{"as_of":"2026-08-22T06:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2aec4925115284d80ceb42d5f800e35719efb718e96135dc8eab9477e9d416e0","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T20:31:43.204245Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.12803/citation-record","integrity":"/paper/2505.12803/integrity","json":"/paper/2505.12803/citation-record.json","paper":"/paper/2505.12803"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:31:43.404194Z","title":"To ensure fair- ness, all models were trained for 600 epochs using default augmentations for contrastive learning as specified in their respective original papers","venue":null,"work_id":"64479160-c74e-44d0-abea-d99252f8df31","year":2012},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.194323Z"},"links":{"citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:41f732b2b45c7fd38de9a70e7b4d351ca9f1d0975bbcc3c5db529895d10638d5","observation_id":"612e99bf-545e-4e6b-b378-3b4a7158bd31","resolution":{"observed_at":"2026-08-15T20:31:43.409713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:31:43.453471Z","title":"and Chan, P","venue":null,"work_id":"398777b7-de32-4bb8-a103-7ae1c75450c1","year":2020},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.150719Z"},"links":{"citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:e00f21e5154cf734d37f8e1c32f5dfe58344787d95e7e1fad3d19d2ea4ebf667","observation_id":"b15e9577-1710-45d3-b976-579424bcaeb3","resolution":{"observed_at":"2026-08-15T20:31:43.458950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:31:43.420420Z","title":null,"venue":null,"work_id":"743f4ac5-6f18-48a9-9d27-96ce89d87332","year":2001},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.169689Z"},"links":{"citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:7a961a279e6865b063e881ee07f9191cf8a4068695a86160b49a927e750319a5","observation_id":"204f10dc-6ea8-4b7c-bd0d-20bd25af67b1","resolution":{"observed_at":"2026-08-15T20:31:43.425279Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.10915","last_updated":"2022-06-22T08:51:40Z","snapshot_observed_at":"2026-08-18T00:43:43.325873Z","submitted_at":"2022-06-22T08:51:40Z","title":"Understanding the effect of sparsity on neural networks robustness","version":1},"cited_work":{"arxiv_id":"2206.10915","doi":null,"metadata_source":"pith","pith_arxiv_id":"2206.10915","snapshot_observed_at":"2026-08-15T20:31:43.280683Z","title":"Understanding the effect of sparsity on neural networks robustness","venue":"cs.CV","work_id":"cebf48f6-983a-4f68-8e9b-5c52da82551b","year":2022},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.178913Z"},"links":{"cited_paper":"/paper/2206.10915","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:fdda5159c9c73b0364beb1a301cd123f8c9e373be01e86c04dc70ee59aeafdc9","observation_id":"1c8a30b1-a302-4939-89bd-e18db2fee570","resolution":{"observed_at":"2026-08-15T20:31:43.285825Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:31:43.372558Z","title":"Figure 10: Attribution maps from CIFAR10 and TinyIma- geNet datasets computed using LayerCAM: Row 1,3,5,7: model trained without GradMix; Row 2,4,6,8: model trained with GradMix","venue":null,"work_id":"7caa3e49-518f-4b44-9abc-add160f6e83c","year":2022},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.204245Z"},"links":{"citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:e9d6af12846ec7e329f81d564346355958e6d438bf41f0312bb9239468e4a93e","observation_id":"4f27cbee-297b-4499-9800-111ccb714d29","resolution":{"observed_at":"2026-08-15T20:31:43.377589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:31:43.388163Z","title":"We list the final applied hyper-parameters in Table 8, including γ andλ in the learning objective,k in the detection method, the number of training epochs, and batch size (BS)","venue":null,"work_id":"82af4cfa-07dc-4ee2-9a01-b2db359fff63","year":2020},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":128,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.198924Z"},"links":{"citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:1d0fbbf8f09dd5ace3a850d8a9d6df49eb7b2eb50b03680d9e25f4291809f057","observation_id":"ea4edf72-14c7-4f88-8723-6c8d77714db1","resolution":{"observed_at":"2026-08-15T20:31:43.393459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-08-14T18:53:38.574749Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-08-15T20:31:43.164902Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.164902Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:f7da0e7609e78c32bb0f8843429c44f525e839d32e43b9ac20677c1f42f17352","observation_id":"ce62385e-2329-4b9a-b8d9-095cedbde99f","resolution":{"observed_at":"2026-08-15T20:31:43.164902Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.04552","last_updated":"2017-11-29T14:51:40Z","snapshot_observed_at":"2026-08-13T11:54:46.030796Z","submitted_at":"2017-08-15T15:21:53Z","title":"Improved Regularization of Convolutional Neural Networks with Cutout","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.04552","snapshot_observed_at":"2026-08-15T20:31:43.145596Z","title":"and Taylor, G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.145596Z"},"links":{"cited_paper":"/paper/1708.04552","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:7136c0f34a8cc066b06b267a49d271aaebbd83ae55c728f63950c16fcc63d34e","observation_id":"d7410632-60ac-4ac5-98de-4724e4f4cf77","resolution":{"observed_at":"2026-08-15T20:31:43.145596Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02594","last_updated":"2024-01-05T01:31:14Z","snapshot_observed_at":"2026-08-16T15:29:15.790890Z","submitted_at":"2024-01-05T01:31:14Z","title":"Unsupervised hard Negative Augmentation for contrastive learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02594","snapshot_observed_at":"2026-08-15T20:31:43.174089Z","title":"and Lampos, V","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.174089Z"},"links":{"cited_paper":"/paper/2401.02594","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:1f480171bbdeb73b8e1ec6ec1e73e85b61fe97a79df97786c1e91d232916f340","observation_id":"9a6e2cc9-dd51-4f32-8a35-4971d982820c","resolution":{"observed_at":"2026-08-15T20:31:43.174089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1710.09412","last_updated":"2018-04-27T21:39:25Z","snapshot_observed_at":"2026-08-08T10:28:19.597631Z","submitted_at":"2017-10-25T18:30:49Z","title":"mixup: Beyond Empirical Risk Minimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.09412","snapshot_observed_at":"2026-08-15T20:31:43.189085Z","title":"N., and Lopez-Paz, D","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.189085Z"},"links":{"cited_paper":"/paper/1710.09412","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:1679421845371f6b99d0c73c1323db73ae0ca30dda381836bb010c3115c945a7","observation_id":"8a4ac1f6-2b07-4483-9d01-0654c4abb67f","resolution":{"observed_at":"2026-08-15T20:31:43.189085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.09844","last_updated":"2022-02-27T07:42:30Z","snapshot_observed_at":"2026-08-16T17:20:00.575217Z","submitted_at":"2022-02-20T15:52:08Z","title":"Sparsity Winning Twice: Better Robust Generalization from More Efficient Training","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.09844","snapshot_observed_at":"2026-08-15T20:31:43.140140Z","title":"Sparsity winning twice: Better robust generalization from more efficient training","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.140140Z"},"links":{"cited_paper":"/paper/2202.09844","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:8015499e440673019a89bc15134f4bf082329a71ae8298a4044ac92780d3b3f4","observation_id":"9d2ce34d-811b-4584-bceb-01cc3ec6ccf6","resolution":{"observed_at":"2026-08-15T20:31:43.140140Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.09348","last_updated":"2022-04-23T16:44:20Z","snapshot_observed_at":"2026-08-16T17:48:26.312603Z","submitted_at":"2021-10-18T14:22:19Z","title":"Understanding Dimensional Collapse in Contrastive Self-supervised Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.09348","snapshot_observed_at":"2026-08-15T20:31:43.155537Z","title":"Understand- ing dimensional collapse in contrastive self-supervised learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.155537Z"},"links":{"cited_paper":"/paper/2110.09348","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:739e0835c17f6a9385d670b32ce45ddc62d74cef197299ce5fbf08c9b1442edd","observation_id":"87e4352e-76c8-4410-9118-07b4f3709cc7","resolution":{"observed_at":"2026-08-15T20:31:43.155537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.13048","last_updated":"2020-04-05T13:35:20Z","snapshot_observed_at":"2026-08-16T14:58:27.016879Z","submitted_at":"2020-03-29T15:01:05Z","title":"Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification","version":2},"cited_work":{"arxiv_id":"2003.13048","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.13048","snapshot_observed_at":"2026-08-15T20:31:43.256643Z","title":"Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification","venue":"cs.CV","work_id":"64181260-7eed-48cc-a94f-01faea54c8e2","year":2020},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.184295Z"},"links":{"cited_paper":"/paper/2003.13048","citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:8ef0657b4122fa3f75d171cf1400e2fd56ff52f7789eab6858dea27a382ac33f","observation_id":"218206f0-e7bd-4096-9fe3-6337b28fa44d","resolution":{"observed_at":"2026-08-15T20:31:43.263416Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:31:43.436451Z","title":"and Carvalho, M","venue":null,"work_id":"44250fab-f5ad-47f7-856f-e41e0345947a","year":2021},"citing_paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-15T20:31:43.160386Z"},"links":{"citing_paper":"/paper/2505.12803"},"observation_digest":"sha256:bebff8cacfd55100f84c8246eeb8e481ae0c5f761d8258d615c0c9e13bcbaaad","observation_id":"d11d4ed7-33e7-4088-8591-6291e214b225","resolution":{"observed_at":"2026-08-15T20:31:43.441361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.12803","last_updated":"2025-05-19T07:32:06Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-18T00:41:55.459190Z","submitted_at":"2025-05-19T07:32:06Z","title":"Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":2,"verified_fuzzy":5},"total_outbound_references":14},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2505.12803."}