{"as_of":"2026-08-21T16:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:97afe2e5ee4f228ecbe46f9d43737f97be7d7d2c70e892ba7ce0afeb340a6f03","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T17:45:00.708043Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2507.20537/citation-record","integrity":"/paper/2507.20537/integrity","json":"/paper/2507.20537/citation-record.json","paper":"/paper/2507.20537"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.10315","last_updated":"2025-06-10T11:45:54Z","snapshot_observed_at":"2026-08-16T14:51:48.203637Z","submitted_at":"2023-10-16T11:52:54Z","title":"A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10315","snapshot_observed_at":"2026-08-15T17:45:00.542600Z","title":"A survey on quantum machine learning: Current trends, challenges, opportunities, and the road ahead,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.542600Z"},"links":{"cited_paper":"/paper/2310.10315","citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:5459d27b1ad0b4fb9647777cd535016ad85fb53ff3acf55bb46f9fbcecdbb227","observation_id":"d4c8224e-1233-4287-8acd-8ad1a972810b","resolution":{"observed_at":"2026-08-15T17:45:00.542600Z","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":"2026-08-15T17:45:00.548787Z","title":"Quantum computing in the nisq era and beyond,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.548787Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:5aa6f9cabe1dcc888b4e6d33ac9d7aaffa6ebc8f221ca5e41451b682a6974e78","observation_id":"b41691f0-a8db-4bbe-a469-a25741a47caf","resolution":{"observed_at":"2026-08-15T17:45:00.548787Z","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":"2026-08-15T17:45:00.555693Z","title":"A comparative analysis of hybrid-quantum classical neural networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.555693Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:917bdade895cd4702468ac08770cf366c3c0119905ff0cb976ce6b9e984b7634","observation_id":"d069a441-ba2d-4032-bd30-ad8df1a4f4bb","resolution":{"observed_at":"2026-08-15T17:45:00.555693Z","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":"2026-08-15T17:45:00.561757Z","title":"Computational advantage in hybrid quantum neural networks: Myth or reality?,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.561757Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:66bd3f5d58665ec587cfd56608f60b196e2a291b69283c1d7d04cbc5b590cd66","observation_id":"e905b0aa-4423-4fdc-898d-c3c9bd1bebc7","resolution":{"observed_at":"2026-08-15T17:45:00.561757Z","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":"2026-08-15T17:45:00.566792Z","title":"Design space exploration of hybrid quantum–classical neural networks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.566792Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:3427fcf89259d2d9ceea5c9bc52729733c986ade431d4c28e0803ecf1c79743a","observation_id":"d4e94c87-6460-4cd1-8cfd-ce17df6e2ea4","resolution":{"observed_at":"2026-08-15T17:45:00.566792Z","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":"2026-08-15T17:45:00.572500Z","title":"Barren plateaus in quantum neural network training landscapes,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.572500Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:1e5351abacdd94a28f77dd5c7f40955bf32cc7de60286fd9781ea8e542e33edc","observation_id":"f8b47247-6be9-4b65-90c6-c0fc514a4b72","resolution":{"observed_at":"2026-08-15T17:45:00.572500Z","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":"2026-08-15T17:45:01.345002Z","title":"Investigating the effect of noise on the training performance of hybrid quantum neural networks,","venue":null,"work_id":"b2029302-6837-44c6-8dfb-008d65775c77","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.579792Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:80b95039db318d9d80242bbc2b5ecd1783452ab6491722475677021ef54771ab","observation_id":"6e6004df-e31a-4c28-8190-df1b5a6c47ab","resolution":{"observed_at":"2026-08-15T17:45:01.350426Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:01.328461Z","title":"Alleviating barren plateaus in parameterized quantum machine learning circuits: Investigating advanced parameter initializa- tion strategies,","venue":null,"work_id":"09bc5292-7748-4e60-84cf-5d821ba1c23e","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.585596Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:b88fbc359e7279745738bcbecd79c2e9ef488602d7b312bcf8c9af01e9fb0289","observation_id":"7b2bccf1-327b-42bd-b605-19b4e1db24d5","resolution":{"observed_at":"2026-08-15T17:45:01.334637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:00.591884Z","title":"The impact of cost function globality and locality in hybrid quantum neural networks on nisq devices,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.591884Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:1148ce623013995eb732c38ab33d68f83576d4bd0082fbcc2bdc2ee3603b5b40","observation_id":"1be6a63a-b62c-4612-b21b-06a8684c1bf0","resolution":{"observed_at":"2026-08-15T17:45:00.591884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.08475","last_updated":"2025-09-11T13:21:55Z","snapshot_observed_at":"2026-07-06T17:29:30.280372Z","submitted_at":"2024-02-13T14:08:18Z","title":"HQNET: Harnessing Quantum Noise for Effective Training of Quantum Neural Networks in NISQ Era","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.08475","snapshot_observed_at":"2026-08-15T17:45:00.596776Z","title":"Hqnet: Harnessing quantum noise for effec- tive training of quantum neural networks in nisq era,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.596776Z"},"links":{"cited_paper":"/paper/2402.08475","citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:3f953b4f1f5b8e8de3babb3de50abdd1496d2e6f301928e07ee61592f3766e1e","observation_id":"54b1082d-7e94-4bc3-9924-aad061bb6f50","resolution":{"observed_at":"2026-08-15T17:45:00.596776Z","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":"2026-08-15T17:45:00.602727Z","title":"The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of hqnns,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.602727Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:349e362e682eb1e170af5ef818f9f44444708de66404304e1f1a38ffe50cf2b0","observation_id":"b0e89d6f-f11e-4119-90c4-39a289b68fbe","resolution":{"observed_at":"2026-08-15T17:45:00.602727Z","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":"2026-08-15T17:45:01.293877Z","title":"The dilemma of random parameter initialization and barren plateaus in variational quantum algorithms,","venue":null,"work_id":"4da72660-0627-4bd1-bb57-13614d3d2847","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.608582Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:187632503820eb0607bf05d6e7735b773a0f280bb5cdb5f99f94ea6a2089a817","observation_id":"a968b991-4531-4902-afda-45963cf140d8","resolution":{"observed_at":"2026-08-15T17:45:01.298821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:00.614303Z","title":"Resqnets: a residual approach for mit- igating barren plateaus in quantum neural networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.614303Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:a389303d8432fd3223f41468632ee38f2ea4144f89cf21aad86ea479838576cc","observation_id":"9e811a75-1f27-4116-986d-8f0951b50557","resolution":{"observed_at":"2026-08-15T17:45:00.614303Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.09146","last_updated":"2025-07-07T06:34:42Z","snapshot_observed_at":"2026-08-21T02:51:57.207368Z","submitted_at":"2024-02-14T12:55:28Z","title":"ResQuNNs: Towards Enabling Deep Learning in Quantum Convolution Neural Networks","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.09146","snapshot_observed_at":"2026-08-15T17:45:00.619275Z","title":"Resqunns:towards enabling deep learning in quantum convolution neural networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.619275Z"},"links":{"cited_paper":"/paper/2402.09146","citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:b8a5768005e39a8495dd83975208232ae90b1d6c9359e508fb710e8bb841ff8e","observation_id":"6c6ebc71-44bf-4741-b749-cdfabc4b96ff","resolution":{"observed_at":"2026-08-15T17:45:00.619275Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04844","last_updated":"2025-08-28T12:22:12Z","snapshot_observed_at":"2026-08-20T03:21:16.189613Z","submitted_at":"2024-12-06T08:29:46Z","title":"Cutting is All You Need: Execution of Large-Scale Quantum Neural Networks on Limited-Qubit Devices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04844","snapshot_observed_at":"2026-08-15T17:45:00.624152Z","title":"Cutting is all you need: Execution of large- scale quantum neural networks on limited-qubit devices,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.624152Z"},"links":{"cited_paper":"/paper/2412.04844","citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:aadd55b1aa47b294c79449f837eadc254e1364585614d12c61f11b44bacf0553","observation_id":"5454bc62-7c87-4e1a-93a3-a1c33f62171d","resolution":{"observed_at":"2026-08-15T17:45:00.624152Z","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":"2026-08-15T17:45:01.268711Z","title":"Noisy hqnns: A comprehensive analysis of noise robustness in hybrid quantum neural networks,","venue":null,"work_id":"d566e816-89fa-491f-a9c7-a8990e69c6a3","year":2025},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.629431Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:fc55f8f79b7e0e75836ecad415a2354afd8ec5da706d8a174d1404c4ac3b7978","observation_id":"dce42154-6e20-48c8-af95-b1356adebbcd","resolution":{"observed_at":"2026-08-15T17:45:01.273812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:00.634024Z","title":"Nrqnn: The role of observable selection in noise-resilient quantum neural networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.634024Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:a6a8dc26a39a779a11ce26b483539aeaaf75f8bbedfe74342c4a44a151e0824d","observation_id":"3973faa3-5053-459f-baae-1ab4b942453b","resolution":{"observed_at":"2026-08-15T17:45:00.634024Z","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":"2026-08-15T17:45:01.241036Z","title":"Advqunn: A methodology for analyzing the adversarial robustness of quanvolutional neural networks,","venue":null,"work_id":"59acb8de-d769-4d9d-baf1-b9a25e424025","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.638855Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:ae76b7da77120699e5c8db46003f80d3bbb797d01ebd45e46fc339132f37275a","observation_id":"6617076e-5067-4482-8cd6-1f5ad8275ca8","resolution":{"observed_at":"2026-08-15T17:45:01.246132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:01.223883Z","title":"Robqunns: A methodology for robust quanvolu- tional neural networks against adversarial attacks,","venue":null,"work_id":"810e4fc4-3dce-4e85-a28a-5ef36747b89c","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.644079Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:1f14438ed53ea3c5b420596a090ee5a620d66510e42aa7fe3c50eb374a52f2e8","observation_id":"688262ff-7bf8-41a7-86a3-f9847558dbab","resolution":{"observed_at":"2026-08-15T17:45:01.230509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11870","last_updated":"2025-03-21T09:59:30Z","snapshot_observed_at":"2026-08-16T13:03:22.079664Z","submitted_at":"2024-11-03T21:18:07Z","title":"Designing Robust Quantum Neural Networks via Optimized Circuit Metrics","version":2},"cited_work":{"arxiv_id":"2411.11870","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.11870","snapshot_observed_at":"2026-08-15T17:45:01.038574Z","title":"Designing Robust Quantum Neural Networks via Optimized Circuit Metrics","venue":"quant-ph","work_id":"7c01fed0-9179-4991-9da8-0be4076fcf3b","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.649712Z"},"links":{"cited_paper":"/paper/2411.11870","citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:001f975fea52cdd0ca0bd3710617373b53f12a27bcab8216dc89c15cc5d2c873","observation_id":"39454b98-933f-42f6-9101-f8d284f21746","resolution":{"observed_at":"2026-08-15T17:45:01.046553Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:01.206934Z","title":"Designing robust quantum neural networks via optimized circuit metrics,","venue":null,"work_id":"e867f631-4f7c-4caa-8d21-00986031a358","year":2025},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.654908Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:cf2906e4414ff8ae8276949288dca782de439712c5a7d74e494a478eac4abec3","observation_id":"cde88e1b-62d6-4303-ae9a-2752a45c2fbb","resolution":{"observed_at":"2026-08-15T17:45:01.213254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:01.191149Z","title":"FedQNN: Federated learning using quantum neural networks,","venue":null,"work_id":"153b2a53-3e0b-48de-8f30-1d91e898e08c","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.659888Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:05479de12fd631be282cbd82159b6683fe518cb915af201ca89a95f9cd357065","observation_id":"7ee21c93-d529-4fdf-af51-fdbb2fdf518d","resolution":{"observed_at":"2026-08-15T17:45:01.195960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:00.668116Z","title":"MQFL-FHE: Multimodal quantum federated learn- ing framework with fully homomorphic encryption,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.668116Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:d0bbc9479e5dcc98e04402a9d656794bceb07e0e939e2ab12867263d65be2a55","observation_id":"e911e77c-14a2-499d-be77-404bb32fc4c8","resolution":{"observed_at":"2026-08-15T17:45:00.668116Z","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":"2026-08-15T17:45:01.173023Z","title":"Financial fraud detection: a comparative study of quantum machine learning models,","venue":null,"work_id":"44139890-57e1-4c25-bf8b-068aa78a4298","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.673580Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:d2bd07161e6a63d696810bf5a9ae0b8c822bb68a81ac86f6ff6753bb0a8b768e","observation_id":"306639f4-f641-4d35-9ddd-e845e6f4e26e","resolution":{"observed_at":"2026-08-15T17:45:01.178506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:00.678610Z","title":"Comparative performance analysis of quantum machine learning architectures for credit card fraud detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.678610Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:b275edc5812f834c3a4246b88cac8d94e4506a3702dc60318763095ca1c6ab04","observation_id":"7811899b-668a-4ff2-999f-aa462b8d580e","resolution":{"observed_at":"2026-08-15T17:45:00.678610Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02595","last_updated":"2025-07-13T04:24:08Z","snapshot_observed_at":"2026-08-19T19:41:23.520516Z","submitted_at":"2024-04-03T09:19:46Z","title":"QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detection","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02595","snapshot_observed_at":"2026-08-15T17:45:00.683239Z","title":"QFNN-FFD: Quantum federated neural network for financial fraud detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.683239Z"},"links":{"cited_paper":"/paper/2404.02595","citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:97e21b7e4198f8ff821eaad3d6af383758711ada6c5a81748dfd79f4d0fc94d2","observation_id":"1e3d80f8-ec6d-4a45-8929-021243cb8225","resolution":{"observed_at":"2026-08-15T17:45:00.683239Z","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":"2026-08-15T17:45:00.688713Z","title":"LEP-QNN: Loan eligibility prediction using quantum neural networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.688713Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:2e58eed6cd781b7aafce000186ef0fbc82f869c22bf803ca2be1327d4bbd4e78","observation_id":"2458a8dc-548b-4244-ad00-53277de4489c","resolution":{"observed_at":"2026-08-15T17:45:00.688713Z","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":"2026-08-15T17:45:01.155706Z","title":"Quantum state tomography using quantum machine learning,","venue":null,"work_id":"799d9897-f847-41ea-859d-8430496a6418","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.693399Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:055519a018cac71036dd1d5821a16d79950039a47e749fd225c7c0b1277f6558","observation_id":"c9ccf02d-9e60-4155-b5c6-a86ccc12be5d","resolution":{"observed_at":"2026-08-15T17:45:01.160696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:01.139924Z","title":"Mqml: Multi-omic quantum machine learning based cancer classification, biomarker identification in human lung adenocarcinoma,","venue":null,"work_id":"3a87b199-0052-464a-b37b-53da7a9cec41","year":2024},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.698616Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:f07e97815187757773b15ce6106af1eb04d9d0e90724e152570bf98a9c77d2d5","observation_id":"14aca403-52b0-4c51-b0a6-fd68f34d10ff","resolution":{"observed_at":"2026-08-15T17:45:01.145126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:01.123041Z","title":"QNN-VRCS: A quantum neural network for vehicle road cooperation systems,","venue":null,"work_id":"8d1c06a1-3de5-4c94-9590-7602fb79ed40","year":2025},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.703481Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:e05d43c992917c14ecbf71ba1fd4f03744d88ce2100c9a3e9261217875c39257","observation_id":"8f60bebb-1c78-4e9f-9af1-348cb0a44f09","resolution":{"observed_at":"2026-08-15T17:45:01.128564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-15T17:45:00.708043Z","title":"QUIET-SR: Quantum image enhancement transformer for single image super-resolution,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T17:45:00.708043Z"},"links":{"citing_paper":"/paper/2507.20537"},"observation_digest":"sha256:3286a4dc5a967bfba7595942556f442186699d1198efff4fde63ea0cede54825","observation_id":"60b0e1cb-f6d8-42e0-ad8c-619643aaf7e2","resolution":{"observed_at":"2026-08-15T17:45:00.708043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.20537","last_updated":"2025-07-28T05:43:02Z","latest_version":1,"primary_category":"quant-ph","snapshot_observed_at":"2026-08-19T19:42:07.630603Z","submitted_at":"2025-07-28T05:43:02Z","title":"Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":12},"total_outbound_references":31},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2507.20537."}