{"as_of":"2026-08-18T18:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:35a7e739404576030683de4d023358f84339491f4b3109d4ccf1939a76ff4d3b","coverage":[{"denominator":51,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T21:43:59.091234Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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/2507.02959/citation-record","integrity":"/paper/2507.02959/integrity","json":"/paper/2507.02959/citation-record.json","paper":"/paper/2507.02959"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:44:08.468998Z","title":"Vision transformers for remote sensing image classification","venue":null,"work_id":"fa5ffbd0-ca50-4637-a5b1-008bb77eab0c","year":2021},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.110182Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:c9ab495da4afb567634c9638429a61f95d0c1255c69bb02e7f1273a6a3da8bff","observation_id":"1cb53df8-2e03-4802-a340-0cc04d717e8f","resolution":{"observed_at":"2026-08-06T21:44:08.558649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:08.195540Z","title":null,"venue":null,"work_id":"1c58dbfe-ec13-4075-bb9d-3bb5de5353c7","year":2022},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.176211Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:d49d4aff37395241bdd4b5cd274bbe5116476842073af991911bf3e68cd6f890","observation_id":"65a8740c-c4f2-4394-b767-5beda7eaad13","resolution":{"observed_at":"2026-08-06T21:44:08.368832Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:07.912468Z","title":"Cnn-lstm and transfer learning models for malware classification based on opcodes and api calls","venue":null,"work_id":"06ef47ad-86f8-48ba-83fd-d98ffd03eea8","year":2024},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.241234Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:eb75938e1a178bda5d7173c92438fd578308759a2347e57790bed7731478ec7f","observation_id":"212c6b07-74f0-4da7-b245-bd40306158eb","resolution":{"observed_at":"2026-08-06T21:44:08.034423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:07.639786Z","title":"Optimized detection of cyber-attacks on iot networks via hybrid deep learning models","venue":null,"work_id":"d537553c-3b94-4d5f-b773-165c0e12e9e2","year":2025},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.294592Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:08ee31be19453e474e3bb50c7ff260d77df4d3f73557e943c51029d2f910ab32","observation_id":"d744a2bc-dd6a-4efe-9c6b-56d4b321f4a1","resolution":{"observed_at":"2026-08-06T21:44:07.728559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:07.406709Z","title":"A survey of malware detection using deep learning","venue":null,"work_id":"8db5da85-0baf-4a66-bee4-e99b44c383e6","year":2024},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.378440Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:76730396cf6f9eab5ac4305e36bac3a7b9f5daeac9519c4cd935edbd31f86dfa","observation_id":"429d7ebe-da5d-491d-931d-7a9e90f047a5","resolution":{"observed_at":"2026-08-06T21:44:07.505740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:07.188568Z","title":"Understandingrobustnessoftransformersforimage classification, in: Proceedings of the IEEE/CVF international conference on computer vision, pp","venue":null,"work_id":"2d6ce43e-464e-4c1f-8450-ef5c57d19580","year":2021},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.435648Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:3cb8a45371644d3f83e1fe8f97d5710c67fbf6fc1598f5a47a754bec38cae7bd","observation_id":"9d6beb15-ee16-4e54-9444-7f83f2a0eb72","resolution":{"observed_at":"2026-08-06T21:44:07.274530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:07.005655Z","title":"Weight uncertainty in neural network, in: International conference on machine learning, PMLR","venue":null,"work_id":"f0a8242f-146c-411d-a160-2f1011c4501c","year":2015},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.523071Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:293ae4715f84ccbeebcf81ce643681372d6a44b60d2eec38ba619c203e2c661d","observation_id":"8ffd1afe-e50d-4043-9418-04a150d148ee","resolution":{"observed_at":"2026-08-06T21:44:07.079627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"3836.2021","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:43:59.899544Z","title":null,"venue":null,"work_id":"a0eef074-a4b2-41d8-9832-21107eecfb0d","year":2021},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.617789Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:d2d76b3ce45217d01c77a091fd99de2efbeff775e4c4b67f80424f9be0542852","observation_id":"8b9967a3-e804-4e4a-aac1-89b7b266685f","resolution":{"observed_at":"2026-08-06T21:43:59.964170Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:06.824644Z","title":"End-to-end object detection with transformers, in: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part I 16, Springer","venue":null,"work_id":"c0ff54f6-775c-4c8d-901f-10fca9b7e7fc","year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.714327Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:9dac28e5778b6d3747b44f7e45dd1d01b7a9dce5644a0af7642b510a6da446dd","observation_id":"4be177cb-a34c-479a-a12a-0e48bc020c14","resolution":{"observed_at":"2026-08-06T21:44:06.889101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:06.644970Z","title":"Crossvit: Cross-attention multi-scale vision transformer for image classification, in: Proceedings of the IEEE/CVF international conference on computer vision, pp","venue":null,"work_id":"d8547636-96ee-49fd-a7a9-cb22045b4295","year":2021},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.793638Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:d8536a59cf5b1e1cebd7b355a148a9ca4b3231ed1c54f4482f7183dd914b8b80","observation_id":"ef24f99b-0c8d-45dc-a2a1-bff475fe938b","resolution":{"observed_at":"2026-08-06T21:44:06.721688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:06.442085Z","title":"Malware family classification using active learning by learning, in: 2020 22nd International Conference on Advanced Communication Technology (ICACT), IEEE","venue":null,"work_id":"a03029f9-097d-4bcb-9d03-a867976e6e86","year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:55.897438Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:2fdaf3be94fa163415f1593084abf05e152a9aeb9b9f725fd5a69f9bfb34da92","observation_id":"36f16064-7435-4c4c-a60c-02b869664cc1","resolution":{"observed_at":"2026-08-06T21:44:06.528545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:06.225419Z","title":"Semi-supervised active learning for object detection","venue":null,"work_id":"bcebcb5c-7c1b-4aef-84a2-ae9853b877ca","year":2023},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.020905Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:b4a2d274c3efdae6eaf937300986314728320b3aa7e8eba851b8befc3e54b5b5","observation_id":"02dc6115-02b8-4668-ae66-562a7f4e945c","resolution":{"observed_at":"2026-08-06T21:44:06.330779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:06.058338Z","title":null,"venue":null,"work_id":"c1f2cef7-3321-40b8-8db6-0a1b618db39c","year":2019},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.145409Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:239f1f5917c128130246a14496cc32fe8daa4a29508f48223e0e32c8adfca54f","observation_id":"0d055703-5f3e-4291-82ee-e2effd585227","resolution":{"observed_at":"2026-08-06T21:44:06.142154Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:05.881256Z","title":"A novel transfer learning based approach for pneumonia detection in chest x-ray images","venue":null,"work_id":"945b585a-3753-4146-885d-052fe582f5d9","year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.241587Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:bc68b1c19f85148211c1810fa6ae37d3e490fe51147b3b9902c1e9621b7c424b","observation_id":"35d146f0-41a1-44ba-b4df-669e5ef77db9","resolution":{"observed_at":"2026-08-06T21:44:05.953272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:05.721399Z","title":"Active learning-based mobile malware detection utilizing auto-labeling and data drift detection, in: 2024 IEEE International Conference on Cyber Security and Resilience (CSR), IEEE","venue":null,"work_id":"40809971-9df5-4b02-98a1-3171f3939fb6","year":2024},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.331654Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:5849fa0210dbb2e4caa6f4e7c3cd1f9102ab4b1477bde978534177072c259d54","observation_id":"d6b12671-ef53-4da5-97ff-c120fa09049e","resolution":{"observed_at":"2026-08-06T21:44:05.808146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-16T09:25:53.087782Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-06T21:43:56.411835Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.411835Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:c5e19a5306b4c74a7493645588a0a4e5a48ec13e09c27f30eeee1ae55313dae0","observation_id":"2042d74c-9d34-424b-8c9d-26d26f6a3e87","resolution":{"observed_at":"2026-08-06T21:43:56.411835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.02425","last_updated":"2020-02-20T01:08:22Z","snapshot_observed_at":"2026-08-14T16:20:02.780241Z","submitted_at":"2019-06-06T05:40:25Z","title":"Uncertainty-guided Continual Learning with Bayesian Neural Networks","version":2},"cited_work":{"arxiv_id":"1906.02425","doi":null,"metadata_source":"pith","pith_arxiv_id":"1906.02425","snapshot_observed_at":"2026-08-06T21:43:59.612149Z","title":"Uncertainty-guided Continual Learning with Bayesian Neural Networks","venue":"cs.LG","work_id":"6c420ea2-36e6-4628-a69b-6b2d2b3d28fd","year":2019},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.480993Z"},"links":{"cited_paper":"/paper/1906.02425","citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:7b9e5507d9826f58dd49479d4c63185100ba8a33b84029fb69d82868024c2eff","observation_id":"d7a1a762-78f9-491c-90a4-509e765a2ce2","resolution":{"observed_at":"2026-08-06T21:43:59.682089Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:05.507645Z","title":"Efficientclassificationofimbalancednaturaldisastersdatausinggenerativeadversarial networks for data augmentation","venue":null,"work_id":"e9f0f5e9-2824-436c-b9a5-93df927e0eaa","year":2023},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.542688Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:a01097739ed9a165a5813555147d84a0f9fb3ecf5816f9653efa532df2a76551","observation_id":"12205b36-bf60-4361-b14f-b4b956975b89","resolution":{"observed_at":"2026-08-06T21:44:05.617827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:05.362719Z","title":"Multiscale vision transformers, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp","venue":null,"work_id":"b55c5b9a-8d60-4417-9946-c5374957f0e4","year":2021},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.606067Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:f8fed99526c0cbbb57e28059d20c50dd110bd8c4fa9a5bfbf9e128bd0c6a3e9f","observation_id":"d2d0e39d-cbf2-4a21-aca5-8e32e585c898","resolution":{"observed_at":"2026-08-06T21:44:05.426872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:05.233740Z","title":"On the expressiveness of approximate inference in bayesian neural networks","venue":null,"work_id":"35869921-7e96-4a94-93be-0126544d1e90","year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.654837Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:2df77b38463e4ceaa3db4ef2474295d1d2a196a541dfd29d5c0d01a2792aadc0","observation_id":"ddde4ce2-755c-4f11-95ee-dccf4ce2b3db","resolution":{"observed_at":"2026-08-06T21:44:05.288004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:05.029801Z","title":"Expertsstillneeded:boostinglong-termandroidmalwaredetectionwithactivelearning","venue":null,"work_id":"608e3574-09f2-46a1-a536-5b40a5a11e05","year":2024},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.745470Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:59a4f511c91e827c68538feff2540f52944a9703501a64afc57634d999613c6d","observation_id":"973fd5fb-5ee0-404c-8cca-44ff415eb745","resolution":{"observed_at":"2026-08-06T21:44:05.106407Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:04.873175Z","title":"Evidential uncertainty sampling strategies for active learning","venue":null,"work_id":"0c4699a3-767e-4104-ae31-5dfd26190677","year":2024},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.834714Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:f859f5225c4fd70cd439d5cdd3f6806999ae98ce124b79db2495f71c4cc8deec","observation_id":"be7ad5d3-e4df-48ad-b7b0-f762848c502b","resolution":{"observed_at":"2026-08-06T21:44:04.955010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.02666","last_updated":"2020-11-05T05:22:58Z","snapshot_observed_at":"2026-08-16T19:07:59.798425Z","submitted_at":"2020-11-05T05:22:58Z","title":"Deep Active Learning with Augmentation-based Consistency Estimation","version":1},"cited_work":{"arxiv_id":"2011.02666","doi":null,"metadata_source":"pith","pith_arxiv_id":"2011.02666","snapshot_observed_at":"2026-08-06T21:43:59.429903Z","title":"Deep Active Learning with Augmentation-based Consistency Estimation","venue":"cs.CV","work_id":"bccc478b-2bdb-4d9c-9728-a28edad20b87","year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.911124Z"},"links":{"cited_paper":"/paper/2011.02666","citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:692da30a4452db2e8d8cf8cc0c31693367fb4ade1921fd131b0d77b3d4617fdb","observation_id":"3bfbc1bf-0235-4dc5-8371-b2f16ae03756","resolution":{"observed_at":"2026-08-06T21:43:59.507409Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:04.673788Z","title":"Uncertainty-driven active developmental learning","venue":null,"work_id":"5526eb9f-fc79-4fd0-a1b8-a5df4b15f6a7","year":2024},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:56.981122Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:bd01df96a5c86bb2e46d8936b0f090b2e4766099bfcb2c2760c5a76c9e82e7e8","observation_id":"5d908f0f-75a3-471f-9c93-54b5bc315888","resolution":{"observed_at":"2026-08-06T21:44:04.765277Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:04.515303Z","title":"Deepactivelearningwithweightingfilterforobjectdetection","venue":null,"work_id":"0681baf9-b268-4cd2-be02-e9ea7e2570ec","year":2023},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.054962Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:830405b8a93e935849cd0a2fc2292676b37949ce4642e4853afae38c4bf9e888","observation_id":"3a962f89-0d06-423f-9e63-944e26a79066","resolution":{"observed_at":"2026-08-06T21:44:04.575484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:04.335839Z","title":"Whatuncertaintiesdoweneedinbayesiandeeplearningforcomputervision? Advancesinneuralinformation processing systems 30","venue":null,"work_id":"1ecbcaf9-b63c-420a-a407-1b70bccb5be9","year":2017},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.155157Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:9471378a04fe7f21a540c036fc7ef9478193bc6bf5c2191641b78564e2699789","observation_id":"4dce9436-c9e0-4933-9bbd-620621d0b08d","resolution":{"observed_at":"2026-08-06T21:44:04.429213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:04.147569Z","title":"Active learning for data quality control: A survey","venue":null,"work_id":"184ff10b-4cb5-4622-9852-975ef625c9da","year":null},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.233351Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:711a939a6accd567143cb0f873434f521c182793fb624b6bad896ad07cd82916","observation_id":"ff7b7b7f-750f-4bbb-903d-73ab29fe1bd2","resolution":{"observed_at":"2026-08-06T21:44:04.211137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:03.984716Z","title":"Unlabeleddataselectionforactivelearninginimageclassification","venue":null,"work_id":"714ee597-fe5f-4d37-b964-72400eb1c25c","year":null},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.301834Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:e2ab86db4a254ef6110e16da76c96c8fc1b027fff14daca4fd303dbdf40e8417","observation_id":"c1105461-aaf2-4977-913f-ec5e9850de03","resolution":{"observed_at":"2026-08-06T21:44:04.069248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:03.777607Z","title":"Deepactivelearningwithnoisestability,in:ProceedingsoftheAAAI Conference on Artificial Intelligence, pp","venue":null,"work_id":"4829ef9b-50be-45e6-bc23-90b840df9976","year":null},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.388218Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:2d16dea9127fdc33c0b3882e71987e83d7346d58d160e0e94b58393218d654e8","observation_id":"8397844b-c14b-4096-8179-d3d8fe1169bc","resolution":{"observed_at":"2026-08-06T21:44:03.876748Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:03.596190Z","title":"Uncertainty-aware twin support vector machines","venue":null,"work_id":"de1b32db-9d4f-4ede-8710-9f73f8229002","year":2022},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.503730Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:3c036ecbae2beb91f956f200eba1b08bc7fd756a6caf972aea89668c1af854e4","observation_id":"371576ba-de65-4fa3-be6d-446758b2f2f5","resolution":{"observed_at":"2026-08-06T21:44:03.682815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.00157","last_updated":"2021-09-02T04:12:13Z","snapshot_observed_at":"2026-08-16T18:54:48.483706Z","submitted_at":"2021-01-01T03:43:36Z","title":"Active Learning Under Malicious Mislabeling and Poisoning Attacks","version":4},"cited_work":{"arxiv_id":"2101.00157","doi":null,"metadata_source":"pith","pith_arxiv_id":"2101.00157","snapshot_observed_at":"2026-08-06T21:43:59.264649Z","title":"Active Learning Under Malicious Mislabeling and Poisoning Attacks","venue":"cs.LG","work_id":"df912276-9869-404a-b8bd-18fd35a9b3ce","year":2021},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.578245Z"},"links":{"cited_paper":"/paper/2101.00157","citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:673c9b695525c758b0b7dc7ba75558a8e24965ad1e25b209b7ce6e52dc7577e7","observation_id":"5d041f0c-db9a-4990-bfd4-b97e569dcf58","resolution":{"observed_at":"2026-08-06T21:43:59.330267Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:03.443408Z","title":"Multiplicative normalizing flows for variational bayesian neural networks, in: International Conference on Machine Learning, PMLR","venue":null,"work_id":"65a66100-4b76-4f0e-8a0b-590457f33aba","year":2017},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.642676Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:d30761095ed2a4343579d232c9c18488283f761d1b7cd4140abeb9786143c5da","observation_id":"71d04b2d-f1be-4313-9403-4814e9e53239","resolution":{"observed_at":"2026-08-06T21:44:03.517387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:03.276977Z","title":"Multisurface proximal support vector machine classification via generalized eigenvalues","venue":null,"work_id":"6ed138f8-227c-43da-b3e3-9f90be1fd315","year":2005},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.722758Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:eb6fcab0b60ef72786fc41956c8cf492cc797d063c79d27b2408ee714a789d4f","observation_id":"b4be03dc-e7b8-4ba6-865a-441ec40b2c3b","resolution":{"observed_at":"2026-08-06T21:44:03.365181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:03.095092Z","title":"Adecadesurveyoftransferlearning(2010–2020)","venue":null,"work_id":"504c94d5-f7d0-44a5-8232-f447425e6de0","year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.814274Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:84e57dc8f5e26338e96506f16129d16854d35de7bbfcbf007cde0946c7537fba","observation_id":"041d3a48-69f1-4858-9144-32e25f651050","resolution":{"observed_at":"2026-08-06T21:44:03.170559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:02.903332Z","title":"What is a support vector machine? Nature biotechnology 24, 1565–1567","venue":null,"work_id":"febbdbfe-b8cd-4caf-b5e8-8ac01ce4926f","year":2006},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:57.907190Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:bd920742098f4ce53ce1a6fddbbc70020d8b4c8bf927eaeffb5d9a3e962a71ed","observation_id":"b6d5404a-2a7a-4d58-990c-56fc094e03e4","resolution":{"observed_at":"2026-08-06T21:44:02.991515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:02.674766Z","title":"Activelearningforobjectdetectionwithevidentialdeeplearningandhierarchical uncertainty aggregation, in: The Eleventh International Conference on Learning Representations","venue":null,"work_id":"e960e313-9236-4b76-ac98-7a51b22a6376","year":2023},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.007507Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:33e01f7c87fe79936fe42014dd8f0587cdff72227ce8b5c3e9b44b0030fb4f84","observation_id":"1ab1b401-81fe-40a3-a051-4e9b0d3d6c04","resolution":{"observed_at":"2026-08-06T21:44:02.776905Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:02.477893Z","title":"Active learning literature survey","venue":null,"work_id":"ffadf1b0-701c-4fd1-aea3-b586443a8638","year":2009},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.077502Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:0b2159ce54bfa33e2d5d49a43b120f0de7aa44bec199fc5fc6af8345be2b8d35","observation_id":"fd948a61-e082-4f4f-b8a4-507955a4c2d9","resolution":{"observed_at":"2026-08-06T21:44:02.563922Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:02.324117Z","title":"A mathematical theory of communication","venue":null,"work_id":"3fdb5d58-ae60-4d4a-ad2f-a03532236e0a","year":2001},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.138603Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:47c5d973948dbc681c7ada8db65566fd84a91cbf037b658032264cee331c9049","observation_id":"23a912ca-0ac8-4f9e-b494-84ba9270699f","resolution":{"observed_at":"2026-08-06T21:44:02.388081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:02.160925Z","title":"Improvements on twin support vector machines","venue":null,"work_id":"afc0df6f-e3a5-4dba-ace5-9d80a79c80c4","year":2011},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.223926Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:86fb4a97127f2469e6b82a4f18376a5ed5908b7e0f9b41f077d777020d568c51","observation_id":"d2d6cf48-b0e4-4ea1-bcac-dc964cab9976","resolution":{"observed_at":"2026-08-06T21:44:02.240123Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:01.950173Z","title":"Rethinking deep active learning: Using unlabeled data at model training, in: 2020 25th International conference on pattern recognition (ICPR), IEEE","venue":null,"work_id":"9e46f6d2-9cb3-47c3-9f29-5252634a41cc","year":2021},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.286206Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:e0aa98e22753e4f92ac9fac26cf1060f88874097450aa1728065d08135a78fb0","observation_id":"f5db5576-e5fa-46ba-8af7-94fa6447021c","resolution":{"observed_at":"2026-08-06T21:44:02.034329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:01.791322Z","title":"Inception-v4,inception-resnetandtheimpactofresidualconnectionsonlearning, in: Proceedings of the AAAI Conference on Artificial Intelligence, pp","venue":null,"work_id":"cbb296f1-d6a8-46af-943b-4ca82bb209d7","year":2017},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.332964Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:47e3f27482077cc56484399b34e778f29990e67d170404bea40a80a35a5d1dde","observation_id":"388ee4b6-dd76-4f80-b37f-14846f3fa1d0","resolution":{"observed_at":"2026-08-06T21:44:01.874727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:01.630261Z","title":null,"venue":null,"work_id":"bfd43299-6230-4031-a613-bff3dd2c8e03","year":2018},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.411687Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:0db302aad71b553e6569d03578e8c75cc384b021bb8b1dd300875616156ae473","observation_id":"4f4da4fc-43dc-460b-9365-58db4fb2641e","resolution":{"observed_at":"2026-08-06T21:44:01.687460Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:01.418288Z","title":null,"venue":null,"work_id":"74f3a58c-155a-4e5a-aea4-ef3be1742c3e","year":2018},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.475382Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:4f14f02a4ca0a657ea385f0514a2d71d012a31079a96e91939d7e0f974d10c40","observation_id":"17990291-435f-491a-ab33-9eae5d41eae0","resolution":{"observed_at":"2026-08-06T21:44:01.532097Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:01.253884Z","title":"Fixing the train-test resolution discrepancy","venue":null,"work_id":"3e4b06dd-cc9e-4add-8710-2e6e4e9cfd0c","year":2019},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.551344Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:48b8193b0dc0b20f494c01dc92e78fe58c4f9e05c5d4dffc8e6b6fb8698f13be","observation_id":"b8a1e100-4920-49b5-9d20-1cfe2a823853","resolution":{"observed_at":"2026-08-06T21:44:01.312318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:01.053519Z","title":"Eigenfaces for recognition","venue":null,"work_id":"19b6ee3c-0ce4-4a86-83e2-2cec880ede1b","year":1991},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.636500Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:72924ef9877bd2aaf03ae1a1a9a79a222b777ea008423841cfb458e2fb808883","observation_id":"54322502-3742-4b24-9da2-b33b5479b32f","resolution":{"observed_at":"2026-08-06T21:44:01.147412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:00.887434Z","title":"Linear maximum margin classifier for learning from uncertain data","venue":null,"work_id":"620c8231-4c56-4602-b6ef-b6d49c0ad42e","year":2017},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.722793Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:4a7c70d9d3d85ac57d6235b868f10bd600ea8b93f1f79638f207239037cfa6a1","observation_id":"6250c920-c1da-45ed-8965-083db1982776","resolution":{"observed_at":"2026-08-06T21:44:00.969436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:00.681764Z","title":"Tokens-to-token vit: Training vision transformers from scratch on imagenet, in: Proceedings of the IEEE/CVF international conference on computer vision, pp","venue":null,"work_id":"dfd567c4-8c07-44b2-820c-eef971d8609b","year":null},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.796623Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:ed9172861af5f09caaf617eaf3f78f5026b92325fe697129320b04af7ba94e2a","observation_id":"c05dc242-e29a-4aed-879d-07c6c9a23be9","resolution":{"observed_at":"2026-08-06T21:44:00.756022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:00.498638Z","title":"Multiple instance active learning for object detection, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"30dd3823-26ff-4c55-a2cc-92362cca6c03","year":null},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.863502Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:8049fdab94ab973832dba29a92ba8ce999e2d81cafa9ecaae72a487d1a8fce76","observation_id":"1d050640-1505-4247-a452-35298b9b2d0b","resolution":{"observed_at":"2026-08-06T21:44:00.602142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.03932","last_updated":"2020-05-11T20:49:28Z","snapshot_observed_at":"2026-08-15T15:12:35.516468Z","submitted_at":"2019-02-11T15:03:30Z","title":"Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.03932","snapshot_observed_at":"2026-08-06T21:43:58.958090Z","title":"Cyclical stochastic gradient mcmc for bayesian deep learning","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:58.958090Z"},"links":{"cited_paper":"/paper/1902.03932","citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:43e9fee1382f7c86f656e9e32ca8245134489b22291df86f811a8bcef01a1f74","observation_id":"4048b4c3-2a9b-4016-9afc-ce3abb607051","resolution":{"observed_at":"2026-08-06T21:43:58.958090Z","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":"2026-08-06T21:44:00.288257Z","title":"Active learning based on belief functions","venue":null,"work_id":"de65b6a2-7de9-4e0d-8245-78e88895e21d","year":2020},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:59.027888Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:b392b77e2dc793ddae5a287363902a99ba6a35304be70ac3a58dccbb37d31b61","observation_id":"5a383b4a-f769-4a66-ad82-c723f3ad5931","resolution":{"observed_at":"2026-08-06T21:44:00.384816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-06T21:44:00.076699Z","title":"Powersvm:Generalizationwithexemplarclassificationuncertainty,in:2012IEEEConference on Computer Vision and Pattern Recognition, IEEE","venue":null,"work_id":"530c7640-a6e3-493d-bf0d-b8e4aa245e7b","year":2012},"citing_paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T21:43:59.091234Z"},"links":{"citing_paper":"/paper/2507.02959"},"observation_digest":"sha256:b4d1f4616586978c8780cae01eb4b29c801017a79b19d74872a08f7dcfdacbd4","observation_id":"4a43b9a2-55d4-456f-979f-dcd1ebd0e2dc","resolution":{"observed_at":"2026-08-06T21:44:00.191222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.02959","last_updated":"2025-06-30T04:18:31Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-14T02:40:12.409358Z","submitted_at":"2025-06-30T04:18:31Z","title":"A Novel Active Learning Approach to Label One Million Unknown Malware Variants"},"reference_resolution":{"displayed":51,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":4,"verified_fuzzy":41},"total_outbound_references":51},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2507.02959."}