2b321594040b8fdd5d1e47a962457c8e5a0ff22b682f72","observation_id":"101a23f9-2327-43a4-af85-5a6555a62d6e","resolution":{"observed_at":"2026-08-06T19:29:12.301867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.06189","last_updated":"2021-01-15T16:02:52Z","snapshot_observed_at":"2026-08-03T18:38:13.451621Z","submitted_at":"2021-01-15T16:02:52Z","title":"Hybrid Quantum-Classical Graph Convolutional Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.06189","snapshot_observed_at":"2026-08-06T19:29:06.474673Z","title":"Hybrid quantum- classical graph convolutional network.arXiv preprint arXiv:2101.06189, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:06.474673Z"},"links":{"cited_paper":"/paper/2101.06189","citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:d720f2bdb881a6811b44d36d50d76984a9d2f2430fbd3a6b7a26b688e369f866","observation_id":"b1cce699-5483-4e57-b8a3-eeba682d2686","resolution":{"observed_at":"2026-08-06T19:29:06.474673Z","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":"2026-08-06T19:29:11.958536Z","title":"Quantum graph as a quantum spectral filter.Journal of Mathematical Physics, 54(3), 2013","venue":null,"work_id":"9970f84b-18bf-4798-b510-79f2f2781f52","year":2013},"citing_paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks","version":2},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-06T19:29:06.583136Z"},"links":{"citing_paper":"/paper/2507.05640"},"observation_digest":"sha256:79060d1506822d7be020ddb26d6dd3d6e874bd9a40a5d8f2aba03f0b9f792f5f","observation_id":"e45ab4df-8f9c-49a2-a82d-0e7d27db4219","resolution":{"observed_at":"2026-08-06T19:29:12.048377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.05640","last_updated":"2025-07-11T15:46:42Z","latest_version":2,"primary_category":"quant-ph","snapshot_observed_at":"2026-08-07T20:47:09.743772Z","submitted_at":"2025-07-08T03:36:40Z","title":"Learnable quantum spectral filters for hybrid graph neural networks"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":58,"verified_exact":3,"verified_fuzzy":39},"total_outbound_references":114},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 100 of 114 outbound references and 0 inbound Pith citation observations for arXiv:2507.05640."}