{"as_of":"2026-08-20T19:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b75e0651617d4ed22dca85033b76d2b502eaa5fdf9761096f227e04420191d16","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T08:43:46.408884Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2510.19475/citation-record","integrity":"/paper/2510.19475/integrity","json":"/paper/2510.19475/citation-record.json","paper":"/paper/2510.19475"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T08:43:42.624728Z","title":"In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (2018)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:42.624728Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:67e6ef09d6bd7d4017a96707f7783e71d2a08b9ee28a0c98199a6a5d713b4211","observation_id":"9d1bf6f3-8754-4650-b933-174162d0a441","resolution":{"observed_at":"2026-08-04T08:43:42.624728Z","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":"2026-08-04T08:43:42.697258Z","title":"Journal of Visual Communication and Image Representation76, 103055 (2021) https://doi.org/10.1016/j.jvcir.2021.103055","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:42.697258Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:79f214617cc26183a7df7e444775bdb38a740b2ed3b9981f4f90da5858a7598d","observation_id":"199450db-d9d2-4628-8c8a-c3b9eb050aaa","resolution":{"observed_at":"2026-08-04T08:43:42.697258Z","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":"2026-08-04T08:43:42.802962Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:42.802962Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:dd962103e6b6f3b3caf9b6c801260d2ec55f86a8e5d1c37d870a2122ef1ccfa8","observation_id":"d4d9a24f-e7db-4b1c-a3e3-ae99694ee292","resolution":{"observed_at":"2026-08-04T08:43:42.802962Z","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":"2026-08-04T08:43:42.910598Z","title":"IEEE Transactions on Industrial Informatics 18(10), 7107–7117 (2022) https://doi.org/10.1109/tii.2022.3143605","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:42.910598Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:dd4998caad88e55f550029a498f3ca69a20743b14194b6a4f4e27a267942a232","observation_id":"9dacb69e-9791-4e05-80fd-82c93cb81ff3","resolution":{"observed_at":"2026-08-04T08:43:42.910598Z","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":"2026-08-04T08:43:43.018817Z","title":"Neurocomputing596, 128049 (2024) https://doi.org/ 10.1016/j.neucom.2024.128049","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.018817Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:64573f5b3aea808e713a029a62a15ade9740a3fa4254d190f1f4d6531e0e25a5","observation_id":"692a4d19-2c60-481d-8739-c8883ce8b68f","resolution":{"observed_at":"2026-08-04T08:43:43.018817Z","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":"2026-08-04T08:43:43.131442Z","title":"IEEE Transactions on Visualization and Computer Graphics 22(12), 2633–2651 (2016) https://doi.org/10.1109/tvcg.2015.2513408","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.131442Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:f3ec56500d62fff7a1d1a6c68b89ef254401db8f9ae8ccf580a76c2a24410414","observation_id":"77277491-e290-4f23-bd5a-4122a81b1f3d","resolution":{"observed_at":"2026-08-04T08:43:43.131442Z","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":"10.1186/s12877-024-05188-7","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"BMC Geriatrics 24(1) (2024) https://doi.org/10.1186/s12877-024-05188-7","venue":"BMC Geriatrics","work_id":"abfbcd92-49d7-40b1-a5ec-30550219a7ac","year":2024},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.207633Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:243d42d3cecb1dfdd023fc832cb3b90dd6a27242e7370e41efcb8f84d10092ac","observation_id":"a0199c16-8758-4b92-aa78-ec1478ba3434","resolution":{"observed_at":"2026-08-04T08:48:31.113796Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-04T08:43:43.277940Z","title":"Frontiers in Computer Science5 (2023) https://doi.org/10.3389/fcomp.2023.1153160","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.277940Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:196eca3ee1726ca6539f8e667b6e75fcad95feb5fd8918016359fbfcc34dfc5f","observation_id":"abdf18e7-1f63-4de4-b8da-3fe9f6a8f97c","resolution":{"observed_at":"2026-08-04T08:43:43.277940Z","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":"2026-08-04T08:43:43.385921Z","title":"5935–5946 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.385921Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:001821dfe8d0aa2e7dd18360556343ba32a750fe214767048009712b7872e06b","observation_id":"a4302b22-4d6f-4e55-b581-d7881036177d","resolution":{"observed_at":"2026-08-04T08:43:43.385921Z","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":"10.1007/s12283-024-00460-w","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Sports Engineering27(1) (2024) https://doi.org/10.1007/s12283-024-00460-w","venue":"Sports Engineering","work_id":"a31592e7-e167-4bea-815f-54b1a49d4be4","year":2024},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.485719Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:e75b9e4bb26eada7b0cc1ba4ff0737ec9b980ae5248e93eede53bc01f7f840a5","observation_id":"9c87f5a2-2321-4b09-881f-c28f668016e0","resolution":{"observed_at":"2026-08-04T08:48:30.936597Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-04T08:43:43.578291Z","title":"In: European Conference on Computer Vision, pp","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.578291Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:b45dc4fec65ae5a80d45ebd083b635b37240beea5ea77c7c4c4bcd9b67e5f71c","observation_id":"9d1dfe48-d118-40b1-9be0-f0c6df4fd406","resolution":{"observed_at":"2026-08-04T08:43:43.578291Z","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":"2026-08-04T08:43:43.687688Z","title":"In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.687688Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:9106d237f78b7d8a7bb955c5e63ecf49851cd18d58be050d6613ebc6dddac688","observation_id":"fe932921-5571-4fc7-b990-cd360e3f9e77","resolution":{"observed_at":"2026-08-04T08:43:43.687688Z","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":"2026-08-04T08:43:43.805962Z","title":"In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.805962Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:7ee896e08ed0aa68b91cfb7f29b944859ef50f9b154a0baca1857a5f1d8953de","observation_id":"ccf187cf-8ab7-4dba-82c8-40a2447e0f4b","resolution":{"observed_at":"2026-08-04T08:43:43.805962Z","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":"2026-08-04T08:43:43.859979Z","title":"In: 2017 IEEE International Conference on Com- puter Vision (ICCV), pp","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.859979Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:4ad6305df706efa889f06f31534013360df1c4a19fba06489f6aabbba8e1b17c","observation_id":"4415c11b-352f-4fda-bb82-1442ba653351","resolution":{"observed_at":"2026-08-04T08:43:43.859979Z","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":"2026-08-04T08:43:43.948538Z","title":"In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:43.948538Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:fe4e6780583ff4196fa33f924e6cae38181a2ea2469726906bcc93db40edcf9b","observation_id":"c240f967-4bd6-4fdd-b729-ed11ea73b611","resolution":{"observed_at":"2026-08-04T08:43:43.948538Z","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":"2026-08-04T08:43:44.030306Z","title":"In: 2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (A VSS), pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.030306Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:f18e46eeb8060f692dd410a12adf0a40c4799c7d85fdf83d0791f8c208041df7","observation_id":"2f491935-af17-4040-a8c3-ee2e0d05cc44","resolution":{"observed_at":"2026-08-04T08:43:44.030306Z","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":"2026-08-04T08:43:44.124924Z","title":"In: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.124924Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:fd9940c9471fc366b8ee070b234a2742909307a6dc4d0bf5ffa78292152ed9af","observation_id":"6e121e3d-0fef-43b9-a7b3-cd29866ed583","resolution":{"observed_at":"2026-08-04T08:43:44.124924Z","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":"2026-08-04T08:43:44.236771Z","title":"In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.236771Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:4c6edb4e7a980b225e536f3753d83af928263b3144a664b6de781c753305fd48","observation_id":"8d3eb156-17dc-4878-ae09-8572d5b15837","resolution":{"observed_at":"2026-08-04T08:43:44.236771Z","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":"2026-08-04T08:43:44.329727Z","title":"In: 2023 IEEE/CVF International Conference on Com- puter Vision (ICCV), pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.329727Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:933e12626617dedaaa9e98ab3390af1c48c9f13fda5acd4948cbe1fed4ecf697","observation_id":"c6b99f97-e0fb-40b9-93c5-31f6a8b1455c","resolution":{"observed_at":"2026-08-04T08:43:44.329727Z","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":"2026-08-04T08:43:44.428542Z","title":"In: Advances in Neural Information Processing Systems, vol","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.428542Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:0d89ea7354dec25b4d8708d3a9611757421e7178b7117232b7f364ce003ffa20","observation_id":"af12e8c3-dd6e-47b5-9638-3f444555c1a8","resolution":{"observed_at":"2026-08-04T08:43:44.428542Z","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":"2026-08-04T08:43:44.577550Z","title":"In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.577550Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:8821f0a3efa3490fef8c3b3fc964a016b59f49773003ebe929e4fc863d578ef2","observation_id":"3cbd069a-0dad-4c59-8b94-89cae66eabc4","resolution":{"observed_at":"2026-08-04T08:43:44.577550Z","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":"2026-08-04T08:43:44.698114Z","title":"In: 2023 IEEE/CVF International Conference on Computer Vision (ICCV), pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.698114Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:b12bcd36cf1590f174e726c8bc5e006c4100b2c1be8893f80860117ffec3924b","observation_id":"cf7087d3-c019-48cb-99e7-25b1fe3bcf9c","resolution":{"observed_at":"2026-08-04T08:43:44.698114Z","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":"2026-08-04T08:43:44.835332Z","title":"In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.835332Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:f1f7db927ebc28cbabb72474ea8b20b8e98671520a8fdad41badf31da5425cda","observation_id":"c7828236-e0fa-4c70-b1a6-b047a189c2d8","resolution":{"observed_at":"2026-08-04T08:43:44.835332Z","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":"2026-08-04T08:43:44.929773Z","title":"IEEE Transactions on Circuits and Systems for Video Technology32(1), 198–209 (2022) https://doi","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:44.929773Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:46bf56695f6e97593261cf3cf82d38243a793f05f663ffd949497ebf67074c23","observation_id":"1714bf54-62db-4b82-bf59-97bdb961a339","resolution":{"observed_at":"2026-08-04T08:43:44.929773Z","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":"2026-08-04T08:43:45.135155Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence39(5), 5478–5486 (2025) https://doi.org/10","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.135155Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:3db47a63e3ee70c330637c4550d43317c169b8cc11ebff68a6450593ed5353bd","observation_id":"2a4f1645-963a-4e97-848a-6554108a35a8","resolution":{"observed_at":"2026-08-04T08:43:45.135155Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.00396","last_updated":"2022-08-05T17:54:38Z","snapshot_observed_at":"2026-08-14T01:02:41.198730Z","submitted_at":"2021-10-31T03:32:18Z","title":"Efficiently Modeling Long Sequences with Structured State Spaces","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.00396","snapshot_observed_at":"2026-08-04T08:43:45.275439Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.275439Z"},"links":{"cited_paper":"/paper/2111.00396","citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:58ef84b264d247edfe8be2062d3df7b9c5925cfffb35626d595693ed9ebfee89","observation_id":"8ba79779-8049-4018-a0a6-bd39af64080a","resolution":{"observed_at":"2026-08-04T08:43:45.275439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-08-17T20:47:46.242385Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-08-04T08:43:45.418654Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.418654Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:3112b08607b0a75f861f15bc49d060bb5b9bfa4b42bb7bfffba6928b62e83d40","observation_id":"dc7a7eec-bf0c-45e0-a53a-39cccb622970","resolution":{"observed_at":"2026-08-04T08:43:45.418654Z","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":"2026-08-04T08:43:45.511310Z","title":"In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.511310Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:5648decae11face6ec0fb52ee9553b0986fc79370dfa08c92150ce2c767f4538","observation_id":"d39ced55-f7a9-4e64-8f8d-388eb683be76","resolution":{"observed_at":"2026-08-04T08:43:45.511310Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-04T08:43:45.571729Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence39(10), 10248–10256 (2025) https://doi.org/10.1609/aaai.v39i10.33112","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.571729Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:77b1f64200d72512418e12c0a6797d7ca5f889a0fda881114d1a71c59e69ab19","observation_id":"d1937381-995d-41c0-adf2-9adacc86eb91","resolution":{"observed_at":"2026-08-04T08:43:45.571729Z","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":"2026-08-04T08:43:45.660570Z","title":"Nature Neuroscience5(11), 1226–1235 (2002) https://doi.org/10.1038/ nn963","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.660570Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:fd1182d1d543e1964fdbb947fdea17e46207aecdf0c8675c94b758e2932775ab","observation_id":"68efd07f-2429-4b18-ae6f-576744596359","resolution":{"observed_at":"2026-08-04T08:43:45.660570Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-04T08:43:45.780640Z","title":"In: 2021 IEEE/CVF International Conference on Computer Vision (ICCV), pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.780640Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:e5d908b7d3da23741ce0217c07e06e9bca3f23d37030b49beb9684d3d5200307","observation_id":"3b457849-74b1-4fa6-ae62-09d9e3a95c72","resolution":{"observed_at":"2026-08-04T08:43:45.780640Z","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":"2026-08-04T08:43:45.855503Z","title":"In: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (W ACV) (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.855503Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:b9d450539fa3d36f5176a199efd58513f899efae1007765b313652763f8a5011","observation_id":"425e8795-a96b-4bf9-9e27-5e38285e6ee5","resolution":{"observed_at":"2026-08-04T08:43:45.855503Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1410.3916","last_updated":"2015-11-29T07:00:41Z","snapshot_observed_at":"2026-08-18T21:39:55.063245Z","submitted_at":"2014-10-15T03:13:18Z","title":"Memory Networks","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1410.3916","snapshot_observed_at":"2026-08-04T08:43:45.941766Z","title":"48550/ARXIV.1410.3916 [cs.AI]","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:45.941766Z"},"links":{"cited_paper":"/paper/1410.3916","citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:030d56b33103203a39ee111f5dc67db1b56a4266541302972a8409601a24411b","observation_id":"3a3a01a9-2c00-4b4c-957e-a68877bdfc0b","resolution":{"observed_at":"2026-08-04T08:43:45.941766Z","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":"10.1016/s0364-0213(85","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T08:48:30.648394Z","title":"Cognitive Science9(1), 75–112 (1985) https://doi.org/10.1016/s0364-0213(85) 80010-0","venue":null,"work_id":"6705f752-3367-44b8-8365-b7b46ceb90fb","year":1985},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:46.053434Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:d048e809a06a37d67c872ff50943b872af5de41cf28105938df0875ef0d2c3ba","observation_id":"9abf11e8-177b-495c-a950-61cd153eb9af","resolution":{"observed_at":"2026-08-04T08:48:30.755790Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-04T08:43:46.162614Z","title":"IEEE Transactions on Pattern Analysis and Machine Intelligence36(7), 1325– 1339 (2014) https://doi.org/10.1109/tpami.2013.248","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:46.162614Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:85878baa2a3f1e74838a2ee53ed835534a695194409b18dcc483a2351f14837e","observation_id":"d273f4d4-33f5-4c1c-a9e4-11bd9cd9ee31","resolution":{"observed_at":"2026-08-04T08:43:46.162614Z","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":"2026-08-04T08:43:46.253424Z","title":"In: 2017 International Conference on 3D Vision (3DV) (2017)","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:46.253424Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:4aef0e2b1cbd534537fbe13bf1e4403934c636f8e806ebe877436842faa8c25e","observation_id":"01582e71-b725-44bb-8a3c-a4d4dde1ece1","resolution":{"observed_at":"2026-08-04T08:43:46.253424Z","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":"2026-08-04T08:43:46.303243Z","title":"614–631 (2018)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:46.303243Z"},"links":{"citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:053a442a0f757bbdd9567baae5d318e34d61f0e15af7345ee46ed1f5fcbee15e","observation_id":"f14238ae-5668-40af-837a-ffcb0a6063a3","resolution":{"observed_at":"2026-08-04T08:43:46.303243Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.06638","last_updated":"2025-04-09T07:28:19Z","snapshot_observed_at":"2026-08-16T12:42:47.765064Z","submitted_at":"2025-04-09T07:28:19Z","title":"HGMamba: Enhancing 3D Human Pose Estimation with a HyperGCN-Mamba Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.06638","snapshot_observed_at":"2026-08-04T08:43:46.408884Z","title":"degree in com- puter science at Wenzhou University","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-04T08:43:46.408884Z"},"links":{"cited_paper":"/paper/2504.06638","citing_paper":"/paper/2510.19475"},"observation_digest":"sha256:2369f62c80bd6f8e5a5815ab351f69d137b86086f427f624cc1c70441de0db5b","observation_id":"299888d5-bc29-468a-b28e-597326c69875","resolution":{"observed_at":"2026-08-04T08:43:46.408884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2510.19475","last_updated":"2026-07-08T16:28:44Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T12:35:25.256739Z","submitted_at":"2025-10-22T11:12:07Z","title":"PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":38},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2510.19475."}