{"as_of":"2026-08-12T11:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0128af8c49628efd0ceeef0cf38c087ceeca17691d86eb0c9ac613962af52265","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T16:54:53.826375Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2412.09701/citation-record","integrity":"/paper/2412.09701/integrity","json":"/paper/2412.09701/citation-record.json","paper":"/paper/2412.09701"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.644894Z","title":"Lifelong Learning Without a Task Oracle","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.644894Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:b50d8edc65bbd066dbbeeb907708dc523363e290d9ac4819a3096602ea585e84","observation_id":"5df0fb2a-bb7b-477e-98cd-e36efbce7e43","resolution":{"observed_at":"2026-08-11T16:54:53.644894Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.649104Z","title":"Continual lifelong learning with neural networks: A review","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.649104Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:d217ac53c2493fcbbe9c0cb1948c3a8563cad576690e118ddf32030807731298","observation_id":"7666d4ff-7e70-42c5-ac34-3280ff7d892e","resolution":{"observed_at":"2026-08-11T16:54:53.649104Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.652823Z","title":"Rethinking experience replay: a bag of tricks for continual learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.652823Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:4a9d7b89591b03f25ebf01beefc4a0f2c737ea972aaf5664426d4923b69f2c21","observation_id":"8bd59bb4-a29e-4125-9854-d22685f1139e","resolution":{"observed_at":"2026-08-11T16:54:53.652823Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.656573Z","title":"A soft nearest-neighbor framework for continual semi-supervised learn- ing","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.656573Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:13e9c73eebc26cd25b90703062d743f86d0afa856aed835da44ea34b9e006e6e","observation_id":"0c76695e-4251-4293-a799-3e8e04354c20","resolution":{"observed_at":"2026-08-11T16:54:53.656573Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.660701Z","title":"Continual semi-supervised learning through contrastive interpolation consistency","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.660701Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:669d4286013f0f982a3a5b85fc0cc5b63cce61515727592243630cbd69188d4a","observation_id":"0796d3aa-14c0-47f7-9300-12a2e38f0f4e","resolution":{"observed_at":"2026-08-11T16:54:53.660701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.14307","last_updated":"2022-08-30T14:44:41Z","snapshot_observed_at":"2026-08-11T01:50:09.951544Z","submitted_at":"2022-08-30T14:44:41Z","title":"Beyond Supervised Continual Learning: a Review","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.14307","snapshot_observed_at":"2026-08-11T16:54:53.664627Z","title":"Beyond Supervised Continual Learning: a Review","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.664627Z"},"links":{"cited_paper":"/paper/2208.14307","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:5419f8069f2780a386660fa07cc735de1180850c99d6dcdd5e84af7dcdef0c20","observation_id":"79b968c2-6fcd-47e3-9f14-0263ce48c427","resolution":{"observed_at":"2026-08-11T16:54:53.664627Z","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":"2026-08-11T16:54:54.293614Z","title":"A survey of deep active learning","venue":null,"work_id":"82b05ca2-9018-4fe5-addc-16a3671eca2d","year":2021},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.669038Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:e61f547b162b2ccffe8794c7c3db81b8e3c430b76ed5d94713d69f94b42f643b","observation_id":"2f800b48-5edd-4ea8-b0cb-7eea9f83802e","resolution":{"observed_at":"2026-08-11T16:54:54.297753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:53.672797Z","title":"Learning loss for active learning","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.672797Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:cc769a3100f1a98107b67e57c01f4f4309381fb1b27d09fec3e831c5ccc38cba","observation_id":"87f8a80b-f8c0-4670-8d0f-d94d31d836dd","resolution":{"observed_at":"2026-08-11T16:54:53.672797Z","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":"2026-08-11T16:54:54.272454Z","title":"Active Learning for Convolutional Neural Networks: A Core-Set Approach","venue":null,"work_id":"44207ea3-7e45-490e-83d4-0f2162395c4c","year":2018},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.676387Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:564ab63ac926d81d069ea67d999a2b6fead45de79b64dad6810d9f0cce7cdc10","observation_id":"eab71085-1309-4a8e-9404-055c2be7bfc6","resolution":{"observed_at":"2026-08-11T16:54:54.276592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:53.680028Z","title":"Deep bayesian active learning with image data","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.680028Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:6e4ef789c093498c04ef977bbc1865f7330155b2d56851e6a3e10c784653856c","observation_id":"1c517a35-cc29-4651-b067-bba463856ec0","resolution":{"observed_at":"2026-08-11T16:54:53.680028Z","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":"2026-08-11T16:54:54.246370Z","title":"How to measure uncertainty in uncertainty sampling for active learning","venue":null,"work_id":"eb6b053f-856f-4f23-9105-19e43883386a","year":2022},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.683924Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:a4c52f1acc69d9b746aabfdfbb3163b1fdfc64c0f10cd953a15fbcd14c05eba4","observation_id":"ded28e11-bf7b-4674-84b3-6754a43f2c75","resolution":{"observed_at":"2026-08-11T16:54:54.252339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.234310Z","title":"Few-shot continual active learning by a robot","venue":null,"work_id":"7c8de436-593d-4436-97c6-ec8cee2e355b","year":2022},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.687808Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:9a51943d7e9724e4823361d295fdb37784df07b8894de866c7c616c15bc643a0","observation_id":"31fdd680-5ef8-42a7-9df5-d4e3f3dc7fc5","resolution":{"observed_at":"2026-08-11T16:54:54.238222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.03923","last_updated":"2024-01-30T12:24:42Z","snapshot_observed_at":"2026-07-06T15:24:00.424056Z","submitted_at":"2023-05-06T04:11:03Z","title":"Active Continual Learning: On Balancing Knowledge Retention and Learnability","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.03923","snapshot_observed_at":"2026-08-11T16:54:53.692182Z","title":"Active Continual Learning: On Balancing Knowledge Retention and Learnability","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.692182Z"},"links":{"cited_paper":"/paper/2305.03923","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:bfd9fa8866736638061226b65647c96be759eb37b8ed897e4a998f717a746b14","observation_id":"dfe19c6d-5b9e-4252-84a0-6bd7f1436025","resolution":{"observed_at":"2026-08-11T16:54:53.692182Z","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":"2026-08-11T16:54:54.222499Z","title":"Online active continual learning for robotic lifelong object recognition","venue":null,"work_id":"89908302-1acb-4e84-b9c6-e41527a93bbc","year":2023},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.696339Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:473e6600e229afdf088b1dd3ba59be108d1d6c934e36135537ed993529c7b259","observation_id":"ec92afcd-e12a-4d4b-b7f3-cbce06601c16","resolution":{"observed_at":"2026-08-11T16:54:54.226780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.210503Z","title":"Most-surely vs. least-surely uncertain","venue":null,"work_id":"c314d369-2353-485e-b350-477eb0b3c267","year":2013},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.701431Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:3518d9a72067a7e6abb826d1c08194ac097273880db082f8d9e77d3bd2677f15","observation_id":"488f5246-7ac7-4dfc-a5d9-2378bee5f186","resolution":{"observed_at":"2026-08-11T16:54:54.214560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.04250","last_updated":"2020-12-08T07:07:11Z","snapshot_observed_at":"2026-08-11T06:44:39.556315Z","submitted_at":"2020-12-08T07:07:11Z","title":"Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.04250","snapshot_observed_at":"2026-08-11T16:54:53.705690Z","title":"Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.705690Z"},"links":{"cited_paper":"/paper/2012.04250","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:85d2e4ab945b79101d06c7cc0f0e6e592c3484fe6064c73fd1fa9ba625dfe185","observation_id":"f27f509e-a666-424f-b8b2-149c77ec92cf","resolution":{"observed_at":"2026-08-11T16:54:53.705690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.709880Z","title":"incdfm: Incremental deep feature modeling for continual novelty detec- tion","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.709880Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:3ced42804aa12a97e88fb917a775ae6bcbad94dd403b01a6d0de5e22eaeb3d0b","observation_id":"c8b8560b-55ec-471a-b215-14cda48f0ce9","resolution":{"observed_at":"2026-08-11T16:54:53.709880Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.713785Z","title":"Experience replay for continual learning","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.713785Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:d3c393f559c828001a4aa2eaa709556dd8e56ffbc3135197b3fe284572a914a7","observation_id":"069e02bb-0e7a-4d79-ae4f-d007ea4d2b5e","resolution":{"observed_at":"2026-08-11T16:54:53.713785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.717350Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.717350Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:600ce215b20b913a01e8106ba4e985cdf4d4acf4db2d794f7503e00ddd6f7966","observation_id":"dbcd722e-3ca5-406f-b3a9-a58f0ee39e16","resolution":{"observed_at":"2026-08-11T16:54:53.717350Z","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":"2026-08-11T16:54:54.177368Z","title":"Unsupervised learning of visual features by contrasting cluster as- signments","venue":null,"work_id":"39b09ed5-a2d8-4c2f-8736-03effd814c2f","year":2020},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.720824Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:8f7fb411e540a69eb5a2648b0f9d19cc5b687c3694774cfa4aa025a6600dd6a3","observation_id":"0940342f-db7b-473c-ba5a-4fe363d456e5","resolution":{"observed_at":"2026-08-11T16:54:54.182176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-10T01:12:16.468283Z","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":"2026-08-11T16:54:53.724729Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.724729Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:57feee3d9bf4824931379f147fca1737aed97d11915a51bec779827a827ecb7f","observation_id":"2ed9385a-8e7f-4a42-8460-56a8ab20e670","resolution":{"observed_at":"2026-08-11T16:54:53.724729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.728610Z","title":"Emerging properties in self-supervised vision transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.728610Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:d5673504c36150f5f99770b50de028c894cbd73472ee7205d0f2a9c1b6a753a1","observation_id":"b9fc55f6-4e1e-4c4a-9154-7932a3ecf371","resolution":{"observed_at":"2026-08-11T16:54:53.728610Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.732266Z","title":"ImageNet-21K Pretraining for the Masses","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.732266Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:1733b6302cb7067c217a8a8a81d319b97732a835ad4867ee955ab1a077f8220a","observation_id":"3d179d18-9406-4f11-935b-6096bdf9cee1","resolution":{"observed_at":"2026-08-11T16:54:53.732266Z","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":"2026-08-11T16:54:54.151962Z","title":"Places: A 10 million Image Database for Scene Recognition","venue":null,"work_id":"39f4b0f9-55bb-4be4-8cb3-1849eaaa0a32","year":2017},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.735684Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:56da89834baf462c1422324bf456a74f64918628a8077c1bcfb751a020ee5c11","observation_id":"f964176e-2385-4dd5-9e30-571f5a12bc12","resolution":{"observed_at":"2026-08-11T16:54:54.155885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.00029","last_updated":"2019-02-01T09:51:18Z","snapshot_observed_at":"2026-08-10T12:27:00.276389Z","submitted_at":"2017-08-31T18:19:10Z","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.00029","snapshot_observed_at":"2026-08-11T16:54:53.739437Z","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.739437Z"},"links":{"cited_paper":"/paper/1709.00029","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:e74157a126e2fcdfa7767722aa13a6fe4dd11eb9eed188dd7cfc6f97f15d2f28","observation_id":"a5b087d9-446f-44a6-9610-c81831f63c1f","resolution":{"observed_at":"2026-08-11T16:54:53.739437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06642","last_updated":"2018-04-10T20:22:13Z","snapshot_observed_at":"2026-07-06T05:52:02.469903Z","submitted_at":"2017-07-20T17:59:55Z","title":"The iNaturalist Species Classification and Detection Dataset","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06642","snapshot_observed_at":"2026-08-11T16:54:53.743688Z","title":"The iNaturalist Species Classification and Detection Dataset","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.743688Z"},"links":{"cited_paper":"/paper/1707.06642","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:990356d12f8d4b7e46c9ec31c9b98952d36d0e001b9bb00425a6461a578214ff","observation_id":"c8dc0fdd-b367-4671-afbb-7f4ce0bad0b3","resolution":{"observed_at":"2026-08-11T16:54:53.743688Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.749178Z","title":"Learning Multiple Layers of Features from Tiny Images","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.749178Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:eb16c2c3c02cbf8c3cae38058a4655139d0aef8fd6660e7349aee98861a003ba","observation_id":"c5799118-f967-4397-84f3-225a74d33893","resolution":{"observed_at":"2026-08-11T16:54:53.749178Z","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":"2026-08-11T16:54:54.130288Z","title":"Mixmatch: A holistic approach to semi-supervised learning","venue":null,"work_id":"9781e01b-9cd5-4b70-a3ef-4d311410b379","year":2019},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.753761Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:d59ae23cee0429364921a601f9f96a3f0c603a4710d78cd26029349ee14e809a","observation_id":"f92a8093-6e15-4c9a-b3df-ebfadf20a88b","resolution":{"observed_at":"2026-08-11T16:54:54.135476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:53.758108Z","title":"Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.758108Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:1def33ccc21ed9eaa1f1223a67f4a772463022773e6df7421ed668be38fd5b05","observation_id":"bc8f7b8e-68cd-43b1-bdba-198426a18b35","resolution":{"observed_at":"2026-08-11T16:54:53.758108Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.761902Z","title":"Generalized odin: Detecting out-of-distribution image without learning from out-of-distribution data","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.761902Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:54aa97408bb5d52822fcde9c0c63e65b551e0b29928f277e93d13ed1252aec61","observation_id":"2835627b-8f81-479e-8d50-b3734cad3d0f","resolution":{"observed_at":"2026-08-11T16:54:53.761902Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.01146","last_updated":"2020-09-28T21:44:55Z","snapshot_observed_at":"2026-07-06T07:12:23.549121Z","submitted_at":"2018-11-03T02:40:01Z","title":"Closed-Loop Memory GAN for Continual Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.01146","snapshot_observed_at":"2026-08-11T16:54:53.765854Z","title":"Closed-loop memory GAN for continual learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.765854Z"},"links":{"cited_paper":"/paper/1811.01146","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:0045e74fe4e7c008f433702b529148d5e4e3914ef0881a7b6d8b856be1cd92a1","observation_id":"f00c5ea0-abe0-4ae7-abc9-d871ca6c1582","resolution":{"observed_at":"2026-08-11T16:54:53.765854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.769398Z","title":"Head2toe: Utilizing intermediate representations for better transfer learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.769398Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:c23117d0800b8e2f3393b260579cbc1cc74dbf312fd1af6beb3464f4ca1a0c96","observation_id":"4c34123a-a116-4308-b97b-74b5bd623e4e","resolution":{"observed_at":"2026-08-11T16:54:53.769398Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.773005Z","title":"The dynamics of perceptual learning: an incremental reweighting model","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.773005Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:3df63322744234e74bfae7ffd40cb6cbea3aa353ca7292d51980f27b0f879862","observation_id":"9e39250f-890e-461b-9d32-a1625f0b0678","resolution":{"observed_at":"2026-08-11T16:54:53.773005Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.02729","last_updated":"2020-10-21T21:13:04Z","snapshot_observed_at":"2026-08-09T22:27:21.918426Z","submitted_at":"2019-09-06T06:14:03Z","title":"A Baseline for Few-Shot Image Classification","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.02729","snapshot_observed_at":"2026-08-11T16:54:53.776726Z","title":"A baseline for few-shot image classification","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.776726Z"},"links":{"cited_paper":"/paper/1909.02729","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:16251e0dc796a473b913463921c9371314472cb82019221c7ab1a16ed12df930","observation_id":"5fe7d56e-3f13-4699-81cc-45f994d6797f","resolution":{"observed_at":"2026-08-11T16:54:53.776726Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-11T16:54:53.780737Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.780737Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:f024a29462e520a170c6ae5a758967831e0684620fe3c22e9176629239dd595b","observation_id":"9516ea2e-ab76-4e04-b602-28a24aa5d134","resolution":{"observed_at":"2026-08-11T16:54:53.780737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:54:53.784504Z","title":"ImageNet Large Scale Visual Recognition Challenge","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.784504Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:ae0365295f2ae197749908db024dfc33705969752175d8d87a7102878ce05824","observation_id":"2681733e-8f54-4f32-bb99-84687acc79cb","resolution":{"observed_at":"2026-08-11T16:54:53.784504Z","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":"2026-08-11T16:54:54.083801Z","title":"Mos: Towards scaling out-of-distribution detection for large semantic space","venue":null,"work_id":"a043fe2b-81e6-4670-a6ed-9939b0428c71","year":2021},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.789477Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:db8f721b79f7edaa24b1332f569b29c853745bf1c6dfdb90a2b52caf38a88fcc","observation_id":"c8f55515-644b-41d9-87ac-126844cd45d1","resolution":{"observed_at":"2026-08-11T16:54:54.087703Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.071643Z","title":"Delving into out-of-distribution detection with vision-language representa- tions","venue":null,"work_id":"eb3c818b-e0a0-46dd-a54e-4b042004927a","year":2022},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.793924Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:9d97f99a3fef0f1edf88cf5145826d3821213fecc096c402bea34d62261321a9","observation_id":"4efe38c8-dc8f-4eea-8f6e-6969a72f6165","resolution":{"observed_at":"2026-08-11T16:54:54.075914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.059536Z","title":"React: Out-of-distribution detection with rectified activations","venue":null,"work_id":"8c48925a-fc00-42c0-8c37-edc77826060c","year":2021},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.797454Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:046e41bb46be0fffccb27f1398501799d77142bbba5e4d4419d57ec8e5b71fd5","observation_id":"dca0b7e5-a652-4c65-a25b-ca373eeda729","resolution":{"observed_at":"2026-08-11T16:54:54.063821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.048322Z","title":"For ViTs16 we tried several extraction points, e.g","venue":null,"work_id":"9957fe17-444b-4ab2-926c-12d930239997","year":null},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.801675Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:241a51a8f07e7ecf3c637ef56746e96e23a5fd3d6c9a7a614c501bd522a7686d","observation_id":"917b5ccd-d6f3-4bb8-88a8-12b7cbfab987","resolution":{"observed_at":"2026-08-11T16:54:54.052103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.035304Z","title":"We use a random set of 500 samples from each of the 50 classes","venue":null,"work_id":"7b5d8f4c-8b23-44c8-b1fe-50b7c901eca9","year":null},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.805962Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:f295277f17af46fd47834236eaf99ee27f85dc3d5ae7e4cbdc691bf8399055ef","observation_id":"6a655eb6-33b8-4ef0-b087-4b4aab834cd4","resolution":{"observed_at":"2026-08-11T16:54:54.039501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.022764Z","title":"environment","venue":null,"work_id":"93a2ff7d-2587-4399-a2f5-84e9a4cae77c","year":null},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.810338Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:d3c9b4f27c3fac386b98c664ab929b234dbbe5f298f2be17e633c10ce6b13326","observation_id":"40f37905-f01a-465a-b58e-328bb9bf3537","resolution":{"observed_at":"2026-08-11T16:54:54.026359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:54.011540Z","title":null,"venue":null,"work_id":"067d81e0-2e17-4b07-8736-afcf2a8e3506","year":null},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.814327Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:338a65dcc5a4a75190815866d604b0be5820bc9d152d5bf2d84239fe97c1d9ff","observation_id":"7e7cea04-923e-4fc2-9384-50b059a8e26b","resolution":{"observed_at":"2026-08-11T16:54:54.015243Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:53.999813Z","title":"This totals 20 labels (super) and 50K images","venue":null,"work_id":"aa933e09-7259-4fb2-b19c-88c8b631b26f","year":null},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.818181Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:c3bef1fb5ba932250c6d5e344b521c1bcc7a3a4eba2fc6c298794a69618b319d","observation_id":"238f69d3-ac41-44c5-95ed-08fbb747b2ea","resolution":{"observed_at":"2026-08-11T16:54:54.003852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:53.987679Z","title":null,"venue":null,"work_id":"11162112-7d55-4e0e-a3d8-de13c16f02c7","year":null},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.822214Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:1be46daf7878448f0104328ed594489807bd8a8b3984108edfbe055faed207c1","observation_id":"f4dfb0e5-6e23-4ac3-92f7-a1ed9cf17498","resolution":{"observed_at":"2026-08-11T16:54:53.991742Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:54:53.973752Z","title":"In both ER and PseudoER, we utilize the cumulative classification entropy as an uncertainty score to actively-label and Pseudo-Label (PseudoER)","venue":null,"work_id":"88498efd-b792-44fa-8bcd-b61d863d19bd","year":null},"citing_paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T16:54:53.826375Z"},"links":{"citing_paper":"/paper/2412.09701"},"observation_digest":"sha256:a0a5a145c59e3f8095b6227a564cf719f566d14c0b563543b08fb70038e60f5e","observation_id":"91adcff1-adac-4243-8146-74dd7cfb714c","resolution":{"observed_at":"2026-08-11T16:54:53.979632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.09701","last_updated":"2024-12-12T19:49:09Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-11T16:47:17.556201Z","submitted_at":"2024-12-12T19:49:09Z","title":"CUAL: Continual Uncertainty-aware Active Learner"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":29,"verified_exact":0,"verified_fuzzy":17},"total_outbound_references":46},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2412.09701."}