{"as_of":"2026-08-09T19:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a15ea6442e53d4f9e8ee2d0726751e96293d99a95ece509a4b560f3401fd2315","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":"2026-08-08T16:19:18.656746Z","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":"2026-08-09T06:31:02.800959+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/2502.06243/citation-record","integrity":"/paper/2502.06243/integrity","json":"/paper/2502.06243/citation-record.json","paper":"/paper/2502.06243"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:19:19.154840Z","title":"Skin lesion classification for melanoma using deep learning,","venue":null,"work_id":"71ae3bd3-e8d5-4844-b554-d52c6e429be6","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.368143Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:4129849cd8d331dcb07238b76845751022887845f3a0196cd1e1cace345259ef","observation_id":"67e5ca55-7db3-4c30-9f4e-dcfc8a4650c4","resolution":{"observed_at":"2026-08-08T16:19:19.212002Z","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":"2026-08-08T16:19:19.072493Z","title":"Conditional adversarial segmentation and deep learning approach for skin lesion sub-typing from dermoscopic images,","venue":null,"work_id":"62b51ec2-ffb5-4f42-bb4a-4c459436bf6d","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.395737Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:246b8491ac7d299bd44a58b527e0eaf2b52bf98c78ef686029c7a529069b147b","observation_id":"ef583995-0d4d-45e3-b5d4-0631afe3e3c1","resolution":{"observed_at":"2026-08-08T16:19:19.106228Z","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":"2412.17301","last_updated":"2024-12-23T05:43:17Z","snapshot_observed_at":"2026-07-06T20:11:55.722067Z","submitted_at":"2024-12-23T05:43:17Z","title":"Dynamic Scheduling Strategies for Resource Optimization in Computing Environments","version":1},"cited_work":{"arxiv_id":"2412.17301","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.17301","snapshot_observed_at":"2026-08-08T16:19:18.833181Z","title":"Dynamic Scheduling Strategies for Resource Optimization in Computing Environments","venue":"cs.DC","work_id":"09595b9e-39d8-495e-aed7-72cab8cc0ca3","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.427629Z"},"links":{"cited_paper":"/paper/2412.17301","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:dd91105cd4f7f5af9cf2333fc9877b06e346d73055b04fd74aa09f8cc71a6b77","observation_id":"74c85b65-108f-428b-9992-da854289dcc2","resolution":{"observed_at":"2026-08-08T16:19:18.892731Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-08T16:19:18.996071Z","title":"A quantum -inspired deep learning model for skin lesion classification,","venue":null,"work_id":"d32c0b17-cb5b-4c1a-ab9d-0508e305aeb9","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.431503Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:10716b156454c7916ffa600735512f24670253704563583147167b7253f238bb","observation_id":"04d3ab00-52a7-4ac3-8072-4e7fd749e425","resolution":{"observed_at":"2026-08-08T16:19:19.024327Z","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":"2402.10454","last_updated":"2024-02-16T05:16:20Z","snapshot_observed_at":"2026-07-06T17:31:00.274878Z","submitted_at":"2024-02-16T05:16:20Z","title":"Optimizing Skin Lesion Classification via Multimodal Data and Auxiliary Task Integration","version":1},"cited_work":{"arxiv_id":"2402.10454","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.10454","snapshot_observed_at":"2026-08-08T16:19:18.771589Z","title":"Optimizing Skin Lesion Classification via Multimodal Data and Auxiliary Task Integration","venue":"cs.CV","work_id":"b59e09ed-dbae-4355-a931-f5bd7e5efdb4","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.435190Z"},"links":{"cited_paper":"/paper/2402.10454","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:b55573483f331a53f13e938b2f33693582857e042f27ea8dfbdfe94e3244e4b6","observation_id":"deddb37c-ef9b-4687-b667-16b0d878543b","resolution":{"observed_at":"2026-08-08T16:19:18.797111Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-08T16:19:18.987680Z","title":"Development, application and utility of a machine learning approach for melanoma and non -melanoma lesion classification using counting box fractal dimension,","venue":null,"work_id":"dd668f85-f887-4fab-861f-188cbb9ec151","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.439552Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:84417f22a90ebb84d7ebf0ab6037cc6c4b34e94c1eeb9733d0fe733967e8dff3","observation_id":"b97fc49b-beb3-4836-b2b1-48146d0dfe5f","resolution":{"observed_at":"2026-08-08T16:19:18.990690Z","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":"2026-08-08T16:19:18.978401Z","title":"Comparison of Tree -Based Feature Selection Algorithms on Biological Omics Dataset,","venue":null,"work_id":"418773bb-b92d-48ca-9bef-ce3d8861a7de","year":2021},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.442951Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:928db1beae7009959160778b313becf37cf4869f9aa5366f346d9c4bddda9836","observation_id":"da93bad9-90cd-4451-9024-c629cafa2f4e","resolution":{"observed_at":"2026-08-08T16:19:18.981924Z","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":"2412.16662","last_updated":"2024-12-24T17:21:50Z","snapshot_observed_at":"2026-08-05T01:26:56.275302Z","submitted_at":"2024-12-21T15:23:34Z","title":"Adversarial Attack Against Images Classification based on Generative Adversarial Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16662","snapshot_observed_at":"2026-08-08T16:19:18.445840Z","title":"Adversarial Attack Against Images Classification based on Generative Adversarial Networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.445840Z"},"links":{"cited_paper":"/paper/2412.16662","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:d747f21e742aee2e8ec9a9c85007ea350748c011d2afc5832cd0ac442ed71153","observation_id":"e83a6ccb-df6b-4d46-a85a-1acd69fa3bab","resolution":{"observed_at":"2026-08-08T16:19:18.445840Z","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":"2026-08-08T16:19:18.449377Z","title":"Scaling -up medical vision -and- language representation learning with federated learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.449377Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:09c390e33018d8ad3abf9fdb60608f19fdcd1f6a32abb5708e52b7f0808c67fb","observation_id":"6f827147-e9aa-4856-85de-77bfe5ba4a41","resolution":{"observed_at":"2026-08-08T16:19:18.449377Z","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":"2026-08-08T16:19:18.963217Z","title":"Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example,","venue":null,"work_id":"4c4ca6b8-cfcb-4162-8de2-3f18930f762d","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.452423Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:3511c2439570186f61f9ab99f9f367068ea06613f3e5ae108680dafa1b47c022","observation_id":"f42bbc71-894b-4e70-9bf5-45547fa117fd","resolution":{"observed_at":"2026-08-08T16:19:18.967194Z","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":"2026-08-08T16:19:18.953442Z","title":"Breast cancer image classification method based on deep transfer learning,","venue":null,"work_id":"52c3d3ff-6d9e-4c9a-a3f6-79c04568cf29","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.455545Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:0e7448b040bc067ad70eb97fcac2f5d7b128edfcd37db0f902c91b2c65bef34e","observation_id":"d8ee726e-49c7-495f-9dce-17eb0479e987","resolution":{"observed_at":"2026-08-08T16:19:18.956739Z","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":"2026-08-08T16:19:18.943199Z","title":"Performance Boost in Deep Neural Networks: Improved ResNext50 for Complex Image Datasets,","venue":null,"work_id":"4e88c03a-1828-487b-b105-af3b2b1d50f4","year":2025},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.459641Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:88b2ab11513246aa3d67ce8d171a14350824556b39e51c8c171e8f452c928a0c","observation_id":"f8c433e0-57d9-4f71-8433-a67efa41a3b2","resolution":{"observed_at":"2026-08-08T16:19:18.947061Z","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":"2026-08-08T16:19:18.462881Z","title":"Mining Multimodal Data with Sparse Decomposition and Adaptive Weighting,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.462881Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:1495700677094c010bd1223091487ec2b194cf7f816937f3d793e323f634d4dd","observation_id":"c6ad87b0-9e0e-4941-b14f-18b79a628f94","resolution":{"observed_at":"2026-08-08T16:19:18.462881Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19449","last_updated":"2024-12-27T04:37:06Z","snapshot_observed_at":"2026-07-06T20:13:36.042546Z","submitted_at":"2024-12-27T04:37:06Z","title":"Feature Alignment-Based Knowledge Distillation for Efficient Compression of Large Language Models","version":1},"cited_work":{"arxiv_id":"2412.19449","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.19449","snapshot_observed_at":"2026-08-08T16:19:18.733386Z","title":"Feature Alignment-Based Knowledge Distillation for Efficient Compression of Large Language Models","venue":"cs.CL","work_id":"a92c0617-bf0c-4e0d-aaa2-a09f533ae170","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.465692Z"},"links":{"cited_paper":"/paper/2412.19449","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:e64cbb8affc4463af91f365c40b924b69cdd276e06f48983b3bf8f6c686cd2d8","observation_id":"1db69827-6ecb-4109-b6ff-002784a7267f","resolution":{"observed_at":"2026-08-08T16:19:18.737208Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2412.19420","last_updated":"2024-12-27T03:13:13Z","snapshot_observed_at":"2026-07-06T20:13:31.499259Z","submitted_at":"2024-12-27T03:13:13Z","title":"A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets","version":1},"cited_work":{"arxiv_id":"2412.19420","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.19420","snapshot_observed_at":"2026-08-08T16:19:18.720719Z","title":"A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets","venue":"cs.DB","work_id":"b876b717-474f-4441-a684-807863b11abf","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.499654Z"},"links":{"cited_paper":"/paper/2412.19420","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:95e4f26e70870309a29b1dbbce3a0098b81c4a92bc3e0106a8acb32bbf047b1a","observation_id":"32d1a750-0460-42eb-b7ae-a936708cc833","resolution":{"observed_at":"2026-08-08T16:19:18.724208Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2412.14521","last_updated":"2024-12-19T04:37:47Z","snapshot_observed_at":"2026-07-06T20:09:42.677491Z","submitted_at":"2024-12-19T04:37:47Z","title":"Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders","version":1},"cited_work":{"arxiv_id":"2412.14521","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.14521","snapshot_observed_at":"2026-08-08T16:19:18.707545Z","title":"Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders","venue":"cs.HC","work_id":"6a7bf777-a38e-4bc4-a153-278c86c48715","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.540580Z"},"links":{"cited_paper":"/paper/2412.14521","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:5e7e753e39d44346ba03878ca3bee5e6c52a639fdd4fa3dfc5079670dd461c51","observation_id":"c17d0bb6-4954-46f2-8f5a-47f8c45fc28a","resolution":{"observed_at":"2026-08-08T16:19:18.711501Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-08T16:19:18.928360Z","title":"Contextual Analysis Using Deep Learning for Sensitive Information Detection,","venue":null,"work_id":"09f22992-127a-44d4-a18c-886fa8140c70","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.580853Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:aab99700a066af39d38539762b814f578462e81effc37214228df5f219b1db96","observation_id":"45e9de05-5389-4aef-b621-e44cd85e3626","resolution":{"observed_at":"2026-08-08T16:19:18.931893Z","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":"2412.15593","last_updated":"2024-12-20T06:32:05Z","snapshot_observed_at":"2026-07-06T20:10:41.978020Z","submitted_at":"2024-12-20T06:32:05Z","title":"Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15593","snapshot_observed_at":"2026-08-08T16:19:18.583647Z","title":"Machine Learning Techniques for Pattern Recognition in High - Dimensional Data Mining,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.583647Z"},"links":{"cited_paper":"/paper/2412.15593","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:4808057a473e5984a92a7a80862c717077db9fad68c678c1f84b16e6ada6cc0f","observation_id":"557743bf-b57e-4070-85b0-56cdffbb9e76","resolution":{"observed_at":"2026-08-08T16:19:18.583647Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05536","last_updated":"2024-12-07T04:38:44Z","snapshot_observed_at":"2026-07-06T20:03:11.541819Z","submitted_at":"2024-12-07T04:38:44Z","title":"Comprehensive Evaluation of Multimodal AI Models in Medical Imaging Diagnosis: From Data Augmentation to Preference-Based Comparison","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05536","snapshot_observed_at":"2026-08-08T16:19:18.586735Z","title":"Comprehensive Evaluation of Multimodal AI Models in Medical Imaging Diagnosis: From Data Augmentation to Preference -Based Comparison,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.586735Z"},"links":{"cited_paper":"/paper/2412.05536","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:2baa637a95babbe0ee25c888f251925fd27ca90352b24c871c2da42cc0a3bcc3","observation_id":"328661ed-1577-499c-adb3-d78b4ea74dfe","resolution":{"observed_at":"2026-08-08T16:19:18.586735Z","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":"2026-08-08T16:19:18.918622Z","title":"Survival prediction across diverse cancer types using neural networks","venue":null,"work_id":"0bd2ad88-61c1-4c45-bcdf-29d867e8307a","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.589959Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:36bdda7f6e609ec67e7d4c0dc26234430c338c653b047eeeea7fe2663e4b2980","observation_id":"539dc2a8-7b17-4d80-9377-00b5a030c599","resolution":{"observed_at":"2026-08-08T16:19:18.922486Z","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":"2026-08-08T16:19:18.909981Z","title":"Transformers in vision: A survey,","venue":null,"work_id":"55a4f133-9dbf-46d9-ab79-bef11f56f704","year":2022},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.650600Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:f8062b05fd4481695ba610768a17869baea8eef9ab94b06c8a3ef3e895b437c6","observation_id":"fb88d5b3-5dd0-4029-a14a-6ec18d07e256","resolution":{"observed_at":"2026-08-08T16:19:18.913118Z","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":"2412.20345","last_updated":"2024-12-29T04:07:58Z","snapshot_observed_at":"2026-07-06T20:14:12.724584Z","submitted_at":"2024-12-29T04:07:58Z","title":"Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data","version":1},"cited_work":{"arxiv_id":"2412.20345","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.20345","snapshot_observed_at":"2026-08-08T16:19:18.677673Z","title":"Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data","venue":"cs.CV","work_id":"0f6eda13-605f-4f22-bf58-9dd309deeaf2","year":2024},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.653753Z"},"links":{"cited_paper":"/paper/2412.20345","citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:c97644873b4b7ab2115002b415759050f435eafdea9b81dfc07deabf389a45e4","observation_id":"141ae286-eafa-4bb3-a8eb-880ba5b7bfba","resolution":{"observed_at":"2026-08-08T16:19:18.683051Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-08T16:19:18.899816Z","title":"SE -ResNeXt-50-CNN: A Deep Learning Model for Lung Cancer Classification,","venue":null,"work_id":"4db94686-5a0b-4bc6-bf74-61c7d242bc34","year":2025},"citing_paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T16:19:18.656746Z"},"links":{"citing_paper":"/paper/2502.06243"},"observation_digest":"sha256:b316a6e8ad2c6243633747c5be150e416c20fe349c40867cb352ac6da37161bb","observation_id":"6d7bb907-0045-4864-bda8-11659a2afb07","resolution":{"observed_at":"2026-08-08T16:19:18.903724Z","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"}}],"paper":{"arxiv_id":"2502.06243","last_updated":"2025-02-10T08:22:25Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T16:14:23.626345Z","submitted_at":"2025-02-10T08:22:25Z","title":"Multi-Scale Transformer Architecture for Accurate Medical Image Classification"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":6,"verified_fuzzy":12},"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":"2026-08-09T06:31:02.800959+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 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2502.06243."}