{"as_of":"2026-08-19T05:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b796c0c2782486f6879b5544b0432552c0b1351993f23f9338a13ce7a52fefbd","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:42:35.760858Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"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/2507.04929/citation-record","integrity":"/paper/2507.04929/integrity","json":"/paper/2507.04929/citation-record.json","paper":"/paper/2507.04929"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:42:36.332168Z","title":"A survey on active learning and human-in-the-loop deep learning for medical image analysis.Medical image analysis, 71:102062, 2021","venue":null,"work_id":"a06be059-346b-4a6a-b276-64faa6524386","year":2021},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.583013Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:9573a364c79a6f7e3214bc7fd0db1536a58432251d72ac6b0280d5c875deb04d","observation_id":"c720e496-273b-4aec-891f-7710a921dc0d","resolution":{"observed_at":"2026-08-06T19:42:36.336808Z","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":"2026-08-06T19:42:36.319309Z","title":"Active learning for improved semi-supervised semantic segmentation in satellite images","venue":null,"work_id":"7aa20a22-2c55-4272-aff0-2544b3886b98","year":2022},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.593745Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:c66858556c3f79942c769c0b5dec41cc97e4169e8f6a4d64b792ffc945bbd1b3","observation_id":"4a6dfd13-ba88-4bc8-a806-a3a9abdd7fde","resolution":{"observed_at":"2026-08-06T19:42:36.323476Z","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":"2026-08-06T19:42:36.305365Z","title":"Active learning for structural reliability: Survey, general framework and benchmark","venue":null,"work_id":"75759e7d-2bb2-4707-8581-a9a46180eefb","year":2022},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.598012Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:8c6b646fcbe5973ab3bea185c98a7df416b362c63dcc967eca950f8babf38967","observation_id":"a8d74639-0d06-4b2d-8808-c202f4382d33","resolution":{"observed_at":"2026-08-06T19:42:36.310423Z","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":"2026-08-06T19:42:36.292270Z","title":"Deep Bayesian active learning with image data","venue":null,"work_id":"3f7049a1-b1d7-4fcb-a4a9-b4c07fa750d9","year":2017},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.602437Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:d7881dd84f783b06ad4c9efc7b38b8f47e4aff1a55cb59ffffe2c2808bf94d58","observation_id":"a04ecfcc-1a02-4611-88f8-343100fdf18f","resolution":{"observed_at":"2026-08-06T19:42:36.296548Z","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":"2026-08-06T19:42:36.279153Z","title":"Bayesian neural networks and density networks","venue":null,"work_id":"5c7fc7e6-ac68-4539-a2ca-c4ccc3233e68","year":1995},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.607081Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:98a5e0237604ddd43a7a33d16b4b934459f2653ffc1467e536bb6fad5315c014","observation_id":"d723624f-bf87-46ee-aeb2-ae02f6c022fd","resolution":{"observed_at":"2026-08-06T19:42:36.283400Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:42:35.611391Z","title":"Bayesian learning for neural networks , volume 118","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.611391Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:6d9b56c741eac72751d7eb1ca4c4ec4fe7bf3bd18f29fd1893a80329a65147b8","observation_id":"3d5a5be6-5d2d-45cc-9b6e-8d804a8b49cb","resolution":{"observed_at":"2026-08-06T19:42:35.611391Z","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":"2026-08-06T19:42:36.257982Z","title":"Deep Bayesian active learning-to-rank with relative annotation for estimation of ulcerative colitis severity","venue":null,"work_id":"1bd4ef09-677b-4441-9706-b6d82054b2ae","year":2024},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.615999Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:dde1855caea5ed314d9c245093a59231582475cd702ea142d281d8fd3f4827ea","observation_id":"1d8da37d-8ca5-4cc8-92dd-6f6b51062dcc","resolution":{"observed_at":"2026-08-06T19:42:36.262154Z","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":"2026-08-06T19:42:36.245772Z","title":"Active learning with convolutional neural networks for hyperspectral image classification using a new Bayesian approach","venue":null,"work_id":"238598a7-ef4f-429d-a34f-1e8f37e926e8","year":2018},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.619810Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:05967844fdbb30544eb0d7c27227d7786c077475899c7c2662729edfdc2fa232","observation_id":"204ba340-c3d3-409a-9c68-5ee721528afb","resolution":{"observed_at":"2026-08-06T19:42:36.249892Z","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":"1808.05697","last_updated":"2018-09-24T17:25:51Z","snapshot_observed_at":"2026-08-14T18:40:11.363706Z","submitted_at":"2018-08-16T22:46:40Z","title":"Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.05697","snapshot_observed_at":"2026-08-06T19:42:35.623810Z","title":"Deep Bayesian active learning for natural language processing: Results of a large-scale empirical study","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.623810Z"},"links":{"cited_paper":"/paper/1808.05697","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:29329489d7097a7b65f14ce0a7b5b8a68069f3ceddcdc93f23ff9ac6fb8cfdb6","observation_id":"f39d41b2-58ac-4189-9e09-67fae8f5113e","resolution":{"observed_at":"2026-08-06T19:42:35.623810Z","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":"2026-08-06T19:42:36.233341Z","title":"Challenges in Markov chain Monte Carlo for Bayesian neural networks","venue":null,"work_id":"d8d4b252-d08b-4c31-8590-7cad5be277c0","year":2022},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.628187Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:5b50890ec82dd43d9b62cc83afef44642c396394e6496d476adb742f33a8c570","observation_id":"21e1d8f5-77fc-4c33-9cff-fe384f13fdb5","resolution":{"observed_at":"2026-08-06T19:42:36.237529Z","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":"2026-08-06T19:42:36.220067Z","title":"A complete recipe for stochastic gradient MCMC","venue":null,"work_id":"ee7ce4c4-42a2-4c66-877f-9e5087bdd742","year":2015},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.632343Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:28ec9eb3cf6c93e4c264463fdaf1295f44a20e188e1ffbf14ed7bdc890e3e349","observation_id":"8fbdee78-05b3-433f-9a1c-337c13af30f2","resolution":{"observed_at":"2026-08-06T19:42:36.224980Z","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":"2026-08-06T19:42:36.207848Z","title":"Bayesian model comparison and backprop nets","venue":null,"work_id":"93709dff-caff-44d0-bd4c-77a738b8a076","year":1991},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.636340Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:11de5c1268e1bb56b9d107515efacff4f686560c46c5ebc6a9fa8214f0efa9b1","observation_id":"cf36c415-6b8d-4d42-8570-17a0c3cd5c9e","resolution":{"observed_at":"2026-08-06T19:42:36.211877Z","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":"2026-08-06T19:42:36.195316Z","title":"Dropout as a Bayesian approximation: Representing model uncertainty in deep learning","venue":null,"work_id":"04283f6c-3ba6-4173-95e0-0c0018381d9a","year":2016},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.640251Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:b2f7e051983a0b40792b35a9d32af30f5636bfbb147fe27fa503b6bedd870b63","observation_id":"665e2081-03a8-4c6b-8292-543d28247ea8","resolution":{"observed_at":"2026-08-06T19:42:36.199613Z","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":"2012.08044","last_updated":"2022-04-21T04:58:09Z","snapshot_observed_at":"2026-08-16T18:58:30.544032Z","submitted_at":"2020-12-15T02:06:07Z","title":"Deep Bayesian Active Learning, A Brief Survey on Recent Advances","version":2},"cited_work":{"arxiv_id":"2012.08044","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.08044","snapshot_observed_at":"2026-08-06T19:42:35.877797Z","title":"Deep Bayesian Active Learning, A Brief Survey on Recent Advances","venue":"cs.LG","work_id":"e2778465-3ec8-4c28-bbe5-5cba21abcb5c","year":2020},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.644187Z"},"links":{"cited_paper":"/paper/2012.08044","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:41a59990fbbb00658255347446cabe2e2635a37a02ebd4c416d734e12bc74dea","observation_id":"c2bce39a-15a8-41c1-90bd-692228e9dd87","resolution":{"observed_at":"2026-08-06T19:42:35.882165Z","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":"2026-08-06T19:42:36.183243Z","title":"A survey on Bayesian deep learning","venue":null,"work_id":"2dc54100-3cb2-4ae8-bc91-da4185835c5c","year":2020},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.648319Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:26a779537c5a3640191d7b9886dbc1ccd653ce761faccc843afa3a782699d91c","observation_id":"e2859f89-e0a0-4b15-af1f-2c709352a3f2","resolution":{"observed_at":"2026-08-06T19:42:36.187255Z","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":"2026-08-06T19:42:36.171090Z","title":"A review of uncertainty quantification in deep learning: Techniques, applications and challenges","venue":null,"work_id":"9722c86e-5151-44fe-ac63-f4c2523d44b0","year":2021},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.652284Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:74ba008be916c8ab76e6847d16440f95d37f20545e26b60fd14f99a223f92014","observation_id":"2e06ad73-57af-4e23-a11e-c91cf4ff5136","resolution":{"observed_at":"2026-08-06T19:42:36.175171Z","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":"2026-08-06T19:42:36.159067Z","title":"Uncertainty in deep learning","venue":null,"work_id":"49e54103-151e-4e20-a01f-95616c5f6ba9","year":2016},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.656165Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:b3b486e74cfff52e27c2c8373915455b727ef49735dc4cc9e45d98d69f8097d4","observation_id":"94d410a7-655d-41ba-b2d5-9b387a49a2ec","resolution":{"observed_at":"2026-08-06T19:42:36.162834Z","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":"2026-08-06T19:42:36.147466Z","title":"A mathematical theory of communication","venue":null,"work_id":"fb35214c-bbe6-46ab-bd76-b21aedc7ac61","year":1948},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.660089Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:7006ea24718ccea395aed1a3cbdd9ac4f96f8f03e98374f01d9b850832c1cfa6","observation_id":"f7925346-5782-41e4-9caa-f5c05422f756","resolution":{"observed_at":"2026-08-06T19:42:36.151170Z","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":"2026-08-06T19:42:36.134848Z","title":"Elementary applied statistics","venue":null,"work_id":"9d7eb6e0-1391-489a-9ad6-9974100fb8f7","year":1975},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.664859Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:4e9cd835cedbf6c828aed34c439cc28d8a0d087e8a31c2e069e7d2a93510cd58","observation_id":"62451d31-7fc3-4043-b0e3-78da252a416b","resolution":{"observed_at":"2026-08-06T19:42:36.138902Z","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":"2026-08-06T19:42:36.121650Z","title":"Batchbald: Efficient and diverse batch acquisition for deep Bayesian active learning","venue":null,"work_id":"f85f6256-61e8-42ad-b33d-6f5fda8f4883","year":2019},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.668609Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:e7f5fad12fbeec72472b78932753bf94cc2d11a293d3ebda707a03dd23ac0f90","observation_id":"74df95dd-035c-4c4e-92c7-ed08dcd5eff3","resolution":{"observed_at":"2026-08-06T19:42:36.126519Z","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":"2301.09490","last_updated":"2023-01-23T15:38:58Z","snapshot_observed_at":"2026-08-16T16:00:43.493486Z","submitted_at":"2023-01-23T15:38:58Z","title":"Speeding Up BatchBALD: A k-BALD Family of Approximations for Active Learning","version":1},"cited_work":{"arxiv_id":"2301.09490","doi":null,"metadata_source":"pith","pith_arxiv_id":"2301.09490","snapshot_observed_at":"2026-08-06T19:42:35.857364Z","title":"Speeding Up BatchBALD: A k-BALD Family of Approximations for Active Learning","venue":"cs.LG","work_id":"675be557-dc22-4412-a85d-94ab68b5a6b0","year":2023},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.673462Z"},"links":{"cited_paper":"/paper/2301.09490","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:597c911f04d78ff0ecb6f070e1dfd724076642bd6de92e389ee1235beeb4333f","observation_id":"286c30ec-1dd9-449d-b806-1a9677690fe9","resolution":{"observed_at":"2026-08-06T19:42:35.863505Z","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":{"arxiv_id":"1906.03671","last_updated":"2020-02-24T02:14:51Z","snapshot_observed_at":"2026-08-14T16:18:32.540444Z","submitted_at":"2019-06-09T16:52:09Z","title":"Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.03671","snapshot_observed_at":"2026-08-06T19:42:35.677648Z","title":"Deep batch active learning by diverse, uncertain gradient lower bounds","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.677648Z"},"links":{"cited_paper":"/paper/1906.03671","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:e368ab5ef6d8341f6da1570e407ca5a4eeb64a1855dcea9e722f6a9ed21501e1","observation_id":"f210c43a-630d-45c7-a559-eaea35024291","resolution":{"observed_at":"2026-08-06T19:42:35.677648Z","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":"2026-08-06T19:42:36.109564Z","title":"Bayesian batch active learning as sparse subset approximation","venue":null,"work_id":"e4acf204-9c1f-456d-ab71-57ff7972eb93","year":2019},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.682447Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:76dc016cbcac2a250eb8d9229bfbfb25e1a7223474a1c53233cc94e415a0332a","observation_id":"9a6987cc-0fa9-42a4-9eb5-19da05b6deef","resolution":{"observed_at":"2026-08-06T19:42:36.113669Z","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":"2106.12059","last_updated":"2023-09-19T21:20:38Z","snapshot_observed_at":"2026-08-16T18:15:13.915349Z","submitted_at":"2021-06-22T21:07:50Z","title":"Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.12059","snapshot_observed_at":"2026-08-06T19:42:35.686203Z","title":"Stochastic batch acquisition: A simple baseline for deep active learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.686203Z"},"links":{"cited_paper":"/paper/2106.12059","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:f56de227d462530caddf93a9c76597876ad82f6a9ab9e9ffdd02bc411c14be8c","observation_id":"73dee689-0639-401e-8c71-78fb735b7a98","resolution":{"observed_at":"2026-08-06T19:42:35.686203Z","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":"2026-08-06T19:42:36.096839Z","title":"Active learning for cost-sensitive classification","venue":null,"work_id":"ada74362-9269-4a57-acb4-81446133efab","year":2019},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.690230Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:d6d2ad9a23e27a563a5330b983310819d788b407ce645af013fa34d0afa3763d","observation_id":"35d923d6-66bc-4220-aece-ab1e760f061d","resolution":{"observed_at":"2026-08-06T19:42:36.100847Z","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":"2026-08-06T19:42:36.084454Z","title":"Learning cost-sensitive active classifiers","venue":null,"work_id":"5230e42d-0827-4096-bc9d-867707532e7d","year":2002},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.694130Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:9ea6f27599db050e523fd680681b0ffcce0aad1da12edf0670ee4796092bac56","observation_id":"d49a6e37-58cc-44f5-b14f-acc3c0153132","resolution":{"observed_at":"2026-08-06T19:42:36.088531Z","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":"2026-08-06T19:42:36.071951Z","title":"Optimised probabilistic active learning (OPAL) for fast, non-myopic, cost-sensitive active classification","venue":null,"work_id":"7317c698-7e91-43ad-a818-6d8b8dfb6c8b","year":2015},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.698269Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:095ebeaf4750755fa46977b2f542b964f63d84a0a178430c2ee098656f84da8c","observation_id":"ce7fe50b-d844-4244-8b0d-f1ac62ec2cc4","resolution":{"observed_at":"2026-08-06T19:42:36.076616Z","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":"2026-08-06T19:42:36.059803Z","title":"Batch multi-fidelity active learning with budget constraints","venue":null,"work_id":"a6771054-4446-43a6-a436-a1a7e25cb23f","year":2022},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.702388Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:9074c70f398726ad1c8e83d419dfb881322cbd3ca1f24d449c21d21441d2bbd9","observation_id":"e0433ee7-49b2-468e-8684-5bc300de1cee","resolution":{"observed_at":"2026-08-06T19:42:36.063778Z","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":"2026-08-06T19:42:36.047204Z","title":"Aid: A benchmark data set for performance evaluation of aerial scene classification","venue":null,"work_id":"bfbc3aec-06e8-499f-a92a-4236f4028c33","year":2017},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.706107Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:4bad2a29480c1e6c3e334a18db9a147ef6c3a9a0b626916ec3d04b4462c127d1","observation_id":"cd959167-f754-4668-b796-6a64e1fc0602","resolution":{"observed_at":"2026-08-06T19:42:36.051484Z","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":"1802.07856","last_updated":"2018-02-22T00:26:46Z","snapshot_observed_at":"2026-08-14T19:43:30.523356Z","submitted_at":"2018-02-22T00:26:46Z","title":"xView: Objects in Context in Overhead Imagery","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.07856","snapshot_observed_at":"2026-08-06T19:42:35.709933Z","title":"xView: Objects in context in overhead imagery","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.709933Z"},"links":{"cited_paper":"/paper/1802.07856","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:560b1ff7a6ef358f0b7aa6db39f4da24c8bf39ed74cc4703156cabf73e6896b7","observation_id":"716440ab-4941-4d1a-8256-c6ef13343ab2","resolution":{"observed_at":"2026-08-06T19:42:35.709933Z","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":"2026-08-06T19:42:36.033989Z","title":"Dota: A large-scale dataset for object detection in aerial images","venue":null,"work_id":"c10c23a8-c216-4497-84d4-3138751899a9","year":2018},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.714175Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:90045888741faafbb8c2e62ba59e3c99eced0d0454a2a9503d8b64b37bb5fd5f","observation_id":"a6de35e7-4f7f-4921-a1d9-1960f2a36525","resolution":{"observed_at":"2026-08-06T19:42:36.038777Z","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":"2026-08-06T19:42:36.021211Z","title":"SPAGRI-AI: Smart precision agriculture dataset of aerial images at different heights for crop and weed detection using super-resolution","venue":null,"work_id":"1e700afc-88c2-48ba-9adb-c4337838ab54","year":2024},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.718147Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:04e28c574709b82381e36c18bda32f52f6dd12e771fd64cf8888bcbdc501e658","observation_id":"50b01f1b-6882-4246-af19-d52a66305836","resolution":{"observed_at":"2026-08-06T19:42:36.025477Z","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":"2026-08-06T19:42:36.008731Z","title":"Estimating building energy efficiency from street view imagery, aerial imagery, and land surface temperature data","venue":null,"work_id":"b44dc7e1-a22c-4e68-a5d4-22c066a6864d","year":2023},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.722158Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:e43b42c184265a8c5bf0eb333d71d750149961d95fb7d738664c1d1fd6fcdb44","observation_id":"9fffe195-291c-4e7b-8bf4-fc469a0b12c8","resolution":{"observed_at":"2026-08-06T19:42:36.012919Z","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":"2026-08-06T19:42:35.996063Z","title":"Review of 50 years of EU energy efficiency policies for buildings","venue":null,"work_id":"a7492370-8ee8-4380-9b01-2e7818376b24","year":2020},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.726095Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:b29edca57608e03548407bcc1d2f16ac58d63e81092c2890446b08a1ea68223d","observation_id":"d47c070f-0765-4df2-84b5-1811068975a3","resolution":{"observed_at":"2026-08-06T19:42:36.000058Z","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":"2026-08-06T19:42:35.983395Z","title":"The relationship be- tween operational energy demand and embodied energy in Dutch residential buildings","venue":null,"work_id":"1bbbaade-ed33-4660-8793-10facf97b5eb","year":2018},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.729826Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:7e644f2be29450f9b1f3656220b0df7d3fc5de94e31472163d609333221a43c0","observation_id":"d5965152-752c-4b20-b71c-8b9387d7a2a7","resolution":{"observed_at":"2026-08-06T19:42:35.987528Z","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":"2026-08-06T19:42:35.970041Z","title":"PDOK - Publieke Dienstverlening Op de Kaart","venue":null,"work_id":"0229359b-ed53-4c4a-ab73-5ae44733e907","year":2024},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.734007Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:02fcadd9d2a8fe67cc06395a1b2eb8343c3e76c6b8707fef015922c3a11b62c1","observation_id":"c40ad079-53db-4eba-b1c7-d4fedf6a557c","resolution":{"observed_at":"2026-08-06T19:42:35.974412Z","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":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-17T13:03:40.359628Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-06T19:42:35.737636Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.737636Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:bff64b9782b63bb99c8515d80d84376c0d815ac29243ade1417b66c88d32f35e","observation_id":"f9722cf5-f9de-4ece-a3f4-216b1efd7210","resolution":{"observed_at":"2026-08-06T19:42:35.737636Z","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":"2026-08-06T19:42:35.956093Z","title":"Understanding architecture age and style through deep learning","venue":null,"work_id":"27eca995-9fad-495d-8141-8d0816de639e","year":2022},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.741679Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:fde2ac87c5a1c4fa9ea8c784c91bcc7f2460fb819f157ba0d0c230294b773718","observation_id":"bb41497e-843c-4268-a1f7-e54071d31cec","resolution":{"observed_at":"2026-08-06T19:42:35.960101Z","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":"2026-08-06T19:42:35.943497Z","title":"Bayesian learning via stochastic gradient Langevin dynamics","venue":null,"work_id":"c5c39b4f-1e98-4bf9-b4a0-b0eb56f60f44","year":2011},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.745407Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:f07471f2d646e9c67c807ea31144ddc12063a07386f48e5557d016504e6ff3f1","observation_id":"107d69e5-1175-4dd0-a344-a080ca7c8eb0","resolution":{"observed_at":"2026-08-06T19:42:35.947437Z","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":"2026-08-06T19:42:35.930540Z","title":"Stochastic gradient hamiltonian monte carlo","venue":null,"work_id":"f531eb21-7814-4793-bd11-94f951fcd4b9","year":2014},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.749133Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:7f081335055cf5b993cae9c59af82936e1f7eac3ca7cd4e26a6908fa705d012a","observation_id":"0e6cb7c3-628f-4894-8022-ae5b88d1f592","resolution":{"observed_at":"2026-08-06T19:42:35.934877Z","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":"2026-08-06T19:42:35.752988Z","title":"Cycli- cal stochastic gradient MCMC for Bayesian deep learning","venue":null,"work_id":null,"year":1902},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.752988Z"},"links":{"cited_paper":"/paper/1902.03932","citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:95bccfe31568d693ac5201c408f5ecd3ffd9618fe9bc3ffafcb07489752e3751","observation_id":"67f285c1-9996-4a57-be40-54aa225831cb","resolution":{"observed_at":"2026-08-06T19:42:35.752988Z","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":"2026-08-06T19:42:35.917740Z","title":"3D BAG viewer","venue":null,"work_id":"89861e3b-3013-49dc-9250-88d8ac9b56b1","year":2024},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.757125Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:f00c16912f3e6c1ecaa063e77e98f9506465c5e5129e3e7d834ea37a04c39815","observation_id":"dc7fc13f-e8da-40a6-b0ff-1cff097fef8c","resolution":{"observed_at":"2026-08-06T19:42:35.921804Z","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":"2026-08-06T19:42:35.904115Z","title":"R VO - Rijksdienst voor Ondernemend Nederland","venue":null,"work_id":"accf55a8-eeb5-4313-a323-d6cfe70ede18","year":2024},"citing_paper":{"arxiv_id":"2507.04929","last_updated":"2025-07-07T12:25:12Z","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T19:42:35.760858Z"},"links":{"citing_paper":"/paper/2507.04929"},"observation_digest":"sha256:ad706dc2e9a38e341f3769adf43351ab3dbafb2f6804afa567a2d0a75a8db3e1","observation_id":"dc5c49a8-8756-4554-9b5a-4a35e210b890","resolution":{"observed_at":"2026-08-06T19:42:35.909015Z","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":"2507.04929","last_updated":"2025-07-07T12:25:12Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T04:59:41.539596Z","submitted_at":"2025-07-07T12:25:12Z","title":"ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":2,"verified_fuzzy":34},"total_outbound_references":43},"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 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.04929."}