{"as_of":"2026-08-12T04:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:707772fdbe26f33f25de286a29359aebe2406368cb802ec407ade999727b0526","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:34:25.605057Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2507.10574/citation-record","integrity":"/paper/2507.10574/integrity","json":"/paper/2507.10574/citation-record.json","paper":"/paper/2507.10574"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:34:25.788654Z","title":null,"venue":null,"work_id":"7cac367c-92bb-4eb7-94d0-fa881ac8d987","year":1948},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.544608Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:fcf1718860dbfc49a966c857c78841ec5964bc9c64537d95174aa1479854d2bb","observation_id":"ea90a32e-daee-406e-b725-684fa2b635c9","resolution":{"observed_at":"2026-08-06T18:34:25.791496Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.780564Z","title":null,"venue":null,"work_id":"bd679ac8-f112-4f6a-b8ab-d0ca144cee9b","year":1948},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.547892Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:715aa932eba9f048a2476a6ae3fe94a792916ddf28961f24687b623885d36932","observation_id":"8ef6d363-e032-4c89-8006-df703e1b8b64","resolution":{"observed_at":"2026-08-06T18:34:25.783886Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.771724Z","title":"Kullback and R","venue":null,"work_id":"354cb548-a803-43a9-ba3e-f1e67d8582c8","year":1951},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.550453Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:dde9766029c69777f6b52e5f48db2ecc5ff1200f32e29a907c25a1e3f8ac61aa","observation_id":"9ffc4f19-f411-4981-a98f-e07e67e6dc26","resolution":{"observed_at":"2026-08-06T18:34:25.775248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.764104Z","title":null,"venue":null,"work_id":"472963ab-1e8e-40f8-b41e-0752b8e93c7c","year":1948},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.553608Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:e0d421f8c763be73a349dacfd11a3f5f375ea94bdcca412c08211596623633a8","observation_id":"d28dbc09-a695-4816-a890-55540be8b2b2","resolution":{"observed_at":"2026-08-06T18:34:25.766710Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.556935Z","title":"Deep learning","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.556935Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:c7ed3fcb06345637e8699da62df9d56b6fb66fe24f431502b9a3eb51723b552c","observation_id":"4a804016-d645-400a-a9c7-688b6c12496c","resolution":{"observed_at":"2026-08-06T18:34:25.556935Z","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":"2026-08-06T18:34:25.753475Z","title":null,"venue":null,"work_id":"0237fb92-3f8c-4c19-a2b4-6f7f27e47f6a","year":1972},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.559857Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:6026f08f92a0e7317fa3a4d00370ad6957000e0f4f3b38f85b35fe5d20ee87a2","observation_id":"d98dfbf1-160c-4e0e-ac9d-29b354bf3647","resolution":{"observed_at":"2026-08-06T18:34:25.755941Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.745867Z","title":"Generalized linear models","venue":null,"work_id":"764485bc-a76b-45b5-9fad-20c64a8050ac","year":2019},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.562594Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:3748cf74405b73bc648c3827b6a110ee84b7b310a4de41ec005fb3d25ce60eee","observation_id":"4d9587a9-97ac-4400-8ed3-93638f121073","resolution":{"observed_at":"2026-08-06T18:34:25.749196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.737981Z","title":"Cross-entropy los s functions: Theoretical analysis and applications","venue":null,"work_id":"dddb3e64-c4e6-4972-acc4-10563843fc47","year":2023},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.565068Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:c43505b8fd25d2dd3cc3d3009b0feaefbe60f1d7e1161b3aa6d6e0b980935a9f","observation_id":"beb578fb-bff9-452f-b66d-b21d8932cf55","resolution":{"observed_at":"2026-08-06T18:34:25.741623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.730426Z","title":"Uniface : Uniﬁed cross-entropy loss for deep face recognition","venue":null,"work_id":"4f9908f8-e1ef-4a86-bf8f-0d502a2c8e19","year":2023},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.567685Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:5ef041c4210915613531f879b073396eeb710c15759e91708bb0aa7ebe8ff59e","observation_id":"ea42d3b2-1cc1-418e-8d20-ddccd26b7fa5","resolution":{"observed_at":"2026-08-06T18:34:25.733511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.723597Z","title":null,"venue":null,"work_id":"9d60da06-076b-4327-a41a-30d082b26141","year":2020},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.570109Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:6f42c81ed2e456171ea7d3d6423f087419f8ded9f38f857b49509e62cb8995ac","observation_id":"a8882f0a-cb61-4987-9ec8-403a2515374e","resolution":{"observed_at":"2026-08-06T18:34:25.725860Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.716543Z","title":"An alternative cross entropy loss for learnin g-to-rank","venue":null,"work_id":"f664b8ff-fc07-46fc-91f7-71e31bea71f3","year":2021},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.573189Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:d0636a03772b0801a1a45e40d542b4b0e671fd3248beb6cb6fc33765a11976a5","observation_id":"35e80819-27ae-4ac6-adb0-a7f9b6bf7b8f","resolution":{"observed_at":"2026-08-06T18:34:25.719066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.709464Z","title":"Ad- dressing imbalance in multi-label classiﬁcation using weighted cross en tropy loss function","venue":null,"work_id":"751ed4d7-10f2-49b5-8259-5a67646735e4","year":2020},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.575596Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:eb11e8318e077dd8e21f0105664c812b72baa623a2f65eaa91f3180a8ece3611","observation_id":"1fc0d861-1c7e-4add-9f05-98dbaaf5844e","resolution":{"observed_at":"2026-08-06T18:34:25.712039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.702034Z","title":"Generalized cross entropy loss f or training deep neural networks with noisy labels","venue":null,"work_id":"e249a5ce-7f65-4b51-9f1f-21a271d7a007","year":2018},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.578410Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:c6f7adfb0a263b98ac74ec30c66e09b99befb5a375b4b38c6e2c45999ff840b1","observation_id":"4a8ad1c2-95cc-422d-8ecc-7b52409e065b","resolution":{"observed_at":"2026-08-06T18:34:25.704990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.693871Z","title":"Taming the cross ent ropy loss","venue":null,"work_id":"ac7f0c6e-1907-4217-b0d9-fe252d595404","year":2019},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.580608Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:59db8995a27cdb9a4ffe7180aa2786df6bc03a00eb4e2082184eff4c44ade7d5","observation_id":"d54883c9-ac09-463f-9f32-6756c1f44f5f","resolution":{"observed_at":"2026-08-06T18:34:25.696413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.686623Z","title":"Dua l cross-entropy loss for small-sample ﬁne-grained vehicle classiﬁcation","venue":null,"work_id":"3a83e071-4749-45e9-bc79-6d42e51fb236","year":2019},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.583706Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:f2d85c44dce95164a037a992f77ed364f092dcb0b06aaac608be934a4e0f0269","observation_id":"fa8959ec-4659-4d46-af20-f984c5a4392e","resolution":{"observed_at":"2026-08-06T18:34:25.689119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10626","last_updated":"2020-02-20T08:50:47Z","snapshot_observed_at":"2026-08-04T22:59:24.503497Z","submitted_at":"2019-05-25T16:11:14Z","title":"Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness","version":3},"cited_work":{"arxiv_id":"1905.10626","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.10626","snapshot_observed_at":"2026-08-06T18:34:25.637759Z","title":"Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness","venue":"cs.LG","work_id":"ac3b938c-8541-4dbe-bda7-883a5e389546","year":2019},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.585989Z"},"links":{"cited_paper":"/paper/1905.10626","citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:e6bdb2ddbd2126a9933de49cd34f155ce3f4298f9a0fa2fa5bfffd93564cd0b6","observation_id":"81d319f5-4068-42a5-95b7-f5ecb4acf1f0","resolution":{"observed_at":"2026-08-06T18:34:25.642460Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.678442Z","title":"An analysis of the softmax cross entropy loss for learning-to-rank with binary relev ance","venue":null,"work_id":"7f42d551-3270-4568-8976-887cc41bb0c0","year":2019},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.589143Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:fd5a1376b104da5ab8cd4c68fbaa24324497d2c35c2536213c6d82976f85a7d4","observation_id":"35468518-7b72-4f95-bbff-e81ca888b0e4","resolution":{"observed_at":"2026-08-06T18:34:25.681239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.669884Z","title":"Mpce: a maximum probability based cross entropy loss function for n eural network classiﬁca- tion","venue":null,"work_id":"46f6cbd4-9f7d-4339-97a8-ff2b8cdbd52a","year":2019},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.591567Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:b5feb909092f953f9127c1d6c59bbc14558a61b1093b7d0f5ed9b06c7ab5d101","observation_id":"4a907d60-468f-45c9-b5a6-29609491c280","resolution":{"observed_at":"2026-08-06T18:34:25.672561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.661275Z","title":"The real-world-weight cross -entropy loss function: Modeling the costs of mislabeling","venue":null,"work_id":"f5de3fd3-f7f9-4bc1-bd2f-79a1ec375ea3","year":2020},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.594825Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:212d18eeef53ebc69dc3e7b677d1eb5289a55dedf1d7add6178b4655749a752c","observation_id":"26653cf6-46f4-490b-bc14-e75e95a97bba","resolution":{"observed_at":"2026-08-06T18:34:25.664784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:34:25.597250Z","title":"Deep res idual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.597250Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:4e5c6464e7122fcf71fae411a91fe6897a329d8d9a31dae4eac8d4b1f98c88d0","observation_id":"8077bdc5-debb-4e67-92e7-ee8f1436f389","resolution":{"observed_at":"2026-08-06T18:34:25.597250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6199","last_updated":"2014-02-19T16:33:14Z","snapshot_observed_at":"2026-07-06T03:31:33.797310Z","submitted_at":"2013-12-21T03:36:08Z","title":"Intriguing properties of neural networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6199","snapshot_observed_at":"2026-08-06T18:34:25.599684Z","title":"Intriguing properties of neural netw orks","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.599684Z"},"links":{"cited_paper":"/paper/1312.6199","citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:64189e746428055778fec75f00c85035b5ce9bd56a3a2070791cc93a23e0f9f1","observation_id":"b0abfe66-e904-46f3-8314-d9b9a01aa745","resolution":{"observed_at":"2026-08-06T18:34:25.599684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-06T18:34:25.602460Z","title":"Exp laining and harnessing adver- sarial examples","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.602460Z"},"links":{"cited_paper":"/paper/1412.6572","citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:b1839b41fdf82aa3d9c33c5ec387336744d5dccc41fca829dd52152ed2da6ce6","observation_id":"e2a30539-0b54-42f6-9148-7404f5cc002c","resolution":{"observed_at":"2026-08-06T18:34:25.602460Z","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":"2026-08-06T18:34:25.648388Z","title":"A review on multi-label learning a lgorithms","venue":null,"work_id":"33e36ec8-fe7f-40ad-b6e3-082587347673","year":2013},"citing_paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T18:34:25.605057Z"},"links":{"citing_paper":"/paper/2507.10574"},"observation_digest":"sha256:214aafbe9fa158f288d5f5a9c5d4e5fd6a417b505966230532914c13e39ff27d","observation_id":"fdc74859-25e5-4c4a-9638-6819ce98b6f2","resolution":{"observed_at":"2026-08-06T18:34:25.651304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.10574","last_updated":"2025-07-10T16:38:57Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T18:27:15.625690Z","submitted_at":"2025-07-10T16:38:57Z","title":"Enhancing Cross Entropy with a Linearly Adaptive Loss Function for Optimized Classification Performance"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":1,"verified_fuzzy":13},"total_outbound_references":23},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.10574."}