{"as_of":"2026-08-09T22:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9bd0cd3153ae976f30c7997ec04b9ca82ef0f5d23f6bfb9e9f0dcc11683262eb","coverage":[{"denominator":53,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":53,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T13:17:46.565951Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-13T02:07:57.055712Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.20834","snapshot_observed_at":"2026-07-13T02:07:57.055712Z","title":"Kravets, D","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09562","last_updated":"2026-07-10T16:06:39Z","snapshot_observed_at":"2026-08-07T00:36:19.564259Z","submitted_at":"2026-07-10T16:06:39Z","title":"TCLA: Training-Free Class-wise Logit Adaptation for Medical Vision-Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-13T02:07:57.055712Z"},"links":{"cited_paper":"/paper/2507.20834","citing_paper":"/paper/2607.09562"},"observation_digest":"sha256:4614e3c973d1aac29c64ae40c6c9172b4268e40a41496710c5de08678d1e8260","observation_id":"fd8765f9-8732-4ee0-aa3b-513ba2534aac","resolution":{"observed_at":"2026-07-13T02:07:57.055712Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.20834/citation-record","integrity":"/paper/2507.20834/integrity","json":"/paper/2507.20834/citation-record.json","paper":"/paper/2507.20834"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:17:47.865051Z","title":"Analysis of representations for domain adaptation","venue":null,"work_id":"0b977cd3-125a-4a09-ba72-67c1cb0a67e3","year":2006},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:43.585420Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:c8a83ad56af9976a2f31e99b70efaab18e41c89fa8e9756a6c0b126297fa6b38","observation_id":"e87f0dd0-161a-4c6f-a371-7943c3e68476","resolution":{"observed_at":"2026-08-06T13:17:47.869671Z","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":"2026-08-06T13:17:47.843878Z","title":"Food-101 – mining discriminative components with random forests","venue":null,"work_id":"456c5614-11fb-4a1c-b0ac-dec2495918cf","year":2014},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:43.651164Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:17b35fad5f1edce176d7226b27b9d50790e405bb3f47128c88de179f4c498caf","observation_id":"a53a75d9-9601-4b18-bc5c-7cf6747271a8","resolution":{"observed_at":"2026-08-06T13:17:47.849850Z","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":"2026-08-06T13:17:47.827496Z","title":"Self-supervised learning for few-shot im- age classification","venue":null,"work_id":"0ac8fa63-7fce-458b-93f6-7f65f49ab124","year":2021},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:43.713281Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:90769c92d8c6cf530781b73568b386b8b343648d5b63774da49e44dce1d642a9","observation_id":"d61bc0de-2536-4925-8934-03bc7a17a1cb","resolution":{"observed_at":"2026-08-06T13:17:47.832208Z","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":"1904.04232","last_updated":"2020-01-12T16:25:06Z","snapshot_observed_at":"2026-08-07T01:22:24.475726Z","submitted_at":"2019-04-08T17:59:07Z","title":"A Closer Look at Few-shot Classification","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.04232","snapshot_observed_at":"2026-08-06T13:17:43.782740Z","title":"A closer look at few-shot classi- fication","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:43.782740Z"},"links":{"cited_paper":"/paper/1904.04232","citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:9b57e1bf6c796415d822f7f0d91839992c56ada2d2764d32705443e5c544033b","observation_id":"063c82c7-3e62-41da-8ded-91ccccaf2107","resolution":{"observed_at":"2026-08-06T13:17:43.782740Z","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":"2026-08-06T13:17:47.811149Z","title":"Describing textures in the wild","venue":null,"work_id":"c37742f8-f7bf-4240-b6ee-8a0b4d5e12a3","year":2014},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:43.854671Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:511f0242a2f5b65560ee4bdc874e75f448c7df8dd502d2b08c0c6e8bab60bffe","observation_id":"aa5d77e4-db46-4068-a48d-f5bcae3e25c8","resolution":{"observed_at":"2026-08-06T13:17:47.815929Z","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":"2026-08-06T13:17:47.793819Z","title":"Salun: Empowering machine un- learning via gradient-based weight saliency in both image classification and generation","venue":null,"work_id":"797addf6-4852-432f-90db-bafef3bda455","year":2024},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:43.924351Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:659aa91a76d769413020d16d6cea5d51049140bf34d3bd83398cd5e466789cc1","observation_id":"6669eafe-2a71-4808-9650-122de2c2e10c","resolution":{"observed_at":"2026-08-06T13:17:47.798802Z","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":"2026-08-06T13:17:47.776831Z","title":"Learning gen- erative visual models from few training examples: An in- cremental bayesian approach tested on 101 object cate- gories","venue":null,"work_id":"56148d8d-6554-499b-b377-b608cd65aa39","year":2007},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:43.988044Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:64dd4b2497a2f1b82aa3bb0ff6ae4346c8a24e2d9a2e8c02c374f442f0fb28b2","observation_id":"8dd26877-cdac-4764-974d-d044718cc924","resolution":{"observed_at":"2026-08-06T13:17:47.782741Z","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":"2026-08-06T13:17:47.760287Z","title":"Fast machine unlearning without retraining through selective synaptic dampening","venue":null,"work_id":"893ded18-64cb-4493-8467-7324b12fffad","year":2024},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.053946Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:e793e6ef26927f02acc29f7184dd8f3e7101e7661ec103b5f43c61acf3870ae3","observation_id":"c311a435-f698-46df-b080-f1749172b1ff","resolution":{"observed_at":"2026-08-06T13:17:47.765206Z","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":"2026-08-06T13:17:47.744351Z","title":"Gen- eralization bounds for few-shot transfer learning with pre- trained classifiers","venue":null,"work_id":"7ab06f66-8d80-4620-a9b4-c9b8f5f88693","year":2022},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.115019Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:af9faad66c9ade609948ef50398999e5fa35cd4c8913b763d6862d1bb29a25eb","observation_id":"cf1df365-9633-442d-bf7e-4483d4ec0a72","resolution":{"observed_at":"2026-08-06T13:17:47.749441Z","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":"2026-08-06T13:17:47.727913Z","title":"Clip-adapter: Better vision-language models with feature adapters","venue":null,"work_id":"333d9c3e-48dd-484e-b732-6c89c7759999","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.195663Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:686d0f52185f45468117d74604246a60d9cd13ba35ade8ff5822d8171eb0826e","observation_id":"20ec5353-ac32-40e7-a6f5-e6d465c01fb1","resolution":{"observed_at":"2026-08-06T13:17:47.733181Z","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":"2026-08-06T13:17:47.711750Z","title":"Amne- siac machine learning, 2020","venue":null,"work_id":"f773ec1b-c77e-4c40-babf-023a183be3d0","year":2020},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.274350Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:3f017c517f8bd319052becbe322ffe99bbf8fa6af1b3e05e3622b4938d1bec56","observation_id":"2e1c73c0-c711-467f-a51d-43cb341d4071","resolution":{"observed_at":"2026-08-06T13:17:47.716157Z","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":"2026-08-06T13:17:47.695650Z","title":"A kernel method for the two- sample-problem","venue":null,"work_id":"cf052caa-5b0b-4f5c-ad1f-06fe99c95e17","year":2006},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.335211Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:7b9581ccfe22b545f85f591cb8ff412398b61e610d910f0c040c6bfd3accb9a0","observation_id":"0cd64bc4-4868-4eb5-97ee-574dc66f5659","resolution":{"observed_at":"2026-08-06T13:17:47.700808Z","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":"2026-08-06T13:17:47.647804Z","title":"Visual-language prompt tuning with knowledge-guided context optimization","venue":null,"work_id":"92c09d01-7b21-4efb-97d6-235362e96884","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.406536Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:cd0a8f9e93a0ad1eebc89548e1fb1a22d9ddab042a7de0dfbeb4a2eb246a741b","observation_id":"b68934a5-a705-49eb-9e1a-7aace2365897","resolution":{"observed_at":"2026-08-06T13:17:47.666369Z","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":"2026-08-06T13:17:47.623225Z","title":"Tcp: Textual-based class-aware prompt tuning for visual-language model","venue":null,"work_id":"66ad72cc-ca78-4cc5-a35e-c1be30af080d","year":2024},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.492761Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:30681f6de5621578c3a6319343ecac12ce0faebe89f8e55c7578bb5eed8336c5","observation_id":"2cfe05d8-a056-4b3d-b51c-a3dc26bd3af7","resolution":{"observed_at":"2026-08-06T13:17:47.628871Z","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":"2026-08-06T13:17:47.606752Z","title":"Fine-grained visual-textual representation learning","venue":null,"work_id":"5be19b75-0181-433d-ad4c-a05ae828e19b","year":2020},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.571397Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:7f59cd958a6ac25bc0cf300e45428bcf307cb3403239cfdf246835ce4cd2e931","observation_id":"e87595d4-4d34-4af2-ad30-fce2353705cc","resolution":{"observed_at":"2026-08-06T13:17:47.611458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:17:44.664639Z","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":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.664639Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:60a0a94893b163cd3f04272d4998048db78d167c1b80ea7ed3795e6a2a07f2d2","observation_id":"2372bef2-687a-4518-bee5-1e5fda07e29a","resolution":{"observed_at":"2026-08-06T13:17:44.664639Z","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":"2026-08-06T13:17:47.578975Z","title":"Pushing the limits of simple pipelines for few-shot learning: External data and fine-tuning make a difference","venue":null,"work_id":"6ecd14f5-78ec-4b27-b984-0f7a9007bc26","year":2022},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.743149Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:2a75e2f0f0144d5d03167f930b263c5dfb6a753fafcabee90bc5ab8655a1a850","observation_id":"d4a46fef-096c-4858-84ab-45b6a75009a3","resolution":{"observed_at":"2026-08-06T13:17:47.583420Z","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":"2026-08-06T13:17:47.563852Z","title":"Maple: Multi-modal prompt learning","venue":null,"work_id":"2e4ee162-eab4-41dd-8844-9a982e94d5db","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.834461Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:4c33669938e6066aa0ffa4bceea52c368d7469de916d33773be93abb7fe52fa8","observation_id":"92a673a4-df35-4787-b15e-1d0d747a1c94","resolution":{"observed_at":"2026-08-06T13:17:47.568967Z","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":"2026-08-06T13:17:47.548388Z","title":"Self-regulating prompts: Foundational model adaptation without forgetting","venue":null,"work_id":"feffdd97-ff90-4527-99fb-504216059d31","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.907899Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:ca9cf1d3148ff4c028bb30eebb33604877cf58a9da7063c875c050890a439c00","observation_id":"ed19e21b-4f83-495c-a386-9a8c0d95ee9e","resolution":{"observed_at":"2026-08-06T13:17:47.552991Z","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":"2026-08-06T13:17:47.532969Z","title":"Novel dataset for fine-grained image categorization","venue":null,"work_id":"34837171-c5d9-4c26-9b0d-991fa3d5352e","year":2011},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:44.980737Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:78b9f0b3804c1662ed8cbf595c4ae02191b26fdc8f7885f3a54dbae5faccc1a1","observation_id":"58a058f3-1c47-41b5-a624-701f1a0acca5","resolution":{"observed_at":"2026-08-06T13:17:47.537996Z","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":"2026-08-06T13:17:47.516770Z","title":"3d object representations for fine-grained categorization","venue":null,"work_id":"a4b9d5f6-8c8a-4835-abe6-72b6ac6a3b4a","year":2013},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.063197Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:4162c9459a10f8293f032c93cf934df4384396b91fb8c47490d3a75a4a4e1bdc","observation_id":"f4efcd33-869e-4e5f-978d-1e77ada0f895","resolution":{"observed_at":"2026-08-06T13:17:47.522192Z","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":"2026-08-06T13:17:47.501961Z","title":"Clip adaptation by intra-modal overlap reduction","venue":null,"work_id":"e69207ef-e7b7-4eab-8e4b-6a127a29cef4","year":2024},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.164338Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:e03104f10ab97617a2e1224707c2ff66bc71c36b0b6361ad6e8b68af5b997f50","observation_id":"09556911-1a32-489d-ad09-11f4e930223c","resolution":{"observed_at":"2026-08-06T13:17:47.506485Z","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":"2026-08-06T13:17:47.485984Z","title":"Kravets and V","venue":null,"work_id":"7316c664-d230-483a-954d-620489779fde","year":2025},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.273038Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:107b7e3b62ff83e8f395899283aef43a7f1254cb3fa6bd4da5f4a1b8ade54ca3","observation_id":"a76679e7-8828-4022-be5b-7ddd9491769f","resolution":{"observed_at":"2026-08-06T13:17:47.490721Z","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":"2026-08-06T13:17:47.470317Z","title":"Namboodiri","venue":null,"work_id":"fc670f51-08b0-4358-afed-317d53eabc36","year":2025},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.334508Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:b1961b2ad3e4d712a632e398b75ec14d43ec9f395f4f81bb8b35cd0ddff8174c","observation_id":"f20802f4-4ae7-4902-80c1-59c7cf5dbb0f","resolution":{"observed_at":"2026-08-06T13:17:47.474993Z","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":"2026-08-06T13:17:47.454936Z","title":"Fine-grained visual classi- fication of aircraft, 2013","venue":null,"work_id":"29905032-16b1-4e75-9c78-44c3e2fe39e2","year":2013},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.447457Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:14590b832b406d2996a85a1ed9fb104805cac39dec4da1a87d748e7b7a50c9dc","observation_id":"221b4a48-3b3d-468e-8bf1-123010e200c6","resolution":{"observed_at":"2026-08-06T13:17:47.459824Z","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":"2026-08-06T13:17:47.313794Z","title":"McInnes, J","venue":null,"work_id":"f92dedaf-d042-4ff6-9bb8-4aba61407080","year":2018},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.523114Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:f1b0e7216060918b97b83bf9f8221ca39080bbf67325a7f9a2d37cad51cf192f","observation_id":"c99e44f6-affa-42af-84fb-9a2eb67442cc","resolution":{"observed_at":"2026-08-06T13:17:47.443666Z","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":"2026-08-06T13:17:47.298488Z","title":"Nilsback and Andrew Zisserman","venue":null,"work_id":"0d58edf8-c026-44dc-9f77-8036c7149b76","year":2008},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.570131Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:e4bfc63a34d539d3db3ef62ed064bec65a397d8823fdbdaeb2d2a6459bb2bf76","observation_id":"93f4f82e-b1f1-4bcf-970c-7b1dea0b8e41","resolution":{"observed_at":"2026-08-06T13:17:47.303151Z","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":"2026-08-06T13:17:47.282381Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"f78dfc56-2472-4bb6-b3f7-b6fc66809a3e","year":2021},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.620861Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:ca83d66cd64b29e2d089e9328a569ff5fa571433bcb05ac65c97bdb84438b778","observation_id":"1a2f9074-be74-4770-9908-629fe5f2b143","resolution":{"observed_at":"2026-08-06T13:17:47.287562Z","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":"2026-08-06T13:17:47.265966Z","title":"Transtrum, James P","venue":null,"work_id":"65aa6618-da7a-42ee-8818-5de54e565a7b","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.712481Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:c6bb634207c78f649d8c7f8870a2488f66c33b9bf2712c47199b8c45cc2bb863","observation_id":"0954d543-7579-4a23-8b5b-414ecd494b0a","resolution":{"observed_at":"2026-08-06T13:17:47.270536Z","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":"2026-08-06T13:17:47.249215Z","title":"Consistency-guided prompt learning for vision-language models","venue":null,"work_id":"ab327d69-44cf-4de6-987c-b4153e530624","year":2024},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.830542Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:05df0d62399ece56a5f786f4eaf472f0be4c1b9d18e1a137e6275d0f19a6e4df","observation_id":"e6d01a97-17f7-4d1a-8e25-b714f87c8ddc","resolution":{"observed_at":"2026-08-06T13:17:47.253970Z","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":"2026-08-06T13:17:47.231654Z","title":"Membership inference attacks against machine learning models","venue":null,"work_id":"19498482-dead-4491-b1fc-9bc849fc1a4a","year":2017},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:45.934876Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:90b2fcccd624c4d3407cc7d79ee82fda112108377ccf54fb8ea8fad1438dcf46","observation_id":"a5001b1c-894b-45e3-b841-1dcef81a5b2c","resolution":{"observed_at":"2026-08-06T13:17:47.236615Z","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":"2026-08-06T13:17:47.213526Z","title":"Plantdoc: A dataset for visual plant disease detection","venue":null,"work_id":"f06dca36-9874-4fa0-89e4-85d2bf5d0c3a","year":2020},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.055416Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:20c5f895cf99d428a0a0349aae5e98cac41fe7d0e4d762f6402a44ed5e6bec6b","observation_id":"f9967565-1ada-4777-b2d2-9bbb2fc581bf","resolution":{"observed_at":"2026-08-06T13:17:47.218885Z","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":"2026-08-06T13:17:47.196338Z","title":"Ucf101: A dataset of 101 human actions classes from videos in the wild, 2012","venue":null,"work_id":"4edd5d42-e569-47d4-8efb-58784dac78ac","year":2012},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.188494Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:057097d8d9cc18a30f95d159cf2c68a7d4d40c4445e16e984cbfa612729bf291","observation_id":"ebdfa429-2fc2-4765-a9f5-a24c588fdbec","resolution":{"observed_at":"2026-08-06T13:17:47.201265Z","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":"2026-08-06T13:17:47.180599Z","title":"Thudi, G","venue":null,"work_id":"02dfd4c1-48aa-455e-b33c-92c2b43d2258","year":2022},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.328351Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:3d697b810ce31fb1e9dbba172740a0ca1b7b0bae2b92a178661d2cdc3498c901","observation_id":"909d7083-e049-43d9-8d35-7742fe696834","resolution":{"observed_at":"2026-08-06T13:17:47.185538Z","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":"2026-08-06T13:17:47.164754Z","title":"Sus-x: Training-free name-only transfer of vision-language models","venue":null,"work_id":"85c6c493-90da-4d6f-9d2a-b6dd733928a6","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.456332Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:cf0f9b406becaf5875bdc92132f1cfe58dc487f6f63d36c3ec325064112a1a63","observation_id":"45ffc4d1-7323-4be9-b0da-f89653b611f7","resolution":{"observed_at":"2026-08-06T13:17:47.169528Z","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":"2026-08-06T13:17:47.147853Z","title":"Matching networks for one shot learning.Ad- vances in neural information processing systems , 29, 2016","venue":null,"work_id":"6c65ee9e-9083-4c8a-a221-99d7bb5cec3f","year":2016},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.461679Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:7d912d05162016100270379d3477cd3a73cc4d058a92e2a50f52d0af7dc6d0f4","observation_id":"1e0e1660-4bde-4013-85ba-eaa08c421423","resolution":{"observed_at":"2026-08-06T13:17:47.153191Z","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":"2026-08-06T13:17:47.131403Z","title":"Machine unlearning of features and la- bels","venue":null,"work_id":"a68cfa1b-d432-4790-b632-d686f52d7ede","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.467642Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:054bbaa9eab2d76b289179361498007079c5984367e78c3c3badab084598517a","observation_id":"c32a8145-62bc-4915-8b0b-5c49ec31846a","resolution":{"observed_at":"2026-08-06T13:17:47.136502Z","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":"2026-08-06T13:17:47.115727Z","title":"Ehinger, Aude Oliva, and Antonio Torralba","venue":null,"work_id":"e5d02375-7590-4674-a288-5598ee3cb5ee","year":2010},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.473171Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:301aaabb93023206bd297aa516481e2498bc11b494d5af01886dc034dd2a0fa4","observation_id":"34356e77-4f59-4267-b23c-32ca03bd907f","resolution":{"observed_at":"2026-08-06T13:17:47.120703Z","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":"2026-08-06T13:17:47.099072Z","title":"Sep: Self-enhanced prompt tuning for visual-language model,","venue":null,"work_id":"f44bc335-935a-4d74-a18a-d6286bbe6674","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.480530Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:503a5eca1283df1bff33cab1eeae3b248761e48b984540437d01a19805405d53","observation_id":"95521bed-b3d3-4868-bcd2-73ca75a93dba","resolution":{"observed_at":"2026-08-06T13:17:47.104885Z","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":"2026-08-06T13:17:47.076703Z","title":null,"venue":null,"work_id":"1dd2a85c-1079-41a5-8e18-876ef00ccefd","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.490062Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:8172608e1847a037227472d88b0521d85a45fc5ff121b322f961bc53dcbd50b0","observation_id":"4860d833-5e6c-4da6-abd0-33e415fb6809","resolution":{"observed_at":"2026-08-06T13:17:47.083027Z","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":"2026-08-06T13:17:47.061115Z","title":"Low-rank few-shot adaptation of vision-language models","venue":null,"work_id":"8a9ac97f-3c49-404e-bdb5-80736e3c85e5","year":2024},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.498152Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:11e3908906f542629a00adbe63582e00c214c8a7dffa47bb587eaf2ba7644871","observation_id":"5e7ca6f1-8b13-4c7a-b9b5-f7e5ff812198","resolution":{"observed_at":"2026-08-06T13:17:47.066177Z","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":"2026-08-06T13:17:47.042831Z","title":"Tip- adapter: Training-free adaption of clip for few-shot classi- fication","venue":null,"work_id":"0d7acd8c-831d-4273-b694-5ee0acee962b","year":2022},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.505098Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:12e426e6430d9aeffb817e1898a6cd85efcaefcf477dbf771aaf362d4a10c371","observation_id":"747dc2a3-5556-4c44-a87e-d36366b2bad6","resolution":{"observed_at":"2026-08-06T13:17:47.048312Z","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":"2026-08-06T13:17:47.025193Z","title":"Learning to prompt for vision-language models","venue":null,"work_id":"64891156-a2a8-40b6-9d2e-0d507e9722a3","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.510319Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:ace140a900674aa569c3bc4bf80f159aa564783477a396f007835e6641d5c530","observation_id":"c9bcd62f-6b86-4389-86b0-ec195df1349e","resolution":{"observed_at":"2026-08-06T13:17:47.032178Z","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":"2026-08-06T13:17:47.006421Z","title":"Conditional prompt learning for vision-language mod- els","venue":null,"work_id":"1c54871a-decc-4666-b943-c31b477bb1d5","year":2022},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.517118Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:afaa434d4742d4fb6a307c8150549ec22260e75d5750c5903b8f3ebbfb5b66c3","observation_id":"543a361e-45b7-4828-ac6c-5885429606a0","resolution":{"observed_at":"2026-08-06T13:17:47.011756Z","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":"2026-08-06T13:17:46.986174Z","title":"Prompt-aligned gradient for prompt tuning","venue":null,"work_id":"15846968-5a06-47fb-ab5f-f8b21dff73e5","year":2023},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.523000Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:84e5c9ba2b98265e413f9a628990195b256df6a6a559f26e1041faee695bee3c","observation_id":"3fa67172-6409-4bb2-8bf1-f3d575f9338b","resolution":{"observed_at":"2026-08-06T13:17:46.992721Z","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":"2026-08-06T13:17:46.967104Z","title":null,"venue":null,"work_id":"7e841ef5-f918-492a-8990-7de199022894","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.527499Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:5f6d07a9be134645618e492f064e6e322e47c5aeac0f595b0611a9671c4d12e8","observation_id":"a48813ed-26d0-439d-abb1-17d2ef7a1323","resolution":{"observed_at":"2026-08-06T13:17:46.971725Z","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":"2026-08-06T13:17:46.949266Z","title":"Our work builds upon the Self- Enhanced Prompt Tuning (SEP) method, which refines vi- sual prompts using a Token Fusion Module (TFM)","venue":null,"work_id":"6048a9b5-25f4-47c8-8f5b-cec3f75fed35","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.532634Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:9ed4c4212122e9aa3a6a5334fce987b5efdb0c12aa8e471a993a0a8b19075a8f","observation_id":"c264a5d7-3882-4804-a609-b2de63d30652","resolution":{"observed_at":"2026-08-06T13:17:46.954257Z","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":"2026-08-06T13:17:46.932137Z","title":"Ablation on α parameter of SEPRES","venue":null,"work_id":"469713e9-8f8e-46fb-84e2-f5daca141700","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.537273Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:9cfcb7de050dcf068cbfad5ef5800ffac5c405cc276912c238fd9b0d9c78ed2f","observation_id":"232ea8ac-63d0-4512-b6ce-a8a57cc1b5ef","resolution":{"observed_at":"2026-08-06T13:17:46.936831Z","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":"2026-08-06T13:17:46.915572Z","title":"4.1 of the main paper","venue":null,"work_id":"c8746840-faa2-469d-9e6e-a534460d850b","year":1907},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.542594Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:8ddbc005a18e4822c8e1e36679d7dca52ced3f78e20ed523de6da5283252049f","observation_id":"a6c5c238-6288-434c-82e6-5bb2c5062d00","resolution":{"observed_at":"2026-08-06T13:17:46.920396Z","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":"2026-08-06T13:17:46.897675Z","title":null,"venue":null,"work_id":"73a5dd06-cf5e-4474-b451-6c1c072f3437","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.548634Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:9d1326a078f2232a9e2fa2f7871f76f6bef57d71a56d71ee748216733a003bb7","observation_id":"4eafbfeb-3f29-4b8a-8fd3-6827a90722ff","resolution":{"observed_at":"2026-08-06T13:17:46.903485Z","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":"2026-08-06T13:17:46.880748Z","title":null,"venue":null,"work_id":"e16e9060-ab9b-4eeb-9520-ec4ecf31f09e","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.553775Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:11b50c1cd64d129f4707b56f3d17813d47fa4e57662ae3a261e4265c2f315876","observation_id":"e61fdcd5-7465-489d-aa29-f3d1f88e83f7","resolution":{"observed_at":"2026-08-06T13:17:46.885505Z","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":"6713.2338","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:17:46.838005Z","title":"5.3 evaluated under two distinct settings - excluding a subset and unlearning a subset","venue":null,"work_id":"12e87bf7-c7c1-46d5-a330-d9598527794e","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.560929Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:85aa1731b1c0c62642ff154a75133431332c41ff9ce67c1dd30f19d681bef5c7","observation_id":"35733d7f-11fc-4d66-b7f4-e8836b043eea","resolution":{"observed_at":"2026-08-06T13:17:46.846620Z","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":"0013.1002","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:17:46.735104Z","title":"Default runs unlearned CLIP","venue":null,"work_id":"01afcf60-c832-49de-a2ab-a52c60f5b90f","year":null},"citing_paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T13:17:46.565951Z"},"links":{"citing_paper":"/paper/2507.20834"},"observation_digest":"sha256:6f3e7c8c6bdc5b380b8461cec418c64bf591eb5ddc28294c98e3451e64ecf127","observation_id":"a9e8f19b-9671-4e38-beb4-7a0eb4a78047","resolution":{"observed_at":"2026-08-06T13:17:46.749919Z","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"}}],"paper":{"arxiv_id":"2507.20834","last_updated":"2025-07-28T13:41:24Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T13:17:41.148843Z","submitted_at":"2025-07-28T13:41:24Z","title":"Rethinking Few Shot CLIP Benchmarks: A Critical Analysis in the Inductive Setting"},"reference_resolution":{"displayed":53,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":45},"total_outbound_references":53},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2507.20834."}