{"as_of":"2026-08-08T13:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8344de11d4ff78a0e416c687d4132d8ddf983669abbf289f2657d2efa89aba0d","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:16:51.047903Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2506.05844/citation-record","integrity":"/paper/2506.05844/integrity","json":"/paper/2506.05844/citation-record.json","paper":"/paper/2506.05844"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:16:50.998723Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:50.998723Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:5dca60d68b0f63d202e6cb7128bda2ec05a5f4b1595a7022f17f003ad4ec6740","observation_id":"f9f81905-ad36-44f0-8646-aae14fd67cc5","resolution":{"observed_at":"2026-08-07T10:16:50.998723Z","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":"2026-08-07T10:16:51.191601Z","title":"P., Selman, B., and Weinberger, K","venue":null,"work_id":"2672ba4c-b407-41f3-b19d-d0f3a23d23b6","year":2018},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.002993Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:28f13b0f0631187746523f135650ec8bc9888df01417b8f19cd5f744ff21a67a","observation_id":"612b37da-ce55-4510-bf1b-ddc20f9f8d89","resolution":{"observed_at":"2026-08-07T10:16:51.194470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:16:51.183170Z","title":"V., Bowyer, K","venue":null,"work_id":"8d323625-6823-4ce7-8a37-5ddcf5c3b672","year":2002},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.006541Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:4760fa7f060efaf45bc8cd0992323bb7c18a0e16cd191082b9853c4a7c503287","observation_id":"c9588e97-ba6d-4025-85e6-ab0c5fbf4da6","resolution":{"observed_at":"2026-08-07T10:16:51.186152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:16:51.175126Z","title":"and Pratap, V","venue":null,"work_id":"0aa6a28e-8c69-4fd5-8f77-628b0bdbc82c","year":2023},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.009526Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:e11376e0008827f92ac4c252283d5d22ec72817d02ed02775a5d1f1d9f9b4b21","observation_id":"a8d4dfdc-0a91-4e21-9b1b-f9d62de8c2ea","resolution":{"observed_at":"2026-08-07T10:16:51.177826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:16:51.012536Z","title":"Generative adversarial networks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.012536Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:fdb9698f8b960e2ec0074d194eeee4b772e10fcdcbb737b8fb2cb869994e55cf","observation_id":"f49f08cc-a642-4942-b9ee-f60c515b5635","resolution":{"observed_at":"2026-08-07T10:16:51.012536Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:16:51.015513Z","title":"P., Welling, M., et al","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.015513Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:19ea8eba1ef2925d4326b20f77e634ba45cc46501e475390c60ec1febd4a3f4c","observation_id":"ed4fe2ec-0b04-499f-b125-1fd04042b199","resolution":{"observed_at":"2026-08-07T10:16:51.015513Z","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":"2026-08-07T10:16:51.154846Z","title":"Intrusion detection system after data augmentation schemes based on the vae and cvae","venue":null,"work_id":"eb8f2af2-b108-4739-90f2-9be3b4b4cd87","year":2022},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.018291Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:0fc94eaf1f0643e8bd726f2648b9b07c52d619659edca86da5a7fa1fc0f89480","observation_id":"c508a63a-04d5-4867-8069-f3662c7cef59","resolution":{"observed_at":"2026-08-07T10:16:51.158143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:16:51.146608Z","title":"J., Saadah, S., Yunanto, P","venue":null,"work_id":"597b67d3-d3f4-4a03-9847-117526d21ded","year":2024},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.021662Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:b6bbfde61e91fc518fb6bfebea0334e39c0b30a8820c4cf040358df298bcb1a3","observation_id":"3ca1999c-7ed0-461d-b630-823cdac4cc60","resolution":{"observed_at":"2026-08-07T10:16:51.149306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1411.1784","last_updated":"2014-11-06T22:33:22Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-11-06T22:33:22Z","title":"Conditional Generative Adversarial Nets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1411.1784","snapshot_observed_at":"2026-08-07T10:16:51.024406Z","title":"and Osindero, S","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.024406Z"},"links":{"cited_paper":"/paper/1411.1784","citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:52d3d3249541db1c5e54514bd94bb0ec17e63dc4da5c3d2a4bf7e61a626633b0","observation_id":"45ca5866-efb6-4162-9c04-5fb46e941298","resolution":{"observed_at":"2026-08-07T10:16:51.024406Z","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":"2026-08-07T10:16:51.138306Z","title":null,"venue":null,"work_id":"febf98f7-82bc-449e-86b2-4ff404edcca9","year":2019},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.027416Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:6f1e2228befbb5350ab97097a908fdbe047d3ef3216e9ba827e3ec6f8f85f0ab","observation_id":"3d239631-5cea-4b7d-8c0e-72e6685e0c20","resolution":{"observed_at":"2026-08-07T10:16:51.141042Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:16:51.030097Z","title":"Learning structured output representation using deep conditional generative models","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.030097Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:2b41889e0ff4d4d89ef64b7a5bb8d776f6d50f9e38d59f64e6bc91cb0f1ddb7b","observation_id":"16275f09-fa90-4bb3-bebb-9eaf6402eeb8","resolution":{"observed_at":"2026-08-07T10:16:51.030097Z","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":"2026-08-07T10:16:51.124159Z","title":"A novel ensemble method for imbalanced data learning: Bagging of extrapolation-smote svm","venue":null,"work_id":"1ec31c6e-6429-4f32-91d1-917fbc382ab8","year":2017},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.033021Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:e111443d4fa8bf51a1f72b8df25d5ae1c77a08f6b351350deb17d422e2b09b50","observation_id":"360a5ecb-c8d4-45f8-8c75-e2371988e4f6","resolution":{"observed_at":"2026-08-07T10:16:51.127384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:16:51.115468Z","title":"Semantics disentangling for text-to-image generation","venue":null,"work_id":"d18b025a-2970-4cb5-a455-0798c5271825","year":2019},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.035968Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:7cac5d46a14ece2bd788b9ba8fa3a3e16f043220fc316dbb0c18f66d698f2e5e","observation_id":"ed9dcaca-0a53-499d-b3a4-fdeddef5e0a7","resolution":{"observed_at":"2026-08-07T10:16:51.118417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.14027","last_updated":"2025-05-20T07:27:51Z","snapshot_observed_at":"2026-08-07T15:39:59.074329Z","submitted_at":"2025-05-20T07:27:51Z","title":"CSAGC-IDS: A Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data","version":1},"cited_work":{"arxiv_id":"2505.14027","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.14027","snapshot_observed_at":"2026-08-07T10:16:51.075509Z","title":"CSAGC-IDS: A Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data","venue":"cs.CR","work_id":"58b9cd20-e6af-4e8d-a80e-06fa43e4cc43","year":2025},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.038434Z"},"links":{"cited_paper":"/paper/2505.14027","citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:0dba6abfca6272006a3fe01d746a5436a9b7553b1311a352b827ea9b0256b928","observation_id":"21b85faf-e5e2-4f95-bf88-7d83556432d5","resolution":{"observed_at":"2026-08-07T10:16:51.081180Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:16:51.041375Z","title":"@esa (Ref","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.041375Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:215d53f2e858a4ac53d60a5d7c1ad92fc019c6ac9129ae81cc49a458ce2635dd","observation_id":"6535de3e-7e04-4f08-b83a-69029d404924","resolution":{"observed_at":"2026-08-07T10:16:51.041375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:16:51.044406Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.044406Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:f204651ae7a57e51d198fc2818de929f6e8e4600c55e3098d76c214989727120","observation_id":"3f904ffb-e384-4b6e-97c7-9f9afc29fd05","resolution":{"observed_at":"2026-08-07T10:16:51.044406Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:16:51.047903Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T10:16:51.047903Z"},"links":{"citing_paper":"/paper/2506.05844"},"observation_digest":"sha256:dc35883509106c73608e30c2c04005bec742309d13f259d40946ca72649e56ca","observation_id":"e63885c2-f26d-4d51-8781-439d3e99bc29","resolution":{"observed_at":"2026-08-07T10:16:51.047903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.05844","last_updated":"2025-06-27T12:12:51Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-07T10:10:56.952625Z","submitted_at":"2025-06-06T08:01:17Z","title":"$\\text{C}^{2}\\text{BNVAE}$: Dual-Conditional Deep Generation of Network Traffic Data for Network Intrusion Detection System Balancing"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":1,"verified_fuzzy":7},"total_outbound_references":17},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2506.05844."}