{"as_of":"2026-08-09T23:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a25b879fc693f6ce83860613e706b37dbb26682bfd1edc0ebc075bc6e9c57ad7","coverage":[{"denominator":69,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":69,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T11:04:57.359901Z","state":"measured"},{"denominator":69,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":69,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2608.05552/citation-record","integrity":"/paper/2608.05552/integrity","json":"/paper/2608.05552/citation-record.json","paper":"/paper/2608.05552"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.997625Z","title":null,"venue":null,"work_id":"22d6d49f-d22b-4330-b258-45ac0f3af029","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.137579Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:b5e0d50bfb9a38aaee6f1cc4660c815afdc44e60ce1ebb62439c7da9871e59d5","observation_id":"00d9f466-6177-431a-81b3-258eb5c5eff2","resolution":{"observed_at":"2026-08-08T11:04:58.000938Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.989163Z","title":"Jaakkola","venue":null,"work_id":"51acb97a-981b-4e66-8f99-9a59fa37d0d9","year":2018},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.141541Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:032ff8f0180601b98d29e934ec5f9aad96e45b2e3b1f9efab6e2ac3b47089f23","observation_id":"739b34d2-6d80-4405-a99b-a01ddc202e04","resolution":{"observed_at":"2026-08-08T11:04:57.992243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.980515Z","title":"Tabnet: Attentive interpretable tabular learning","venue":null,"work_id":"6d4ff172-5c96-4cb0-928d-c01535ebced6","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.144403Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:9d2c8105d5d47eeb4791aa0eca9d4fa42dc0b92d4981e0be0a11525b3fcf5a80","observation_id":"b3d5c040-4a45-49e2-9893-dd8541222cce","resolution":{"observed_at":"2026-08-08T11:04:57.983744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.971486Z","title":"Sok: Modeling explainability in security analytics for interpretability, trustworthiness, and usability","venue":null,"work_id":"58d1b9f6-fee7-453b-8d24-455908198fff","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.147535Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:9cf0e3af8a4be9b6d02041e945a7e975fb622092cdc186a86e791261c5246823","observation_id":"15206d76-b7f5-46be-99e4-2a896140b707","resolution":{"observed_at":"2026-08-08T11:04:57.974899Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.963943Z","title":null,"venue":null,"work_id":"aabf14ad-70fe-4fb5-aefe-266c8b996023","year":1990},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.150533Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:89690f623c1ad8df66cfc2d2030c65aaeed15b5d1e5d543dd03cd91f42dd32ab","observation_id":"ae78fd78-0a7b-4877-998d-97afd866e3b8","resolution":{"observed_at":"2026-08-08T11:04:57.966427Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.955659Z","title":"This looks like that: Deep learning for interpretable image recognition","venue":null,"work_id":"20fc40f2-a310-4811-827d-fd381d53f143","year":2019},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.153400Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:a5fe7e24777f6a021cc59d3b277ea319edeb45dfcfb9764ea0099264a11a152e","observation_id":"d36e5572-edc8-4b53-92f1-c7c698e20ac5","resolution":{"observed_at":"2026-08-08T11:04:57.958926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.947045Z","title":"Yong, and Wei King Tiong","venue":null,"work_id":"5bdc1e56-7dcb-4357-83db-6f5130f88ddf","year":2019},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.156357Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:ab32a7532003ae05926f77132439afe11ee60e6b25409b29f47d946082781662","observation_id":"6f87f671-163c-4239-9914-efc5e01a92c6","resolution":{"observed_at":"2026-08-08T11:04:57.950052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.938266Z","title":"Explanations can be manipulated and geometry is to blame","venue":null,"work_id":"20662e71-1a9d-4b05-9332-68ec8e9d0c58","year":2019},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.158900Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:686b4a361ae871f84bb83ed123aa0e02097b2ddbab703b79836e02024c20ab24","observation_id":"2c51dbc1-2aab-41f3-a4a4-c5876544eb30","resolution":{"observed_at":"2026-08-08T11:04:57.941538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.928979Z","title":"Concept embedding models: Beyond the accuracy-explainability trade-off.Advances in Neural Information Processing Systems, 2022","venue":null,"work_id":"ea11d970-ba18-436d-8699-39291b478c39","year":2022},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.161342Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:b2a582a01916f28296bc1b79a47dc8657275c4f6a75c0e1b1a786dd47fef1855","observation_id":"5ea5965f-3a0e-496f-9a05-5005cf39c9e2","resolution":{"observed_at":"2026-08-08T11:04:57.932476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.919961Z","title":"Tabcbm: Concept-based interpretable neural networks for tabu- lar data.Transactions on Machine Learning Research, 2023","venue":null,"work_id":"a41bd208-782c-4fe7-aacb-0ac5d84310c0","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.163928Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:2f14dd89770c29a36d07656feb518fbab4c4a1f8aeb9a67f289967876dd3df69","observation_id":"4dc5c7c6-3d7d-4b89-be63-c71d9741e713","resolution":{"observed_at":"2026-08-08T11:04:57.923255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.910975Z","title":"A lightweight, efficient and explainable-by-design convo- lutional neural network for internet traffic classification","venue":null,"work_id":"533aa46f-5b9e-4ec8-80d9-7f25263568fa","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.166310Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:7aeee5f9faee1a1c8baa9c7304f67d7009ad6afddfbb3adaeeaf21fa7ab47053","observation_id":"5e02ad89-5e11-4099-ab73-e91a43719caa","resolution":{"observed_at":"2026-08-08T11:04:57.914232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.902291Z","title":"Fong and Andrea Vedaldi","venue":null,"work_id":"86acb388-a7e1-467e-b9c4-e68f55e97b28","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.169657Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:49d391505ba0d7313b6956263decb5b28ff87688852875da96f879159e64d38c","observation_id":"6c574f55-0f78-4f8b-aa9b-88ecadf82d4f","resolution":{"observed_at":"2026-08-08T11:04:57.905346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6572","last_updated":"2015-03-20T20:19:16Z","snapshot_observed_at":"2026-07-06T04:04:16.777653Z","submitted_at":"2014-12-20T01:17:12Z","title":"Explaining and Harnessing Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6572","snapshot_observed_at":"2026-08-08T11:04:57.173103Z","title":"Goodfellow, Jonathon Shlens, and Christian Szegedy","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.173103Z"},"links":{"cited_paper":"/paper/1412.6572","citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:1cbfb1d9b151569aac410f45a865fed5470292b729aeab2396b32de53400f6b9","observation_id":"1adc5231-5ff0-4a44-b045-40257d4d81e3","resolution":{"observed_at":"2026-08-08T11:04:57.173103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.893419Z","title":"right to explanation","venue":null,"work_id":"13f11310-6cab-4943-a8ce-0f4bba078b78","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.177483Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:41b214ca64bd09b8a786f83181e7f69c2b7f5c41420f4a355c6d6b90bf6afc87","observation_id":"c5ce1013-fce5-44e8-9f12-7d7bc6b5d4c2","resolution":{"observed_at":"2026-08-08T11:04:57.896458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.884115Z","title":null,"venue":null,"work_id":"809eadbc-d7c9-4f6c-9b41-c96ad705ff92","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.181006Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:d311cf3649e1ac67c6ca1681d1d35f3067ae5d1b818d015f0ea96a1ba856c202","observation_id":"fa8396ff-280e-4cad-8b39-52458556f8ab","resolution":{"observed_at":"2026-08-08T11:04:57.887475Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.874194Z","title":"Lemna: Explaining deep learn- ing based security applications","venue":null,"work_id":"db205538-281b-4b73-85aa-45ae0cef3888","year":2018},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.184563Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:9e7fa978a880e05e27e86fd1758c384f2a000b3382b0a9a4559ed651970256de","observation_id":"735fb763-c1a9-4e0f-8aa0-61672e9bea7a","resolution":{"observed_at":"2026-08-08T11:04:57.877685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.864814Z","title":"Lemna: Explaining deep learn- ing based security applications","venue":null,"work_id":"45a3b56e-8174-4632-8531-d226f6194aa9","year":2018},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.188014Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:11b191582390c60481664cca1acaea0588f742767a615fcd8e8f1fad980fb600","observation_id":"10089961-7ee4-4179-b022-0758c30f42b2","resolution":{"observed_at":"2026-08-08T11:04:57.868183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.855937Z","title":"Evaluation and improvement of interpretability for self- explainable part-prototype networks","venue":null,"work_id":"e9bdd237-3c0b-41fd-9b06-e1a85bf285d6","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.191203Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:8ab8acd8c3bca997aa870bc32bb3b1fb565aaa649a8ff8229491464bbef812b0","observation_id":"2327929a-5851-4f45-a456-cef62713b08d","resolution":{"observed_at":"2026-08-08T11:04:57.858867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.847850Z","title":"An interpretable prototype parts-based neural network for medical tabular data","venue":null,"work_id":"37277db4-1a62-49d9-9f49-fe613bf3a64c","year":2025},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.194499Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:5e4b49467a8ba503fbee2026586176070a6d6365dbbdb7f79c5cf6b41ac88266","observation_id":"a0444606-f7b6-4a30-a86b-a890f4eeae63","resolution":{"observed_at":"2026-08-08T11:04:57.850623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.839626Z","title":"Protogate: Prototype-based neural networks with global-to-local feature selection for tab- ular biomedical data","venue":null,"work_id":"18711690-b110-452f-96a7-cdd21390e42b","year":2024},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.197802Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:ac556d562ec331d6966caed1877cc42bd013ce1dc71c15fd5bbcb7d9275546a7","observation_id":"f84ce080-6098-4dc0-981d-d340462fb653","resolution":{"observed_at":"2026-08-08T11:04:57.842536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T11:04:57.201149Z","title":"Kingma and Jimmy Ba","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.201149Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:d5edc0268f420b5e5bcd1403237814ccdf08923d6e82b6eb91eaa629d5cc3b90","observation_id":"ca036de8-4bab-4933-b4cb-c5a4f6143366","resolution":{"observed_at":"2026-08-08T11:04:57.201149Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.825416Z","title":"Pantypes: Diverse representatives for self- explainable models","venue":null,"work_id":"61a2bd88-8725-4a4c-aba4-991ed4501b11","year":2024},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.205108Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:a628a4d623bca9cc174042528ed54398299d2b2f5502b46d25b203ddedc18a28","observation_id":"a6c890a2-0639-45bf-9bf0-d99cf8516fa7","resolution":{"observed_at":"2026-08-08T11:04:57.828377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.816164Z","title":"Concept bottleneck models","venue":null,"work_id":"bb0f8c85-bdc5-4e8c-b4f0-7a44c14b8936","year":2020},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.208459Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:f1559508cd476c7e67a7fd985fcacca53226fa478e3377d79b469aabe1988fc1","observation_id":"83c477e6-2f5c-4796-ab2a-e6d8dcbc85f6","resolution":{"observed_at":"2026-08-08T11:04:57.819381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.806554Z","title":"Howard, Wayne Hubbard, and Lawrence Jackel","venue":null,"work_id":"37e1ed12-b1ff-4f5a-a24f-2975d207906f","year":1989},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.211706Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:29b2e004e5fe1a37ea1196bdc2da0a77d26e876f95927c4625ef1a1ef6eaa078","observation_id":"b3e34a3e-c5e0-4821-b2e3-57bbe9f5f92e","resolution":{"observed_at":"2026-08-08T11:04:57.809792Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.797341Z","title":"Deep learning for case-based reasoning through proto- types: A neural network that explains its predictions","venue":null,"work_id":"dca2320d-ff32-48a9-bd9b-5745dbab56bb","year":2018},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.214947Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:13945875413c0ed4129b75b4caad7631e9611acd10a1a3706c28e7eabc0566ec","observation_id":"57e25502-8b2e-4028-baae-1d3caa09edf9","resolution":{"observed_at":"2026-08-08T11:04:57.800726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.788125Z","title":"Shap: Shapley addi- tive explanations","venue":null,"work_id":"4e43c399-033f-4328-826e-b7acfe1cf992","year":null},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.218311Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:bd302138bd20a8ff7f838552f98090ea57c73c528b79cfa406f62ede76814453","observation_id":"6e4e9184-08f7-4b34-b6da-6c236542d44f","resolution":{"observed_at":"2026-08-08T11:04:57.791591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.769938Z","title":"Lundberg and Su-In Lee","venue":null,"work_id":"dc2c00dd-89c7-462c-b114-330f40ef543d","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.225375Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:49fb16b2073a740a63f6e119f6a523307b23a38c081637612b38d11538946350","observation_id":"a3822c64-7e06-47b4-8ef2-25ebf407c3e4","resolution":{"observed_at":"2026-08-08T11:04:57.773146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T11:04:57.228879Z","title":"Towards deep learning models resistant to adversarial attacks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.228879Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:57c92de287ac37a2f41b0adfdbd973b0b94016a5f8ece6a6cd8ebe6c1c143f48","observation_id":"952491c4-c67d-44e0-8558-87001033e28d","resolution":{"observed_at":"2026-08-08T11:04:57.228879Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.755706Z","title":"Explainable artificial intelligence: a compre- hensive review.Artificial Intelligence Review, 2022","venue":null,"work_id":"acd8132d-5e52-4dc0-9e8b-a3672f3f32a7","year":2022},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.232371Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:8edfc6c5073cb990f562e1660b91c85cbda07c041b9446584e9f164cb39eaec5","observation_id":"d8c6c8a3-3ec6-4624-92cc-5e3be4c0c541","resolution":{"observed_at":"2026-08-08T11:04:57.758876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.746822Z","title":"Security is not my field, i’m a stats guy: A qualitative root cause analysis of barriers to adversarial machine learning defenses in industry","venue":null,"work_id":"671e2e29-c7f9-4831-a330-5f745dc7eb00","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.235852Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:29718cf7a0bc8cd18fe8920140a7f76b46e1f40eaa54b5629058b3ffd494fb8b","observation_id":"c63ef1d1-4155-483d-a9f2-5468d62d36e1","resolution":{"observed_at":"2026-08-08T11:04:57.750059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.737888Z","title":"Big data analytics for intrusion detection system: Statistical decision-making using finite dirichlet mixture models","venue":null,"work_id":"00dc8f3f-b133-49f9-9229-0eb38c653070","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.239133Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:55d386ad274504183919be4194c6da29df1de81fb0390306e72a4edcd8e38739","observation_id":"43f7ae8e-b2a7-433a-ab2b-d9a240ee789c","resolution":{"observed_at":"2026-08-08T11:04:57.741259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.728928Z","title":"Unsw-nb15: a compre- hensive dataset for network intrusion detection systems (unsw-nb15 network dataset)","venue":null,"work_id":"4b94f3a5-f22e-442f-89d8-08f5f56a36c1","year":2015},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.242480Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:b7665a4795c574d7e2efe3d204e8642098b63719dc246b7c68c6db7a7ad684f7","observation_id":"99fe45f9-ddac-40ff-b381-a7e2b781de42","resolution":{"observed_at":"2026-08-08T11:04:57.732243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.720755Z","title":"The evaluation of network anomaly detection systems: Statistical analysis of the unsw-nb15 dataset and the comparison with the kdd99 dataset","venue":null,"work_id":"c0c2ced0-9718-4d2d-8d65-86f7e4b19219","year":2016},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.245923Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:4e05c250d8665fffc8fd0a5a49a4c85a7ad79fcb28cb478e3c1a33b2f895dbb3","observation_id":"e411adf2-cbcf-4e36-801c-def0da8ea2c3","resolution":{"observed_at":"2026-08-08T11:04:57.723840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.713092Z","title":"Novel geometric area analysis technique for anomaly detec- tion using trapezoidal area estimation on large-scale networks","venue":null,"work_id":"d54a59ae-f3b7-45aa-b77f-c6e765e46be4","year":2019},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.249187Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:b5566fe9711d79d2f450ce1ba3817d5661788013b4cd15bf5cec4dd5901ef5bf","observation_id":"e3d364f4-f1df-465d-a57d-2685392547a8","resolution":{"observed_at":"2026-08-08T11:04:57.715852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.705224Z","title":"Neu- ral prototype trees for interpretable fine-grained image recognition","venue":null,"work_id":"3797dc30-9188-4585-92a5-66ca824212f9","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.252434Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:d1dfcfca3fde4eefb5fb6dd00b63d205cb768d70f1f1ed3fa7040d95cfaebde9","observation_id":"fe83c16a-d97a-4b0e-887d-46f5dbc568fb","resolution":{"observed_at":"2026-08-08T11:04:57.708135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.696218Z","title":"Pytorch: an imperative style, high-performance deep learning library","venue":null,"work_id":"bed9c837-fb7c-43f8-8efb-a67e64b9d594","year":2019},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.255870Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:f24a9bc99b872c8bf83202bb9ce6a1d37986d28dca0025070a974ffbae24cbf7","observation_id":"0e602415-2040-4b27-9de5-050ea975b3b7","resolution":{"observed_at":"2026-08-08T11:04:57.699609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.687426Z","title":"Captum: Model in- terpretability for pytorch","venue":null,"work_id":"9dccb6ea-4682-4f57-9a7d-0f1525feeef5","year":2019},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.258627Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:aef167f60e5475bf2066b32be372b8e903c3d13bde0acf88bc864ab8f06062c6","observation_id":"4048ee19-262b-44f9-8b89-1d9af18a82f9","resolution":{"observed_at":"2026-08-08T11:04:57.690706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.677661Z","title":"Lime: Local interpretable model-agnostic explanations","venue":null,"work_id":"70f86bbc-1df5-48bb-9e44-ce36b3353772","year":null},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.261428Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:735e3b8f0b99ff32b30bc683c1370e71514db109f9b3b280f5b8a482ec0d776f","observation_id":"4d974ff9-e40a-43b1-b177-36263ece6e62","resolution":{"observed_at":"2026-08-08T11:04:57.681077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.669346Z","title":"why should i trust you?","venue":null,"work_id":"e71c5d42-d02f-4ebb-bb82-e6728d86e24a","year":2016},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.267640Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:8ad0044c52cb63699a572c674fbdef8d9f3777952ae4525cb62fd944963cfbe2","observation_id":"5c5d115f-c57a-4150-82a3-9d37d61efc38","resolution":{"observed_at":"2026-08-08T11:04:57.672529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.659882Z","title":"Interpretable image classification with differ- entiable prototypes assignment","venue":null,"work_id":"a8667ec3-22d6-4269-9f01-efbd9934e96b","year":2022},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.270472Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:281fd386935cb7f03888a6a5118c34cb61ca928d6786075f9745b15706fb9be3","observation_id":"863bbd1c-a408-42c1-9969-c1d62cd51291","resolution":{"observed_at":"2026-08-08T11:04:57.663492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.650444Z","title":"Protopshare: Prototypical parts shar- ing for similarity discovery in interpretable image clas- sification","venue":null,"work_id":"9f7e08c9-d0ac-4a69-bdda-bb544854a167","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.273305Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:c01a6fc95090fbdfd41fef3be89672af23561d8831feab9e97380d3d1dfeb393","observation_id":"6b1a8b0a-3591-4445-bfe3-ebc69b5219eb","resolution":{"observed_at":"2026-08-08T11:04:57.654141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.640411Z","title":"Evaluating the visualization of what a deep neural net- work has learned.IEEE Transactions on Neural Net- works and Learning Systems, 2017","venue":null,"work_id":"322f2c97-a35c-477f-90c8-2ec7683b1487","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.276022Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:55e0b74fea7dadf5c8d6369ad1c23d3b33d6e1255cf16f3113b4b568880cca8f","observation_id":"db5bf0a5-cdef-41a2-be57-b24afe077b9b","resolution":{"observed_at":"2026-08-08T11:04:57.644611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14335","last_updated":"2025-07-16T14:35:17Z","snapshot_observed_at":"2026-08-09T22:53:00.900901Z","submitted_at":"2024-06-20T14:04:53Z","title":"Linearly-Interpretable Concept Embedding Models for Text Analysis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14335","snapshot_observed_at":"2026-08-08T11:04:57.279317Z","title":"Self-supervised interpretable concept-based models for text classification","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.279317Z"},"links":{"cited_paper":"/paper/2406.14335","citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:14928022c3d68e5b551e5d3d45a3abee033b3e54cb2552560cf67f553c542c37","observation_id":"c1dd39b7-5126-4a11-9bc0-37ae4f19d6d2","resolution":{"observed_at":"2026-08-08T11:04:57.279317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.632196Z","title":"Netflow datasets for machine learning-based network intrusion detection systems","venue":null,"work_id":"df580be4-a22c-40fe-9006-1e2e24746854","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.282846Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:c08d994acb8f979fc8ded580fe6fab82f9517d5a156329db554079fe050e2442","observation_id":"3d113942-36a2-4bf9-97a6-6a8d69d0ca52","resolution":{"observed_at":"2026-08-08T11:04:57.635453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.623285Z","title":"Towards a standard feature set for network intru- sion detection system datasets","venue":null,"work_id":"95d49cc5-4dee-4edc-9340-3d572d59c800","year":2022},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.286120Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:af2bf623fbf8563c122c8d55e6c146a2b1684266a09b933fe4c3a2a7048065a6","observation_id":"a9d366d7-e237-4ac2-bca7-ecd8f7c3d31e","resolution":{"observed_at":"2026-08-08T11:04:57.626552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.614481Z","title":"Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, et al","venue":null,"work_id":"1ad0231f-4a12-4feb-add8-07647c75eb3c","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.289238Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:2b8d1714f921b01b2ddd40cf020eee9b2cc381406217141231b46e3ab237bfa9","observation_id":"096ccf3b-8bc5-48f2-bf78-3b3fe87ee8f4","resolution":{"observed_at":"2026-08-08T11:04:57.617705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.605848Z","title":"On the robustness of domain constraints","venue":null,"work_id":"1f932121-5ef4-47bc-9c80-3a46683344d0","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.292357Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:358f326f9f434b79c1c941c7b83bc3069776a9630df64dc7f16b0c187734dcfb","observation_id":"ae90cf8d-1c13-427f-a430-2a703e4fb4d3","resolution":{"observed_at":"2026-08-08T11:04:57.609015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.596909Z","title":"Krishnan","venue":null,"work_id":"fd33e89f-b868-48f0-bd48-ff1ea90eec95","year":2024},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.295538Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:5dfea76a3f9c77a4763003fece892578961e14c95b2c0096d7740c2a3c140c1e","observation_id":"61f96dfe-4eb2-49b5-bfce-1ae8922de8c5","resolution":{"observed_at":"2026-08-08T11:04:57.600048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.587967Z","title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","venue":null,"work_id":"328e06e9-cf74-4417-bfc9-d4e1f445556a","year":2014},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.298726Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:b85a0f0eca1cc1bb3613f88b41e2fce02e7fb0a78aa7901133975e055d4dab79","observation_id":"d62e46b5-e8b4-4448-8ab4-c2ae95cb244f","resolution":{"observed_at":"2026-08-08T11:04:57.591432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.578472Z","title":"Fooling lime and shap: Ad- versarial attacks on post hoc explanation methods","venue":null,"work_id":"7c33977b-f8c3-4b39-ac9d-d8768967d38d","year":2020},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.301788Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:2c6d87b771515a088a071ccb8310c1fce8cd6d2ff949c858ce0186ef3e6c6ec0","observation_id":"42b485bd-c04b-4e58-b55f-9cb6042a8d80","resolution":{"observed_at":"2026-08-08T11:04:57.581969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03825","last_updated":"2017-06-12T19:53:30Z","snapshot_observed_at":"2026-07-06T05:46:32.599765Z","submitted_at":"2017-06-12T19:53:30Z","title":"SmoothGrad: removing noise by adding noise","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03825","snapshot_observed_at":"2026-08-08T11:04:57.305182Z","title":"Smoothgrad: re- moving noise by adding noise","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.305182Z"},"links":{"cited_paper":"/paper/1706.03825","citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:bb90618324c39a57c7271ef5fad2e55968402f348faca73301bedc50c69a55a1","observation_id":"dc581b8b-a3c9-45ab-8de9-cfee8abcc30b","resolution":{"observed_at":"2026-08-08T11:04:57.305182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.570470Z","title":"Malicious pdf de- tection using metadata and structural features","venue":null,"work_id":"c095190b-d8b8-4140-bbc2-8503cb7b8ad6","year":2012},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.308732Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:5c05310f6bcfa674e2ba701ee3c8b1f3fcad3db5e3f5a446005dfb81659f2ea8","observation_id":"85ae8c13-d80a-4da9-9d2b-4e690598e275","resolution":{"observed_at":"2026-08-08T11:04:57.573277Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.561683Z","title":"Striving for simplicity: The all convolutional net","venue":null,"work_id":"656b50b2-1459-432e-9977-1762041f8bc9","year":2015},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.311675Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:a612a5d428dd825950522f498b8dcf253a4de07ed993e67c7939d0380a4a1a81","observation_id":"e7ccc99c-eb42-470e-9332-db8db238fb50","resolution":{"observed_at":"2026-08-08T11:04:57.564843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.552119Z","title":"Practical evasion of a learning-based classifier: A case study","venue":null,"work_id":"541fdd72-b83c-4dc2-94df-c10395bf8309","year":2014},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.314726Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:6bed331ec266d1d20b9fa78683aa44c6ea92bb585b5c8bbb18dda871cf9ddcc5","observation_id":"3cdbe187-6f71-4b3d-a1e5-a9451edae707","resolution":{"observed_at":"2026-08-08T11:04:57.555393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.543232Z","title":"Ax- iomatic attribution for deep networks","venue":null,"work_id":"79825cb6-cc4b-461b-99da-8df45345753a","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.317715Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:7ecdab74255bd994affc9014e5dbfa1a82c871a806ae515a61da8d81b10eb844","observation_id":"8c9241d9-8a0d-4afc-99ea-a217cdfae5d7","resolution":{"observed_at":"2026-08-08T11:04:57.546408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.534195Z","title":"Ghorbani","venue":null,"work_id":"78f90d77-0beb-43c4-a8d8-9297afce9e4b","year":2009},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.320818Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:37768d8f1c5e9408d8fff718b3693029944ad07c04cbf960ce4b613297340b7c","observation_id":"8bbee272-8e37-4e62-ab52-f95ac7aea42e","resolution":{"observed_at":"2026-08-08T11:04:57.537546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.524894Z","title":"Attention is all you need","venue":null,"work_id":"a9f79386-76ae-4776-b2bd-2cdd7157598b","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.323757Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:ed9f3a62054e1dac10a003c515d02a35a3e4428d8503d0ff3440da639dadb8c8","observation_id":"ed28e061-255d-4045-bc77-3330e983317e","resolution":{"observed_at":"2026-08-08T11:04:57.528144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.515757Z","title":"Interpretable image recognition by constructing trans- parent embedding space","venue":null,"work_id":"b6f20589-1bdd-4173-a7d5-66e884186ef7","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.326769Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:c9925f759a6dfb3c48c9d1a7d6af60252b8344be7ff8564bbc8daf1f884306cb","observation_id":"0d092c81-5c2a-4835-a001-44d863f8a03b","resolution":{"observed_at":"2026-08-08T11:04:57.519026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.506460Z","title":"Evaluating explanation methods for deep learning in security","venue":null,"work_id":"db1b8312-3889-418b-8838-97b959ec6762","year":2020},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.330084Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:aad269c4c3f74183c3afcc1e0bb95232c085206754912c3789e7a09ea40effaf","observation_id":"4bc84f9c-1fc7-4031-9675-ae6425f933cc","resolution":{"observed_at":"2026-08-08T11:04:57.509884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.496176Z","title":"xnids: Explaining deep learning-based network intrusion detection systems for active intrusion responses","venue":null,"work_id":"3fc2a4fe-e52d-4282-be49-bc84c95a0d0d","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.333654Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:a9691d8033586c16927e8b2a71909c52cfa32c6b46a8b4c757bbf3809c956c57","observation_id":"d8a14bc8-5b56-4515-8590-980c3a206c62","resolution":{"observed_at":"2026-08-08T11:04:57.500033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.484772Z","title":"xnids: Explaining deep learning-based network intru- sion detection systems for active intrusion responses","venue":null,"work_id":"26954e1a-2fac-4eac-9145-2bfed737c16c","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.336809Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:d3a05700922c60dfcb2d7fa056a3aced6784c668eecd3f64352fffae7da1ca32","observation_id":"41657f18-1ced-4a13-bb55-8f9dfcdd5504","resolution":{"observed_at":"2026-08-08T11:04:57.488504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.473426Z","title":"Bodmas: An open dataset for learning based temporal analysis of pe malware","venue":null,"work_id":"84be8be1-6505-4726-89a0-0a8b2ecccd08","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.340199Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:1a70300fac68da16efda1dd0100db488fc1c4726c1fb686df1b1a2968073597c","observation_id":"d9e22bcf-2f28-4a5a-9885-572fec2bb55f","resolution":{"observed_at":"2026-08-08T11:04:57.477345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.463693Z","title":"Cade: Detecting and ex- plaining concept drift samples for security applications","venue":null,"work_id":"7cc8b7af-e8be-4149-94b6-19a6f6e80b8d","year":2021},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.343471Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:a5c7147638180054d0fb9a1133b117680e4c5df8771a96418af5d3d80d273b57","observation_id":"65d94b80-2b08-47e4-8d87-c7ae2f8aff6d","resolution":{"observed_at":"2026-08-08T11:04:57.466852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.454303Z","title":null,"venue":null,"work_id":"80b99316-1aa4-4e4f-888b-d0ef490dfb0d","year":2023},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.346639Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:3371312c1f052be08047e0e2a24c2bd5f6c18a53221506d5bef9dc2b70c42999","observation_id":"8710e027-a1bb-470a-8fd7-a7c4c4c319af","resolution":{"observed_at":"2026-08-08T11:04:57.457356Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.445155Z","title":"Concept embedding models: Beyond the accuracy- explainability trade-off","venue":null,"work_id":"f248e9fd-befe-4709-93d9-7920cba56cda","year":2022},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.349878Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:f98eebf05928411f201b6d54a959c1072b1216c145787224f92eb3795061fa4f","observation_id":"93144c59-e18a-4c03-ae76-3adc49342606","resolution":{"observed_at":"2026-08-08T11:04:57.448169Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-08T11:04:57.353100Z","title":"Zeiler and Rob Fergus","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.353100Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:f8169a4a606950c775da8a9c626f843b8ca03f6088f2611a2b8e6e7aa7bc0701","observation_id":"1a364c20-a404-422e-a85e-dbd78cefa638","resolution":{"observed_at":"2026-08-08T11:04:57.353100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.429211Z","title":"Interpretable deep learning under fire","venue":null,"work_id":"41a294a0-3e46-4517-8955-76838ba4964a","year":2020},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.356602Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:01994010289145d0a909b8e31f124aebb382ed97f9a48bc19d75351baa245060","observation_id":"591913a8-ab16-4798-8fdd-518a13fe8013","resolution":{"observed_at":"2026-08-08T11:04:57.433402Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.417188Z","title":"Zintgraf, Taco S","venue":null,"work_id":"8d7c0836-49b3-4abd-b1db-dbdc6693faf2","year":2017},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.359901Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:c31f62d3608f2bde6e1a088248648447868970d366b048febc36756cf1e49c2a","observation_id":"878f1864-b015-42f3-9cab-02da38a7d673","resolution":{"observed_at":"2026-08-08T11:04:57.422044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T11:04:57.779179Z","title":null,"venue":null,"work_id":"a4a55e8d-66ff-4a9e-bdd2-a51515f651f6","year":2025},"citing_paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-08T11:04:57.264202Z"},"links":{"citing_paper":"/paper/2608.05552"},"observation_digest":"sha256:4312bbe606f5d9a6cb5c5c2638e6c6f5d57ffbfe6f9436e294eb2a43e5c7a279","observation_id":"4c74fcdd-ebb6-475b-b679-6d2d34860519","resolution":{"observed_at":"2026-08-08T11:04:57.782360Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.05552","last_updated":"2026-08-06T03:08:13Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-09T22:11:17.895721Z","submitted_at":"2026-08-06T03:08:13Z","title":"A Self-Explainable Deep Architecture for Security Applications"},"reference_resolution":{"displayed":69,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":10,"verified_exact":0,"verified_fuzzy":58},"total_outbound_references":69},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2608.05552."}