{"as_of":"2026-08-08T02:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0b0d191ec21864071870bd20419c2ea75cc1cce00c963113a79413383613978e","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T19:15:34.756343Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"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/2508.13005/citation-record","integrity":"/paper/2508.13005/integrity","json":"/paper/2508.13005/citation-record.json","paper":"/paper/2508.13005"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T19:15:31.713622Z","title":"Memory aware synapses: Learning what (not) to forget","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.713622Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:5dddb27012e4c82aaab7dee8fad1be4d082a968b0d3092af7011bb033d044d64","observation_id":"ac27ed92-a653-40d4-9396-223e66cce63e","resolution":{"observed_at":"2026-08-05T19:15:31.713622Z","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":"2026-08-05T19:15:31.721778Z","title":"Make continual learning stronger via c-flat","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.721778Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:7ee9287e84a31c4b803b1284f1886d88f8bc39b59ce23934ab1381a99c6bebad","observation_id":"6053a0f2-6646-447d-9c14-289cd446c137","resolution":{"observed_at":"2026-08-05T19:15:31.721778Z","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":"2026-08-05T19:15:31.730172Z","title":"Semi- supervised novelty detection.The Journal of Machine Learn- ing Research, 11:2973–3009, 2010","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.730172Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:88c72ee8fdcfde857757015809143f3f99f9d46a5574c54e405d1380f0ab4fe8","observation_id":"83b0ac65-1e94-4b16-839e-2a8a5d03253f","resolution":{"observed_at":"2026-08-05T19:15:31.730172Z","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":"2026-08-05T19:15:31.735711Z","title":"Dark experience for general continual learning: a strong, simple baseline","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.735711Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:97af84cf9d6e792e00a28926eb84c92a2e57d26a8fb8251c8a0c98a589e8e6f9","observation_id":"34acb235-0773-4e25-a8c6-51363fcac204","resolution":{"observed_at":"2026-08-05T19:15:31.735711Z","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":"2026-08-05T19:15:31.743307Z","title":"Open-set recognition with gaussian mixture variational autoencoders","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.743307Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:da70674c9ed469afd2547cd6f82b5efe144441ebf554ca9aa2827cb760fc90b2","observation_id":"7e6204ca-9863-4d4b-ac8c-dc642f2fdc17","resolution":{"observed_at":"2026-08-05T19:15:31.743307Z","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":"2026-08-05T19:15:31.752408Z","title":"On measuring the distance between histograms","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.752408Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:a11b6c1eaf1af7a4ab18d61cdbbc19468068623fd45d46e016a63f8a0c439958","observation_id":"5c9d892f-e85e-45e5-9426-a085bbae92c0","resolution":{"observed_at":"2026-08-05T19:15:31.752408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09958","last_updated":"2021-06-18T07:26:15Z","snapshot_observed_at":"2026-07-06T11:20:35.920607Z","submitted_at":"2021-06-18T07:26:15Z","title":"Novelty Detection via Contrastive Learning with Negative Data Augmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09958","snapshot_observed_at":"2026-08-05T19:15:31.766963Z","title":"Novelty de- tection via contrastive learning with negative data augmenta- tion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.766963Z"},"links":{"cited_paper":"/paper/2106.09958","citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:ebd415c277190dd0ac4e0a8d8739418d7aeeba5f27ca1d20ef4657f5141ec2f3","observation_id":"23bb8d77-ed16-41b7-8880-12d485bda701","resolution":{"observed_at":"2026-08-05T19:15:31.766963Z","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":"2026-08-05T19:15:31.775035Z","title":"Learning open set network with discriminative reciprocal points","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.775035Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:c926e56b666b573f0094e4db3f3658273774f1d146c6a19e36949263a3ed5d57","observation_id":"2063f6a4-d868-4c66-adf3-33a9eee897c3","resolution":{"observed_at":"2026-08-05T19:15:31.775035Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08207","last_updated":"2023-03-14T19:52:09Z","snapshot_observed_at":"2026-07-06T15:03:25.644795Z","submitted_at":"2023-03-14T19:52:09Z","title":"Is forgetting less a good inductive bias for forward transfer?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08207","snapshot_observed_at":"2026-08-05T19:15:31.786795Z","title":"Is forgetting less a good inductive bias for for- ward transfer? arXiv preprint arXiv:2303.08207, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.786795Z"},"links":{"cited_paper":"/paper/2303.08207","citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:7a2163bae788a9267cf4aed1afbe28e5add91f5af04c04f0b1965a6b31c7ab88","observation_id":"6dc50562-da45-4ec3-8893-c6d58b5c7797","resolution":{"observed_at":"2026-08-05T19:15:31.786795Z","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":"2026-08-05T19:15:31.807160Z","title":"Imagenet: A large-scale hierarchical im- age database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.807160Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:2df52d054a63528db46821d6eb5c2faa54452599caf071aa934e8ecf9f00be13","observation_id":"b2216ef0-cc0e-4328-8193-81a520bddcf4","resolution":{"observed_at":"2026-08-05T19:15:31.807160Z","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":"2026-08-05T19:15:31.839094Z","title":"Reducing network agnostophobia","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.839094Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:deb2d2063a3a4c57410c903ed58216dd10bccd47371c040d386d231ddf1d987d","observation_id":"2420c93c-5446-4dce-8a52-ba67db2ad804","resolution":{"observed_at":"2026-08-05T19:15:31.839094Z","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":"2026-08-05T19:15:31.844492Z","title":"Re- visiting deep ensemble for out-of-distribution detection: A loss landscape perspective","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.844492Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:6a67922f21d146a3423b709d2b71896903bbf64a81905a524ddd55930299f9c0","observation_id":"974f2f13-12c3-4fa0-9eda-6f54d9c2bd04","resolution":{"observed_at":"2026-08-05T19:15:31.844492Z","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":"2026-08-05T19:15:31.853966Z","title":"Gen- erative openmax for multi-class open set classification","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.853966Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:49ffb5e6fba0cb1ad4d5cf3d57a0de9d3581c6a13269ae0ec2d11cb43710afb8","observation_id":"8eccccf8-594e-48e7-b0b3-ec702fba8e3e","resolution":{"observed_at":"2026-08-05T19:15:31.853966Z","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":"2026-08-05T19:15:31.863135Z","title":"Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.863135Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:7d6f7bd2847b9f610df449a8037904221b01333dbc1743e41e4ed24e951c400a","observation_id":"58cd43b7-c19c-44f0-b5dc-632e43b104a3","resolution":{"observed_at":"2026-08-05T19:15:31.863135Z","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":"2026-08-05T19:15:31.876780Z","title":"Learning a neural- network-based representation for open set recognition","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.876780Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:7671a3ded16c4ddafa5e8de9bc6580f108881ca4e378a792ca1209bfd47ef3b0","observation_id":"c7d64894-8bb3-49cf-b61f-d88df431a02f","resolution":{"observed_at":"2026-08-05T19:15:31.876780Z","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":"2026-08-05T19:15:31.887044Z","title":"Learning a unified classifier incrementally via rebalancing","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.887044Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:cea08f8e69a47f5ee57b24087bd80af32f8323eeffe08d336da1a3518d7adf62","observation_id":"9f989af2-d131-4226-9973-3fabc1035774","resolution":{"observed_at":"2026-08-05T19:15:31.887044Z","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":"2026-08-05T19:15:31.967123Z","title":"Overcoming catastrophic forgetting for continual learning via model adaptation","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:31.967123Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:a7cc6b2423e942a2d28ebf0f8e9f7db61abf5e26be88f3515746df495ed1d64e","observation_id":"65c20935-d075-4de1-b281-bcca7d7ff7c1","resolution":{"observed_at":"2026-08-05T19:15:31.967123Z","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":"2026-08-05T19:15:32.125401Z","title":"Compacting, picking and growing for unforgetting continual learning.Ad- vances in neural information processing systems , 32, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.125401Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:b6cf0e7b54d167fc226c031b88fed97db874253608f8a5b4fe3a8d9317095639","observation_id":"30b42798-63d9-4457-a948-9040d20dbbe4","resolution":{"observed_at":"2026-08-05T19:15:32.125401Z","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":"2026-08-05T19:15:32.216495Z","title":"Class- incremental learning by knowledge distillation with adaptive feature consolidation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.216495Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:5a4965b10a8bd497b2b5713310e9a9f72aac83f8fd0d8c806bd09c37deadadff","observation_id":"f562e911-e054-4829-9fd6-9eabb53f6048","resolution":{"observed_at":"2026-08-05T19:15:32.216495Z","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":"2026-08-05T19:15:32.347090Z","title":"Large-scale video classification with convolutional neural networks","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.347090Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:2b3df5c2061b51561e7a0cd2ecbeec6b9cb5aa4ab0283182cbdd78ffb836ecd5","observation_id":"2684ecff-71bf-43dd-963a-6d685674f43b","resolution":{"observed_at":"2026-08-05T19:15:32.347090Z","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":"2026-08-05T19:15:32.439277Z","title":"Overcoming catastrophic forgetting in neu- ral networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.439277Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:71bd2217fd4b06a13247539dbc863c3c188a1ea584052937101f0adeaa8654dd","observation_id":"f59cc104-eeb8-484d-a9e9-d9560a955c40","resolution":{"observed_at":"2026-08-05T19:15:32.439277Z","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":"2026-08-05T19:15:32.449529Z","title":"Similarity of neural network represen- tations revisited","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.449529Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:7abd0ae51357210ee903a9a71aa48dd766082cc296d3081dfe80f92f40fcc8df","observation_id":"bfdd6082-6da8-475b-bcab-44da84cbfba3","resolution":{"observed_at":"2026-08-05T19:15:32.449529Z","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":"2026-08-05T19:15:32.475877Z","title":"A simple unified framework for detecting out-of-distribution samples and adversarial attacks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.475877Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:30f53547f09ce443452764843eab681b36db33f24c331eea18a8f05b02af14ac","observation_id":"86eae241-e3fd-4b53-838b-551341760df3","resolution":{"observed_at":"2026-08-05T19:15:32.475877Z","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":"2026-08-05T19:15:32.530055Z","title":"Applications of machine learning to machine fault diagnosis: A review and roadmap.Mechanical Systems and Signal Processing, 138:106587, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.530055Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:8aead749ad46f82e2dd3062534c5980790475376d010fab67e34e40cedbbbdb7","observation_id":"d4d39c2c-5a3d-4d41-9de5-41ce249b5e8c","resolution":{"observed_at":"2026-08-05T19:15:32.530055Z","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":"2026-08-05T19:15:32.618018Z","title":"Con- trastive continual learning with importance sampling and prototype-instance relation distillation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.618018Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:1ecb90fd39b00500d050a94b993ab13692ad61841191620b88a9fe4c18b69a95","observation_id":"5612c863-0ecd-4de3-b74c-21e1040ec7b3","resolution":{"observed_at":"2026-08-05T19:15:32.618018Z","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":"2026-08-05T19:15:32.696604Z","title":"Learn to grow: A continual structure learn- ing framework for overcoming catastrophic forgetting","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.696604Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:984acf4c8b14ca991cb307fe9cecd2e5456a5fd1057ab3343acc9b89a12dd3e2","observation_id":"7fb4aa18-a42a-4543-af60-bd3277cd52fe","resolution":{"observed_at":"2026-08-05T19:15:32.696604Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.02026","last_updated":"2022-11-07T18:45:18Z","snapshot_observed_at":"2026-08-04T16:12:31.164262Z","submitted_at":"2022-03-03T21:23:08Z","title":"Provable and Efficient Continual Representation Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.02026","snapshot_observed_at":"2026-08-05T19:15:32.795084Z","title":"Provable and efficient continual representation learn- ing","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.795084Z"},"links":{"cited_paper":"/paper/2203.02026","citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:c8c5cc25bdb84e3347c680560fb2a2cfe96d2503ab4d6b47b218a5bad839e47f","observation_id":"f07fe84f-d4dc-4314-9170-e39a8671b10f","resolution":{"observed_at":"2026-08-05T19:15:32.795084Z","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":"2026-08-05T19:15:32.860945Z","title":"Learning without forgetting","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.860945Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:35047ffff02ee37afb77ae49dcd489bd728c301d899bece1096c6f5410296440","observation_id":"b608b856-d9c4-49bb-b010-feab18a3b612","resolution":{"observed_at":"2026-08-05T19:15:32.860945Z","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":"2026-08-05T19:15:32.929986Z","title":"Few-shot open-set recognition using meta- learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.929986Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:b31089c599081906e194ace99559eea584559004d9763e888cb1ea31e169b876","observation_id":"bac1d0c8-3f29-4f96-9846-ddc1655702aa","resolution":{"observed_at":"2026-08-05T19:15:32.929986Z","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":"2026-08-05T19:15:32.987518Z","title":"Catastrophic inter- ference in connectionist networks: The sequential learning problem","venue":null,"work_id":null,"year":1989},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:32.987518Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:40fc5b7724b67bd68d149eac9474f9519e64952b3a8378066b020891953d9bed","observation_id":"d4973f6c-44d7-438d-87e6-798ca2b247ea","resolution":{"observed_at":"2026-08-05T19:15:32.987518Z","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":"2026-08-05T19:15:33.055849Z","title":"Class anchor clustering: A loss for distance- based open set recognition","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.055849Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:c9dbf49f838de179ae451013c8afcc9c338b1856bb751f479a50a227856ff078","observation_id":"22c4f889-ca1b-4f9c-ac9f-32b186d1c635","resolution":{"observed_at":"2026-08-05T19:15:33.055849Z","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":"2026-08-05T19:15:33.170327Z","title":"Open set learning with counterfac- tual images","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.170327Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:3b93febca3393df34c761055f6072b395bef4a7d111f508290359593b615faa0","observation_id":"830929ec-8477-4a67-aa6b-e59b482f9706","resolution":{"observed_at":"2026-08-05T19:15:33.170327Z","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":"2026-08-05T19:15:33.320018Z","title":"C2ae: Class conditioned auto-encoder for open-set recognition","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.320018Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:b2494d99e244597bb1c25df1eb965426133c7ed42b187bf7b7a6fa4290a24891","observation_id":"fefe1c77-3297-40fb-a0b7-cb2473502b15","resolution":{"observed_at":"2026-08-05T19:15:33.320018Z","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":"2026-08-05T19:15:33.439221Z","title":"Generative-discriminative feature representations for open-set recognition","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.439221Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:dd064802a7b9c74ce9614dd361190fb10d7215375c840a86d156c992b36d299b","observation_id":"f4a2b5a0-1472-4b20-92b6-c4dca41c26f5","resolution":{"observed_at":"2026-08-05T19:15:33.439221Z","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":"2026-08-05T19:15:33.534637Z","title":"A review of novelty detection","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.534637Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:e38b42d9a59b8e56bf2c7087f5f7ebb85fdb834546c50b0bd78d9e59e6a423c4","observation_id":"c9b53f35-e275-470d-a9d0-89c2513ee58c","resolution":{"observed_at":"2026-08-05T19:15:33.534637Z","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":"2026-08-05T19:15:33.604191Z","title":"icarl: Incremental classifier and representation learning","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.604191Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:3440a85f9b1477a790930a20921b8a50c2db942b531bcf268138e5057f1db657","observation_id":"b0db3ab7-0720-490f-9289-20808c165084","resolution":{"observed_at":"2026-08-05T19:15:33.604191Z","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":"2026-08-05T19:15:33.720137Z","title":"Overcoming catastrophic forgetting with hard attention to the task","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.720137Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:593bfe0b58ad3d729e4d3d0a72372f10886852e58e8cf3be7b8bb09d609ed0a1","observation_id":"39103b68-5dae-4686-a3bf-228b40113c77","resolution":{"observed_at":"2026-08-05T19:15:33.720137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.06917","last_updated":"2020-12-12T22:55:06Z","snapshot_observed_at":"2026-07-06T10:23:49.697086Z","submitted_at":"2020-12-12T22:55:06Z","title":"Assessing The Importance Of Colours For CNNs In Object Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.06917","snapshot_observed_at":"2026-08-05T19:15:33.764351Z","title":"As- sessing the importance of colours for cnns in object recogni- tion","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.764351Z"},"links":{"cited_paper":"/paper/2012.06917","citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:52a3f5dd288606f2b65857cdb7613e06eca71dbfc1a51e52b36286147fc79ebf","observation_id":"d3ff99ed-789b-4a47-a1a8-487758aaba94","resolution":{"observed_at":"2026-08-05T19:15:33.764351Z","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":"2026-08-05T19:15:33.847638Z","title":"Dice: Leveraging sparsification for out-of-distribution detection","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:33.847638Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:d4976b3b71dbb2a79c0861ab985410e128fe012a769a08cee0eb00ed85c0950d","observation_id":"8c8a2993-bc7b-49bf-9754-b62244c717ef","resolution":{"observed_at":"2026-08-05T19:15:33.847638Z","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":"2026-08-05T19:15:34.009544Z","title":"Ex- ploring diverse representations for open set recognition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:34.009544Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:feac28c28ee39adf0f2008ec0cd690d558edbe89f98b329a066c37b4ff9c7672","observation_id":"431fcf62-ce39-44b3-9e13-e2360b3d8380","resolution":{"observed_at":"2026-08-05T19:15:34.009544Z","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":"2026-08-05T19:15:34.136528Z","title":"Learning to prompt for con- tinual learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:34.136528Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:5be83427c230cf208f4c8226b1cfa6ab4bcc2b121d5cbbd806a30ebdba3dceb6","observation_id":"6cecf683-9941-4900-8af5-05a593c8f484","resolution":{"observed_at":"2026-08-05T19:15:34.136528Z","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":"2026-08-05T19:15:34.287543Z","title":"Openincre- ment: A unified framework for open set recognition and deep class-incremental learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:34.287543Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:93945b73189d1fc019656c14de3d101af94a38414994f276c5f634e8fb99f13a","observation_id":"67347c73-2450-45d6-bb15-61955621cc10","resolution":{"observed_at":"2026-08-05T19:15:34.287543Z","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":"2026-08-05T19:15:34.429083Z","title":"Convolutional prototype network for open set recognition","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:34.429083Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:4c595fd7945f49f7f01f2986b554f2270eed29cfe78a6cc4c6bd9c2b0e625d87","observation_id":"1e9be925-db1f-44a4-b081-43ab79ff7e74","resolution":{"observed_at":"2026-08-05T19:15:34.429083Z","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":"2026-08-05T19:15:34.548532Z","title":"Openood: Benchmarking generalized out-of-distribution detection","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:34.548532Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:4bc51fed5b7ca7930c21b13a5e71374f5bea23093be7ade484cc8dcff4f0dd78","observation_id":"9a3fb17a-0ff4-40eb-af8f-db08f36aea7a","resolution":{"observed_at":"2026-08-05T19:15:34.548532Z","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":"2026-08-05T19:15:34.648742Z","title":"Generalized out-of-distribution detection: A survey","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:34.648742Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:cbb9591fcc7bc699e0a63d514f73da836afe3ccb615c52b76de13a9a620b2394","observation_id":"ec4a5563-5f3a-43d6-910b-7210e2b20040","resolution":{"observed_at":"2026-08-05T19:15:34.648742Z","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":"2026-08-05T19:15:34.756343Z","title":"Classification- reconstruction learning for open-set recognition","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T19:15:34.756343Z"},"links":{"citing_paper":"/paper/2508.13005"},"observation_digest":"sha256:1e6616c1098e4ad7653539495193cfa608cb9bb1c8eec5e078a2a2330777ba82","observation_id":"1dfa7e1c-0273-4bf4-811b-3457607dac35","resolution":{"observed_at":"2026-08-05T19:15:34.756343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2508.13005","last_updated":"2025-08-18T15:25:06Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T19:15:31.406332Z","submitted_at":"2025-08-18T15:25:06Z","title":"Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":46,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":46},"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 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2508.13005."}