{"as_of":"2026-08-10T01:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:44e476fa2f8c035c8457b1682cd93fceea73743b6f63ca7f01f6b69ab0865551","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T13:58:16.081454Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.20028/citation-record","integrity":"/paper/2507.20028/integrity","json":"/paper/2507.20028/citation-record.json","paper":"/paper/2507.20028"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:28.928356Z","title":"Align your prompts: Test-time prompting with distribution alignment for zero-shot generalization","venue":null,"work_id":"6875000b-070e-477f-bac2-71b3e179cc04","year":2024},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:10.875288Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:ce777d41a615793d9dd3d8eeee75d2cb11dc9674f2c55a295c2f9df6a26ff71b","observation_id":"b377b24f-eb72-4983-a5cb-1295b39421e0","resolution":{"observed_at":"2026-08-06T13:58:29.020039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:28.751139Z","title":"Active prompt learning in vision language models","venue":null,"work_id":"03911af5-8e85-49c0-9199-784560740f1d","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:10.945592Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:e35383c8378f30fb19e1f82af60bdefa3429dbd1145f11a19c9f5f5786437ca0","observation_id":"c0c079e4-798c-4695-a509-0b18bb66dbd3","resolution":{"observed_at":"2026-08-06T13:58:28.816442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:28.301343Z","title":"Food-101–mining discriminative compo- nents with random forests","venue":null,"work_id":"a8baa6af-c07d-4819-93d3-7818ebf252fe","year":2014},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.019250Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:10cd0f459b1ff0433a4fad9ab9090f4e1550f1efe398b39fecfcdba1cc263339","observation_id":"3db6cb66-c6fe-4822-bcac-5f2fbaf92a68","resolution":{"observed_at":"2026-08-06T13:58:28.545913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:27.971456Z","title":"Describing textures in the wild","venue":null,"work_id":"994020b2-c9d1-42c1-8440-cf1f4373aa3d","year":2014},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.092955Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:60a5060ead4bafc7b69d303e0cf62eae81666a1aa7785bbe630e79c0886070fd","observation_id":"8eff9fb1-43b8-4486-97e8-ffd0f76af136","resolution":{"observed_at":"2026-08-06T13:58:28.128288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:27.719920Z","title":"Imagenet: A large-scale hierarchi- cal image database","venue":null,"work_id":"7f50734a-8448-46b8-b9f5-1346e6e1c614","year":2009},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.169344Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:26cfa6026bf7a6d5b0cef4597f974f4bb9623847b2f9c46b3bdd04ed2c4de5ed","observation_id":"bbcd98b0-820e-4968-b1c0-ecdb8f190986","resolution":{"observed_at":"2026-08-06T13:58:27.852709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-07-30T09:12:38.100527Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-06T13:58:11.288383Z","title":"Bert: Pre-training of deep bidirec- tional transformers for language understanding","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.288383Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:f867ee0667fa0b64c454c6945ac6facfdc96ef76dad6a96ef504d4f2f4e29368","observation_id":"128c2a2d-9fae-49eb-9aa0-b3db7e6ee689","resolution":{"observed_at":"2026-08-06T13:58:11.288383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2026-08-06T13:58:11.322593Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.322593Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:5d7f928d9e1eaf041ede7949cef89129a2f286e2a34ca1286ca8da2ea07f968b","observation_id":"30968219-4c6d-40b6-98cd-d1d512d22c2a","resolution":{"observed_at":"2026-08-06T13:58:11.322593Z","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":"2026-08-06T13:58:27.434314Z","title":"Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 ob- ject categories","venue":null,"work_id":"96a5fc90-a484-4012-b8e3-ec1f47137709","year":2004},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.431519Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:1c07166eb0ce79c241dd9d80a052995ef12cce63a7f2b0a6839550e3891245b0","observation_id":"7dbf61f2-fb3e-4d9b-b0f7-52138ab08c94","resolution":{"observed_at":"2026-08-06T13:58:27.577373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.08675","last_updated":"2023-11-04T17:55:12Z","snapshot_observed_at":"2026-08-02T23:50:44.949692Z","submitted_at":"2023-05-15T14:31:49Z","title":"Improved baselines for vision-language pre-training","version":2},"cited_work":{"arxiv_id":"2305.08675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.08675","snapshot_observed_at":"2026-08-06T13:58:16.333412Z","title":"Improved baselines for vision-language pre-training","venue":"cs.CV","work_id":"38a400fd-f198-4294-9950-b6d547d2d2c3","year":2023},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.499233Z"},"links":{"cited_paper":"/paper/2305.08675","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:e8e36eacc073ea8e0216d385001339de3dcfa04bcf4c6cec36a05627bae696c4","observation_id":"69cdd656-8c2b-477e-a295-e79ba726b29a","resolution":{"observed_at":"2026-08-06T13:58:16.459417Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.05094","last_updated":"2024-04-07T22:31:34Z","snapshot_observed_at":"2026-08-07T05:57:01.906469Z","submitted_at":"2024-04-07T22:31:34Z","title":"Active Test-Time Adaptation: Theoretical Analyses and An Algorithm","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.05094","snapshot_observed_at":"2026-08-06T13:58:11.546469Z","title":"Active test- time adaptation: Theoretical analyses and an algo- rithm","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.546469Z"},"links":{"cited_paper":"/paper/2404.05094","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:91a2948a09e995b84a282b4eb4a70f129e70705ed2a72d6f1e7a42d0a7be8fab","observation_id":"8a2eb9c0-9596-4b00-9312-16c365a181ae","resolution":{"observed_at":"2026-08-06T13:58:11.546469Z","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":"2026-08-06T13:58:27.182098Z","title":"Deep residual learning for image recognition","venue":null,"work_id":"4838bf40-9492-490f-830d-a963acd5d62a","year":2016},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.624542Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:34e9e39a749580c247a56f3669e4542f0cf750027aa0573997f3442097076050","observation_id":"7887eac0-e444-472f-b88e-3c6aac79eeca","resolution":{"observed_at":"2026-08-06T13:58:27.284303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:27.002478Z","title":"Eurosat: A novel dataset and deep learning benchmark for land use and land cover clas- sification","venue":null,"work_id":"b3096903-8bdc-4be8-9233-54926e7a1270","year":2019},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.719567Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:038fc08aebc842c97829cd67842d802c824f39a144340137569d814915363518","observation_id":"aa5dc4fc-1bfa-48da-a42b-44400ac51557","resolution":{"observed_at":"2026-08-06T13:58:27.128940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:26.769060Z","title":"The many faces of robustness: A critical analysis of out- of-distribution generalization","venue":null,"work_id":"f5855dcb-4095-427e-bcbf-9093887d91cb","year":2021},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.821091Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:e5541dcaf9d8ac8565f8e30c062ee329a9c8c8cb6836c8bdbed5584d161a2874","observation_id":"9d2d6a5f-15c0-467f-a30a-a8dbe9159687","resolution":{"observed_at":"2026-08-06T13:58:26.884000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:26.558188Z","title":"Natural adversarial ex- amples","venue":null,"work_id":"69000f9f-8510-46e7-a827-0d183f6fe979","year":2021},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.917024Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:e66394f199a9313e67df56ca93882a1cfeafff6c70971dca76379b59cdd62686","observation_id":"9ff9cd7d-26ff-4a4e-9870-224cca5a6153","resolution":{"observed_at":"2026-08-06T13:58:26.666542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:26.284008Z","title":"Entropy-based active learning for object recognition","venue":null,"work_id":"c484fd42-5a66-4de7-8410-b8001a4a913d","year":2008},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:11.991183Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:a4252f612e5f1b6cf78a1a481537b771c7d49a146aadf141a10b7c2fd210d2f4","observation_id":"c19c83d4-8949-41ac-b912-6acb12248f19","resolution":{"observed_at":"2026-08-06T13:58:26.396801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:26.056859Z","title":"Maple: Multi-modal prompt learning","venue":null,"work_id":"b6410770-0122-4b5c-9395-c36830d53a09","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.061652Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:283eaebc34964a456704d0cb485ba1f1ecbc37c792c4f0c623ba259dc5b123cb","observation_id":"53a26261-53d5-4bc0-a4f1-452d829173db","resolution":{"observed_at":"2026-08-06T13:58:26.162222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:25.841856Z","title":"Salad: Source-free active label-agnostic do- main adaptation for classification, segmentation and detection, 2022","venue":null,"work_id":"47cbbf1d-8e23-4485-ba5f-72d9c6d68a85","year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.103259Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:b1e25632b484f7c50bfe11dd8369b316153b7bec47cf6e598c9ab37af68e36d6","observation_id":"a4cd0aa5-0f37-49e0-bba7-a436e538d9fa","resolution":{"observed_at":"2026-08-06T13:58:25.939759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:25.571586Z","title":"3d object representations for fine-grained cate- gorization","venue":null,"work_id":"56ceacc5-ed4a-464e-af45-b21ab6b3cc88","year":2013},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.167171Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:d08fde74d81d3a94b9a4619349b12ad110816c6a6ab024dbc9f6966295e6da69","observation_id":"10ad735b-4151-4899-a7ea-4faa0a0b86da","resolution":{"observed_at":"2026-08-06T13:58:25.672046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:25.273913Z","title":"Heterogeneous un- certainty sampling for supervised learning","venue":null,"work_id":"cdf7af07-1b3d-4801-a693-f3238c16bbbf","year":1994},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.235720Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:38c2bd1cb7800d8e313ed88c028cedfe098cdb86973d70b2817df640ff91b87a","observation_id":"c7e40817-ca60-4f73-a907-f74f6981fddc","resolution":{"observed_at":"2026-08-06T13:58:25.426628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:24.998953Z","title":"Blip: Bootstrapping language-image pre-training 9 for unified vision-language understanding and genera- tion","venue":null,"work_id":"710420c4-d99f-42c7-96db-5cdc23f13ba1","year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.301832Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:823135a2aa06a756ed1f5f982ffcd88a653ce04770aa947a3c457fe1a7d7fe73","observation_id":"c7857527-b134-4f99-9e32-35a8580507e3","resolution":{"observed_at":"2026-08-06T13:58:25.128788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.15361","last_updated":"2024-12-12T09:06:56Z","snapshot_observed_at":"2026-07-06T15:08:34.018146Z","submitted_at":"2023-03-27T16:32:21Z","title":"A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.15361","snapshot_observed_at":"2026-08-06T13:58:12.413511Z","title":"A comprehen- sive survey on test-time adaptation under distribution shifts","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.413511Z"},"links":{"cited_paper":"/paper/2303.15361","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:72404ed8f0d273bf0bf1787af3bd2d5012855c5dda24ad1971e6ae837d02fb6e","observation_id":"67d7c45e-818b-485f-922f-2347f6660ba2","resolution":{"observed_at":"2026-08-06T13:58:12.413511Z","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":"2026-08-06T13:58:24.733210Z","title":"A compre- hensive survey on test-time adaptation under distribu- tion shifts","venue":null,"work_id":"5a683f6f-aac1-44e6-b18a-602a051f8deb","year":2024},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.500905Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:726dddedd9ea7f1a08e7dd82c364a2dd8de9e484d2c75050f23be964730e9904","observation_id":"7d2b9c8e-ff8d-4d0b-8714-0f66b9b5557c","resolution":{"observed_at":"2026-08-06T13:58:24.862610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1306.5151","last_updated":"2013-06-21T14:31:57Z","snapshot_observed_at":"2026-07-06T03:16:28.287173Z","submitted_at":"2013-06-21T14:31:57Z","title":"Fine-Grained Visual Classification of Aircraft","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1306.5151","snapshot_observed_at":"2026-08-06T13:58:12.580789Z","title":"Fine-grained vi- sual classification of aircraft","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.580789Z"},"links":{"cited_paper":"/paper/1306.5151","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:aa77a17bd6b030ae7beb041f52c58df4c39e268d6fbc0f29d911b6733e0278b1","observation_id":"c3134652-9e53-412b-b44e-5e93a55f78a6","resolution":{"observed_at":"2026-08-06T13:58:12.580789Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.10963","last_updated":"2021-01-14T21:11:06Z","snapshot_observed_at":"2026-08-06T05:58:45.817385Z","submitted_at":"2020-06-19T05:08:43Z","title":"Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.10963","snapshot_observed_at":"2026-08-06T13:58:12.680831Z","title":"Evaluating prediction-time batch normal- ization for robustness under covariate shift","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.680831Z"},"links":{"cited_paper":"/paper/2006.10963","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:ccfade08f5989e5a011a672a15dcb1b93c3714603359188938e8598e3f593f6f","observation_id":"89b82b46-2aff-4f4c-b132-eb183933a1e1","resolution":{"observed_at":"2026-08-06T13:58:12.680831Z","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":"2026-08-06T13:58:24.559640Z","title":"Au- tomated flower classification over a large number of classes","venue":null,"work_id":"0a9140c3-0d2d-4977-9a58-8f9f19e8bd28","year":2008},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.764329Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:010529f1033341f3d5b9381d7247750715a4dd83f35cb365169fa10bd80ee8b4","observation_id":"c9ab1532-9bbd-4f60-86df-c59a2fd76e91","resolution":{"observed_at":"2026-08-06T13:58:24.643109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:24.378271Z","title":"Cats and dogs","venue":null,"work_id":"0d40cdc5-9704-460a-91c9-b2d740e4374a","year":2012},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.865425Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:f3da6637decfe0aaf31e761ead0eb4ecb04d9aa773459afcb944e4145519c205","observation_id":"d5e6ea16-09c0-4aeb-8afe-2b7541e725e7","resolution":{"observed_at":"2026-08-06T13:58:24.457784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:24.220771Z","title":"Active learning by feature mixing","venue":null,"work_id":"c3d4b1ec-b1c4-4693-8f6c-4c349b749c7f","year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:12.931874Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:759c7821899fbd531194dc6e6838b84226fdac84054c0d09e3aa128df095172f","observation_id":"b40734fa-cb7a-4dfa-bfe6-afbeb11a5f4b","resolution":{"observed_at":"2026-08-06T13:58:24.302393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:24.053456Z","title":"Active domain adaptation via clustering uncertainty-weighted embeddings","venue":null,"work_id":"c1a8a8c6-287a-4b27-832f-c586b2d1245b","year":2021},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.039943Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:84ec88f756eb51ba886d0006a52962c6ebed592dd810675e35c2894f6b0918cf","observation_id":"ad8a8cac-40de-489e-8d98-07f44b7b8622","resolution":{"observed_at":"2026-08-06T13:58:24.120736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:23.865291Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"1289a050-67f3-4ad1-871c-3da5d88a8a57","year":2021},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.155573Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:b0ebdc47d027796dbd92005bdc3921f11a4c78a576811e3add2fd15519a51047","observation_id":"fe3cd786-682d-4a47-bd5a-2798332ebb76","resolution":{"observed_at":"2026-08-06T13:58:23.969892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:23.572173Z","title":"Do imagenet classifiers gen- eralize to imagenet? In International conference on machine learning, pages 5389–5400","venue":null,"work_id":"eb11cebf-15de-4e5d-8d9e-f16739a2819d","year":2019},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.269501Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:6ecb44285217125e8acc67da6805da5569b24acaa0b230bb5188371d26448381","observation_id":"4e6dae91-16e2-4d88-9dd5-c045bd07442e","resolution":{"observed_at":"2026-08-06T13:58:23.715060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:23.318692Z","title":"A survey of deep active learning","venue":null,"work_id":"7dcfb503-2ea6-46b1-af7f-8a397e03af70","year":2021},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.354251Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:192e0032edfbc446981cf1a1434307affdfe8ea40671c45a67080eb3592b78f3","observation_id":"7b302eeb-4e71-4f3f-9e1f-06d0154c7121","resolution":{"observed_at":"2026-08-06T13:58:23.438729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:23.081515Z","title":"Margin-based active learning for structured output spaces","venue":null,"work_id":"7161bafd-f692-43e2-81ef-f935e2d39a9c","year":2006},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.437705Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:21bbdde683649e761cfca8c705f5348da4bf8b46e608f532f5d48916c9f8d434","observation_id":"9881bb30-8d73-4d62-8ee3-8d6551f3a7bd","resolution":{"observed_at":"2026-08-06T13:58:23.173761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:22.776126Z","title":null,"venue":null,"work_id":"c6e2f21b-3cfe-4dcc-bf1a-6be0f160dfcf","year":2023},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.551491Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:b890b79fa0ae264ad2e69f496ad3a9715388df002903c203a52dfbe045e24deb","observation_id":"3e6f5c97-38ea-4808-92dd-cc465f9a2cd9","resolution":{"observed_at":"2026-08-06T13:58:22.954277Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:22.459007Z","title":"Improving robustness against common corruptions by covariate shift adaptation","venue":null,"work_id":"cde35d6f-873f-46ea-b97a-538dcdc41bbe","year":2020},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.680398Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:bffceed202af02e6b35649c40432628a1906be8437378c89c08c95519ef8fe6b","observation_id":"af048913-f37f-49cb-b1c2-e842d0308933","resolution":{"observed_at":"2026-08-06T13:58:22.592383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.00489","last_updated":"2018-06-01T10:17:23Z","snapshot_observed_at":"2026-07-06T05:53:39.440274Z","submitted_at":"2017-08-01T19:50:53Z","title":"Active Learning for Convolutional Neural Networks: A Core-Set Approach","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.00489","snapshot_observed_at":"2026-08-06T13:58:13.763941Z","title":"Active learning for convolutional neural networks: A core-set approach","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.763941Z"},"links":{"cited_paper":"/paper/1708.00489","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:7a0a9d9df442c3dd90785ee9b6fb70f6cb2c428e6f3e0ad5f3a2d3e02bafe152","observation_id":"fbc00de6-e4d8-4424-881e-1c5422565b12","resolution":{"observed_at":"2026-08-06T13:58:13.763941Z","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":"2026-08-06T13:58:22.182316Z","title":"Test-time prompt tuning for zero-shot general- ization in vision-language models","venue":null,"work_id":"22899d33-7130-4930-b1f9-42a77f7e90d4","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.879534Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:69e7ecf57d454b5b409d84277d0008f272afc7146b9af7d12b397eb3e0cd2044","observation_id":"4cb42f1d-bb15-425a-a8d6-f1c314f90d7b","resolution":{"observed_at":"2026-08-06T13:58:22.290094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1212.0402","last_updated":"2012-12-03T14:45:31Z","snapshot_observed_at":"2026-07-06T03:01:10.229407Z","submitted_at":"2012-12-03T14:45:31Z","title":"UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1212.0402","snapshot_observed_at":"2026-08-06T13:58:13.970986Z","title":"Ucf101: A dataset of 101 human actions classes from videos in the wild","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:13.970986Z"},"links":{"cited_paper":"/paper/1212.0402","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:ddd9e78e4691981bfe2a0d5cd68a2003b7b55d6c38ab65e7b98d1333bcc3e61c","observation_id":"e295553e-f8b0-46dd-b313-3f4508ab3f43","resolution":{"observed_at":"2026-08-06T13:58:13.970986Z","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":"2026-08-06T13:58:22.017416Z","title":"Deep coral: Correla- tion alignment for deep domain adaptation, 2016","venue":null,"work_id":"d96e3621-3579-41ee-b78e-1c33445a9cac","year":2016},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.039053Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:6877f8932bae32ff3fe9e090bdfe929309a8058a0e69799edb08e86d9c905d56","observation_id":"47c34744-dc68-4003-9fc9-cf6895a4a511","resolution":{"observed_at":"2026-08-06T13:58:22.066711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:21.750523Z","title":"Vpa: Fully test-time visual prompt adaptation","venue":null,"work_id":"c5c46757-904a-497a-8d04-ca3d9fdacc00","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.110022Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:41bf30eb9ca712e17de8182869112452cb82db2fc9995961c89aca6182576205","observation_id":"f1f9c169-0e45-4326-a80f-3a1ce4ebec88","resolution":{"observed_at":"2026-08-06T13:58:21.907659Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:21.526137Z","title":"Test-time training with self-supervision for generalization under distri- bution shifts","venue":null,"work_id":"b4e94991-4557-4d90-b695-12816e97ec95","year":2020},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.178466Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:8be93de26e84363d09ea2ad162178863d31e44334e824f9a1492f169b4257469","observation_id":"3c1487c2-d925-4aeb-8488-4ba568430248","resolution":{"observed_at":"2026-08-06T13:58:21.615888Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:21.373110Z","title":"Attention is all you need","venue":null,"work_id":"66289dd6-cc10-4a21-bcab-9f3fa28e4bfb","year":2017},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.238421Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:223de118146e4c2f59fe78dd534b42db9f5ea564757361e9f22470d8dabf0f3e","observation_id":"b2d688e1-2102-432c-80f6-88a32ace45a1","resolution":{"observed_at":"2026-08-06T13:58:21.478246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.10726","last_updated":"2021-03-18T17:58:01Z","snapshot_observed_at":"2026-07-06T09:30:32.320227Z","submitted_at":"2020-06-18T17:55:28Z","title":"Tent: Fully Test-time Adaptation by Entropy Minimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.10726","snapshot_observed_at":"2026-08-06T13:58:14.350158Z","title":"Tent: Fully test-time adaptation by entropy minimization","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.350158Z"},"links":{"cited_paper":"/paper/2006.10726","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:e0b96d2f5e9a508222d146732a61c4603768d938d4a024e0ead09ba04ab9bed0","observation_id":"5c8f87ed-899e-48ad-ac4b-9dd12c0277c8","resolution":{"observed_at":"2026-08-06T13:58:14.350158Z","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":"2026-08-06T13:58:21.106696Z","title":"Active source free domain adaptation, 2022","venue":null,"work_id":"236b1a40-0c03-4335-9853-9ff97bbeb654","year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.467596Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:a285fe35ac6e974b30db9592e3c30c16a3403a41b37381886d21e7e9ac29fdf7","observation_id":"cfcfc350-99a1-40c4-b3ef-e3e1df56650a","resolution":{"observed_at":"2026-08-06T13:58:21.217254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:20.830757Z","title":"Learning robust global representations by penalizing local predictive power.Advances in Neural Information Processing Systems, 32, 2019","venue":null,"work_id":"975499f9-cd2e-42e0-a4cb-bdb7e76217ab","year":2019},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.548621Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:f5b1cfa0161b251e73248c24f5544fc7cd29b6c5353d25ebd033c915ecd17bbe","observation_id":"51768d88-7c67-4405-8ef8-bcf7931dfb6e","resolution":{"observed_at":"2026-08-06T13:58:20.977285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:20.561422Z","title":"Position-guided text prompt for vision-language pre-training","venue":null,"work_id":"1586d06a-0b44-497f-9b98-f2d85495d7f9","year":2023},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.628453Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:e81dbc5bb3d9d13727260461d8b61c6f4a99573539156c1e332cddf6812b6319","observation_id":"b6eca4ef-20a4-4428-88d2-55f3d4e960ae","resolution":{"observed_at":"2026-08-06T13:58:20.695622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:20.149604Z","title":"Active learning us- ing uncertainty information","venue":null,"work_id":"fbf46190-dca3-41a1-ab0c-89f3ed10b0e8","year":2016},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.741001Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:9aa40720beb4543db79d40281f1aa555fedd49c8f7c247e735eb1a591f81c431","observation_id":"7b58afce-0874-440c-a2c7-77156ceb06fe","resolution":{"observed_at":"2026-08-06T13:58:20.379173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:19.899337Z","title":"Robust test-time adaptation in dynamic scenarios","venue":null,"work_id":"d8312a95-a844-460b-acc5-f2e6d1c52d55","year":2023},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.839064Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:d5f07b2c34c3af80bc0f973b53aef0869a3acab398ac5ef96a313cc03c5fd106","observation_id":"0e072f56-2026-4c54-be7f-5cddaacba3d3","resolution":{"observed_at":"2026-08-06T13:58:20.000488Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:19.645769Z","title":"Central moment discrepancy (cmd) for domain-invariant representation learning, 2019","venue":null,"work_id":"06cfe0ef-c5ac-4371-9d0e-10395bad98a7","year":2019},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.906063Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:bbc3a02d00069e24fdbd172b7f44621d533db01671a834e7f48270554856f5a5","observation_id":"d1da0031-e8e7-4c87-aea0-ec360b2f50d2","resolution":{"observed_at":"2026-08-06T13:58:19.722046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.13450","last_updated":"2022-07-19T15:31:09Z","snapshot_observed_at":"2026-07-06T12:52:16.992962Z","submitted_at":"2022-03-25T05:17:24Z","title":"A Comparative Survey of Deep Active Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.13450","snapshot_observed_at":"2026-08-06T13:58:14.983531Z","title":"A comparative survey of deep active learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:14.983531Z"},"links":{"cited_paper":"/paper/2203.13450","citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:9321baa957ffd374246687647fd9307d0e1de51ee27e182f4ef48000f355bf95","observation_id":"dcd31108-fb5a-4f79-b8dc-3e8885b2068d","resolution":{"observed_at":"2026-08-06T13:58:14.983531Z","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":"2026-08-06T13:58:19.372328Z","title":"Memo: Test time robustness via adaptation and aug- mentation","venue":null,"work_id":"c8450203-4b5d-46b8-913c-58766170baf3","year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.053540Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:5946bdb3d997948de0a1b4d027fe0ebab0a9d63d56a85c53026ade6366e59bea","observation_id":"475ad72a-6a30-490b-8529-bffc701c2520","resolution":{"observed_at":"2026-08-06T13:58:19.534395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:19.211588Z","title":"Conditional prompt learning for vision- language models","venue":null,"work_id":"414e7b55-d408-475d-ba56-802df18f0a34","year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.091440Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:23918c47d36b6981a16c4d277927453473f017c9cb4ba3d68c26e677fba0d125","observation_id":"65815c8c-2f76-4204-a4d1-07601173aefc","resolution":{"observed_at":"2026-08-06T13:58:19.275924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:18.946577Z","title":"Learning to prompt for vision-language models","venue":null,"work_id":"ffdf8513-35ba-4993-8c9c-a4950c0e90b1","year":2022},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.196598Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:f65a53957981d9bb8c535346a98b1af036d3aaeb3100e26ab3f5dc6f36bb3621","observation_id":"eb5b6da4-264a-4e66-a6fa-4cea8fcf694c","resolution":{"observed_at":"2026-08-06T13:58:19.051434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:18.666269Z","title":"Active Learning In active learning, we have an unlabelled dataset Du","venue":null,"work_id":"7d058875-e7b2-4cd0-80d3-1de9cb910a43","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.310838Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:c1aa63cb1bc639745ee5b1def460cc01d47fa170772a947512f00628bbe36991","observation_id":"d9ccb9e7-0dbc-4af2-a18c-8cbbfe77309b","resolution":{"observed_at":"2026-08-06T13:58:18.759587Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:18.525163Z","title":"Active Learning Active Learning promotes label efficiency by imposing a label budget","venue":null,"work_id":"0813fd8c-cc26-4de0-b10a-e442f0d2b3a5","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.414820Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:2adc26fcec471d2eb450e72d7fabd3c633fe8019fdf9fa374a35b56ee4c5e601","observation_id":"b70ff9a8-9ce0-4c89-814e-37f006e72ce2","resolution":{"observed_at":"2026-08-06T13:58:18.594476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:18.154075Z","title":"In domain generalization, we evaluate on four out-of-distribution (OOD) variants of ImageNet [5]; ImageNet-Sketch [44],ImageNet-A [14], ImageNet-V2","venue":null,"work_id":"9f411a69-8300-4b50-b435-9b033e1b4fcb","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.491043Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:4a8321cf63de40271360a0c806182ba58f998f930639650ecae7333982f58ba0","observation_id":"707d1e0b-0736-45a0-99ec-dc95b478bdda","resolution":{"observed_at":"2026-08-06T13:58:18.336421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:17.876048Z","title":"For cross-dataset transfer, we try on 10 image classification datasets which cover a wide variety of visual recognition tasks","venue":null,"work_id":"9d45d02f-4c65-4c76-8244-8462bafe2e55","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.573498Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:ca88ccfae9d72c4b7b4d8dd99baf309c603ed3af359152dcfa4dcae2ca2e6198","observation_id":"239cfbb7-50e4-43df-9579-0534859703fa","resolution":{"observed_at":"2026-08-06T13:58:18.027114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:17.662085Z","title":null,"venue":null,"work_id":"f37227c2-7d8b-4f61-a1e3-56f39b182266","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.649267Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:e81a2115cd193682d0c8e79becead2b27bf614745ee65aab2e2107b5af91bcde","observation_id":"318cacc6-7691-4cf0-a2c0-039adb280f69","resolution":{"observed_at":"2026-08-06T13:58:17.756107Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:17.380343Z","title":"Implementation Details","venue":null,"work_id":"4de59060-7fd6-4ff3-b72b-411bd3b12f9b","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.705256Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:001b8f9132d2030391985225fb32d3b6463a364bbbfe6e205e9bd73e021d97cf","observation_id":"f0c75f98-39ca-402f-b14c-5b0398d01005","resolution":{"observed_at":"2026-08-06T13:58:17.513410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:17.174291Z","title":"MaPLe [16] is a multi-modal prompt learn- ing baseline, which adapts CLIP by learning deep prompts on both the text and vision branches","venue":null,"work_id":"0abe826c-8012-45b4-a4b2-46bd06856d33","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.797187Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:24f223f02e0f2a4aee4a22134d0a81cb8d2ea4e18abac6c2d2005459c61e8597","observation_id":"df6605f9-330a-45c7-916b-912c66345b51","resolution":{"observed_at":"2026-08-06T13:58:17.267170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:17.022636Z","title":null,"venue":null,"work_id":"129e9a6f-fc03-4dfd-91bd-d0da54c1ff25","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.871431Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:28908be975d66e200933842ce5220545aee1c1a04ea74f4d1803a7050c51fa79","observation_id":"c060219c-80e4-4a04-8481-2cdff944c54b","resolution":{"observed_at":"2026-08-06T13:58:17.100000Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:16.778823Z","title":"Class Balance in Buffer Our policy is to first fill the buffer, not caring about the class of the image added","venue":null,"work_id":"2446238b-2c3c-4520-9df2-5913f5613ada","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:15.977944Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:43ae0097d0ee5541ca5ca8976bbeaf7c8b233ea6029edc88e403aa0854cc870d","observation_id":"8aa55b33-e962-4526-88a4-444b4c8d3d12","resolution":{"observed_at":"2026-08-06T13:58:16.896069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:58:16.583202Z","title":"5% regime","venue":null,"work_id":"fa5fa0b7-4ec4-459f-a9d6-247a7aa9ef63","year":null},"citing_paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T13:58:16.081454Z"},"links":{"citing_paper":"/paper/2507.20028"},"observation_digest":"sha256:7daf6a591941955ef96a1bfee0d3de90abab1bb5035bdff1ce5a6b729b15751c","observation_id":"68c37d0b-8f7c-4a6e-b1b5-ed1ce5f0a99a","resolution":{"observed_at":"2026-08-06T13:58:16.662767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.20028","last_updated":"2025-07-26T18:04:49Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T05:57:57.026454Z","submitted_at":"2025-07-26T18:04:49Z","title":"TAPS : Frustratingly Simple Test Time Active Learning for VLMs"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":1,"verified_fuzzy":48},"total_outbound_references":62},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2507.20028."}