{"as_of":"2026-08-07T12:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bda0a2516567767bd0be3c82cf7675276793d668014b0b9537650d42145ad222","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T10:38:34.814963Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2509.03895/citation-record","integrity":"/paper/2509.03895/integrity","json":"/paper/2509.03895/citation-record.json","paper":"/paper/2509.03895"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.04942","last_updated":"2025-08-07T00:08:31Z","snapshot_observed_at":"2026-08-06T22:25:08.339311Z","submitted_at":"2025-08-07T00:08:31Z","title":"Accelerating Conditional Prompt Learning via Masked Image Modeling for Vision-Language Models","version":1},"cited_work":{"arxiv_id":"2508.04942","doi":null,"metadata_source":"pith","pith_arxiv_id":"2508.04942","snapshot_observed_at":"2026-08-05T10:38:35.432628Z","title":"Accelerating Conditional Prompt Learning via Masked Image Modeling for Vision-Language Models","venue":"cs.CV","work_id":"6728e124-d886-44d2-909a-7f0aef1034c0","year":2025},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.374829Z"},"links":{"cited_paper":"/paper/2508.04942","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:0906309841d7cbb5f82a20b55052038cc05b68b884f859867bf9342fa86cd9c8","observation_id":"c64cae44-341b-48af-9c39-8e383e2a19ac","resolution":{"observed_at":"2026-08-05T10:38:35.510572Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:38.924832Z","title":"Describing textures in the wild","venue":null,"work_id":"78a16e8d-1f25-40d1-a601-81956277a9ba","year":2014},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.429550Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:891c4d9f39ecafe496be21152b8b758ff865bc4ea5f6288aba5195723c1329f9","observation_id":"927e97d4-882e-47f4-8c91-8b7ffc8a0ea9","resolution":{"observed_at":"2026-08-05T10:38:38.965490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:38.775878Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":"c92cf847-9416-4f59-807b-6a8d5bd8cd5c","year":2009},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.515224Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:ecdaef20b4ef1d0f94adf6229608bacd761a20dbfa40d63118959b8afd766286","observation_id":"9c9aed4e-c2e6-4597-9fec-342c0318bb34","resolution":{"observed_at":"2026-08-05T10:38:38.847693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2026-08-05T10:38:32.583907Z","title":"An image is worth 16x16 words: Trans- formers for image recognition at scale","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.583907Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:712163cb77a9943b2d2b8d15635e5b7e670267571753c280c9815ec1f77b4dcc","observation_id":"2f457c9d-4bca-46b9-beac-83389e1cdf0c","resolution":{"observed_at":"2026-08-05T10:38:32.583907Z","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":"2026-08-05T10:38:38.650100Z","title":"Learning to prompt for open-vocabulary object Table 5","venue":null,"work_id":"ce10d615-9d85-48c8-b299-ba23582fe4e1","year":2022},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.670879Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:d9e3d31c718a03e05c3a28948b43dbc2f227d4c92cdc22eaa0fa8c763cb05cef","observation_id":"a6297866-f22b-4ff5-b0d8-6ae6134742ea","resolution":{"observed_at":"2026-08-05T10:38:38.699811Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:38.512844Z","title":"Learning gener- ative visual models from few training examples: An incre- mental bayesian approach tested on 101 object categories","venue":null,"work_id":"25605660-fcb7-4504-978c-e253a78aab9c","year":2004},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.733927Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:454f8097cfe01a4d738c58a4334a4c34cc2a78f2ab7fbdd70e9cbbfc9caf33cd","observation_id":"aa37dac8-bd51-4f7d-95d2-147ac5bb7db0","resolution":{"observed_at":"2026-08-05T10:38:38.575371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.04544","last_updated":"2025-03-25T14:34:04Z","snapshot_observed_at":"2026-08-04T10:22:52.279940Z","submitted_at":"2021-10-09T11:39:30Z","title":"CLIP-Adapter: Better Vision-Language Models with Feature Adapters","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.04544","snapshot_observed_at":"2026-08-05T10:38:32.816317Z","title":"Clip- adapter: Better vision-language models with feature adapters","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.816317Z"},"links":{"cited_paper":"/paper/2110.04544","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:815e3abd62c4f5ae470d7b612ffa8be522f6837536effd64ae2baededd42cb5a","observation_id":"2a6c4d74-0d82-42b3-95e9-63219634dfb2","resolution":{"observed_at":"2026-08-05T10:38:32.816317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.13921","last_updated":"2022-05-12T01:27:40Z","snapshot_observed_at":"2026-07-06T11:04:30.929441Z","submitted_at":"2021-04-28T17:58:57Z","title":"Open-vocabulary Object Detection via Vision and Language Knowledge Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.13921","snapshot_observed_at":"2026-08-05T10:38:32.882353Z","title":"Open- vocabulary object detection via vision and language knowl- edge distillation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.882353Z"},"links":{"cited_paper":"/paper/2104.13921","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:2aa478514d7f24ef9b9ce9d720cd4144552e2e4944dffbe55b6921f3745fb9a4","observation_id":"f96d96d8-24ed-4363-96a4-5eb9f0b40f26","resolution":{"observed_at":"2026-08-05T10:38:32.882353Z","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":"2026-08-05T10:38:38.362990Z","title":"Deep residual learning for image recognition","venue":null,"work_id":"f6a1792d-c8dc-443b-8fc2-fedf25af9f09","year":2016},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:32.960808Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:e41c7c2c0e52bc372f3247d4758015513340f895cd0a85488711af231d0d2927","observation_id":"364d720d-35d1-4801-8e5f-a87468f5e535","resolution":{"observed_at":"2026-08-05T10:38:38.427446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:38.212981Z","title":"Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification","venue":null,"work_id":"14105c7f-c5e9-49f4-acc9-94d2b00ab2f3","year":2019},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.030128Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:688d00ee0d211780e8ddb8d00585a8d98bbbbec146254656cf8867465dc06280","observation_id":"45badd11-c3b5-4e3e-9509-230eea41ef7b","resolution":{"observed_at":"2026-08-05T10:38:38.289350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:38.070070Z","title":"The many faces of robust- ness: A critical analysis of out-of-distribution generalization","venue":null,"work_id":"6dac26fb-b92b-4496-9931-0206815a809a","year":2021},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.090794Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:9bc64a2ad356e4f3fe47a71f58b028f7cb152fe29c3efb5bb05cf8a975560e2a","observation_id":"7ff0dfd4-383d-43c9-8fbf-ac20997db6d9","resolution":{"observed_at":"2026-08-05T10:38:38.133392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:37.951081Z","title":"Natural adversarial examples","venue":null,"work_id":"d6b5fab2-4c9a-49a8-bac8-e89be953091a","year":2021},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.173447Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:20c4ccf76b100175a8366ca9d3e822e2b9091d1c3e433c5bacd6998e4fca4554","observation_id":"eef1642c-d45a-4bff-a340-363b0fc09342","resolution":{"observed_at":"2026-08-05T10:38:38.007794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:37.838879Z","title":"Gallop: Learning global and local prompts for vision-language models","venue":null,"work_id":"a9046e7f-164b-4ed2-be34-7266f60cc5b4","year":2025},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.253045Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:4a7d03277ba89201a9e28da56e88b7d3a34d3d019a5b90806e2a00aca21a7ca4","observation_id":"475eee5d-f078-4db4-8b66-4a662618bee9","resolution":{"observed_at":"2026-08-05T10:38:37.879279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-05T10:38:33.300869Z","title":"Decoupled weight decay regularization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.300869Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:969e59e6c9de88d9f4170dae5a7cbe31f33cf0c6b56b2273f204b53f8e618b7d","observation_id":"39f7addb-e785-4132-af11-6de6a3e685aa","resolution":{"observed_at":"2026-08-05T10:38:33.300869Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:38:33.384744Z","title":"Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.384744Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:7c84a6eb216ff8987875f889654a685b1bc8d4e78a3ec4f98782581e16fa3ebc","observation_id":"63dbc736-73a6-4fd6-a0fa-75b9ca7f5455","resolution":{"observed_at":"2026-08-05T10:38:33.384744Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-05T10:38:33.440910Z","title":"Fine-grained visual clas- sification of aircraft","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.440910Z"},"links":{"cited_paper":"/paper/1306.5151","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:eab89f420edb026752d5810006cd8c79ba45f9d5e9303b338be851160f5698f8","observation_id":"c26a6630-fe86-4095-83ca-233e3c4dd86c","resolution":{"observed_at":"2026-08-05T10:38:33.440910Z","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":"2026-08-05T10:38:37.697972Z","title":"Locoop: Few-shot out-of-distribution detection via prompt learning","venue":null,"work_id":"e69c7383-ea37-4bff-94c2-3012e114e494","year":2024},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.524260Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:6a4fcbff0c2d271829487badc75f98ca05a60f469a16ba8eb679dd8e30bee253","observation_id":"d48385e4-5bfc-465a-94aa-193f94775e20","resolution":{"observed_at":"2026-08-05T10:38:37.746542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:37.588768Z","title":"Debiasing, calibrating, and improving semi-supervised learning performance via simple ensemble projector","venue":null,"work_id":"69748c2b-d02f-412f-a48e-e3a2039765ce","year":2024},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.600592Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:9b85a955b44ebb99eb6e9e376de8e06f769462c24c7a0dbbe31674fde3da0372","observation_id":"1d0422c1-e8a4-4eb8-ba97-6b024ddce208","resolution":{"observed_at":"2026-08-05T10:38:37.628767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:37.359530Z","title":"Sequencematch: Revisiting the design of weak-strong augmentations for semi-supervised learning","venue":null,"work_id":"7dbb83bd-54ee-41ec-a065-44e5a760f6de","year":2024},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.668297Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:c4c202f29da219bc59f795c4456a3ab032ca02d8fdb6cd03ee857f782416d11e","observation_id":"dd54a4a5-a189-499d-b406-ae87affec971","resolution":{"observed_at":"2026-08-05T10:38:37.446260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:37.129799Z","title":"On calibration of prompt learning using temperature scaling","venue":null,"work_id":"eb21f3c8-6c4d-4352-a66e-d71c60c6562a","year":null},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.728143Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:c3f1bf30a2e7717d6bf96dc9d4016095a413b430e16014cd514e3fe298827db7","observation_id":"71e44c00-43b3-46a0-8145-2f20455dfdae","resolution":{"observed_at":"2026-08-05T10:38:37.221731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:36.860078Z","title":"Boosting semi- supervised learning by bridging high and low-confidence predictions","venue":null,"work_id":"00086bb9-6cf4-4333-a69f-8e489d06ecf8","year":2023},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.804128Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:9ffe5b935d3548fcbd6e8692aee548a80f4cbabecde197f67250223556856f7c","observation_id":"136539b0-c43e-4e54-a688-f587770705b9","resolution":{"observed_at":"2026-08-05T10:38:37.010494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2508.07570","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:38:35.177713Z","title":"Adaptive cache enhancement for test- time adaptation of vision-language models","venue":null,"work_id":"d87ad7f1-4495-47c6-be71-ef1d6bbb3f90","year":2025},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.861860Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:c17724bbd4c86ae397cd290c697dff4b9ba6257f89bb74ab3307034d3e2761e9","observation_id":"097340f0-c97d-4a0f-a2fd-795e761b79db","resolution":{"observed_at":"2026-08-05T10:38:35.233777Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:36.652404Z","title":"Proto-clip: Vision-language prototypical network for few-shot learning","venue":null,"work_id":"f8aef04e-debd-4952-8557-a1da472c3632","year":2024},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:33.928210Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:ccb917c651cbfc9a55ed9b820e722b3817455be90eaa53abd6a98947e8565578","observation_id":"1fdc48bd-61f5-4ab4-b6b0-d5c68ea7b6e1","resolution":{"observed_at":"2026-08-05T10:38:36.734860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:36.436393Z","title":"Cats and dogs","venue":null,"work_id":"bb0e8b84-7b5a-40c2-bb9f-634bc8ac2584","year":2012},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.011666Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:2ea3d317d27c0847abc30b30d256869048ffe3bc157a14a9cf28180a62bccd1d","observation_id":"dcada900-7b6c-48dd-8750-d0ddc8f6a822","resolution":{"observed_at":"2026-08-05T10:38:36.516368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:36.243843Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"fc77c372-4293-4ae5-b72c-38f4979b09b9","year":2021},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.075065Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:aa4e86e20d6cf4e5156307c5577fa0cd02d2696748448d252e9687f3b6e32a12","observation_id":"bba2293a-8aa4-44d2-a09a-2922e6660ce9","resolution":{"observed_at":"2026-08-05T10:38:36.317396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:36.136404Z","title":"Meta-adapter: An online few-shot learner for vision-language model","venue":null,"work_id":"0b16e330-2646-41b4-ac23-dcedacd7be06","year":2023},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.131278Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:6d9d1854aeda120714905446bdeaa7954a9043158948a4cb2bba88c87b9fa16c","observation_id":"6cd70bbb-8f11-4819-9454-42b8499834d5","resolution":{"observed_at":"2026-08-05T10:38:36.196770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:34.195332Z","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":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.195332Z"},"links":{"cited_paper":"/paper/1212.0402","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:f6d395ba8a2ea73d17fc8209def0137b247433e34adf0aa199e5336f7ad9415b","observation_id":"336a9857-7861-44f0-a4d2-eda70d8c088d","resolution":{"observed_at":"2026-08-05T10:38:34.195332Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.07490","last_updated":"2019-12-03T19:30:19Z","snapshot_observed_at":"2026-08-06T03:44:36.669916Z","submitted_at":"2019-08-20T17:05:18Z","title":"LXMERT: Learning Cross-Modality Encoder Representations from Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.07490","snapshot_observed_at":"2026-08-05T10:38:34.289924Z","title":"Lxmert: Learning cross-modality encoder representations from transformers","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.289924Z"},"links":{"cited_paper":"/paper/1908.07490","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:062ab4834c02c2c4674d50ee1ab60015bc46f519870a629ad80f8b6c25c49c98","observation_id":"e494f152-e49b-4c76-85be-fa7ec22e0c33","resolution":{"observed_at":"2026-08-05T10:38:34.289924Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:38:34.361960Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.361960Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:63694bdfa1f7de8a2c9c8121a7a462bc2e5d683a25014345d3413dafff6d3431","observation_id":"2d2d8eea-96c3-46cd-aa4c-20444bb25c7c","resolution":{"observed_at":"2026-08-05T10:38:34.361960Z","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":"2026-08-05T10:38:35.959434Z","title":"Learning robust global representations by penalizing local predictive power","venue":null,"work_id":"6aa14a01-602d-498f-8fff-4d9550a7b2ea","year":2019},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.409456Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:a6ebb3725f4ca9d9cbd3b84863abeef8d81d99c28fcbb2471b9297fbe3c09824","observation_id":"507ddd6c-cf86-41f8-9526-93532de6227a","resolution":{"observed_at":"2026-08-05T10:38:36.001684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:35.823842Z","title":"Sun database: Large-scale scene recog- nition from abbey to zoo","venue":null,"work_id":"f85c952f-0967-414f-bb66-21ec44ac335a","year":2010},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.494555Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:7dccf7be17a50c826d181113d65d90ecd040d7d7822e9867110f7489f6a24de5","observation_id":"912eaa99-f8fb-4333-bf0e-b90a5e13a0af","resolution":{"observed_at":"2026-08-05T10:38:35.882840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08340","last_updated":"2023-07-07T04:14:37Z","snapshot_observed_at":"2026-08-03T14:25:57.547805Z","submitted_at":"2022-08-17T15:06:36Z","title":"Dual Modality Prompt Tuning for Vision-Language Pre-Trained Model","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08340","snapshot_observed_at":"2026-08-05T10:38:34.556038Z","title":"Class-aware visual prompt tuning for vision-language pre-trained model","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.556038Z"},"links":{"cited_paper":"/paper/2208.08340","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:1773529d2ffba4154d8cd3dac4f0abe663b6b4905013dec277121d5d606e721d","observation_id":"cdca2cc4-7826-4ef8-bc17-84f86d4e290f","resolution":{"observed_at":"2026-08-05T10:38:34.556038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.03930","last_updated":"2021-11-15T04:58:28Z","snapshot_observed_at":"2026-07-31T03:05:21.352948Z","submitted_at":"2021-11-06T18:09:22Z","title":"Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.03930","snapshot_observed_at":"2026-08-05T10:38:34.663103Z","title":"Tip- adapter: Training-free clip-adapter for better vision-language modeling","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.663103Z"},"links":{"cited_paper":"/paper/2111.03930","citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:ea248cf9dd725db99a7c19f6bbc28ea580980a66a61d37c6042526ff689a2322","observation_id":"014ff591-b180-43fb-8ecb-b479a7f57ed1","resolution":{"observed_at":"2026-08-05T10:38:34.663103Z","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":"2026-08-05T10:38:35.714505Z","title":"Conditional prompt learning for vision-language models","venue":null,"work_id":"dda8ce6a-8fb6-4448-839e-f1e0efa9cc99","year":2022},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.754654Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:3321c8f18c38efca6d118c57f82f12b4d77d77324ae91073504aeb834f2d1160","observation_id":"0c062390-4ed8-4422-987b-69003325eb7c","resolution":{"observed_at":"2026-08-05T10:38:35.752900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-05T10:38:35.576192Z","title":"Learning to prompt for vision-language models","venue":null,"work_id":"4df242c8-3a40-4c5d-8135-bb7362dc8878","year":2022},"citing_paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T10:38:34.814963Z"},"links":{"citing_paper":"/paper/2509.03895"},"observation_digest":"sha256:0370935a7ff33d4ad1c03587820800af37030456063ab84caf0129f506d0586c","observation_id":"2291968b-3534-41b4-9342-705809ab650d","resolution":{"observed_at":"2026-08-05T10:38:35.634444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.03895","last_updated":"2025-09-04T05:42:02Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T10:24:00.174135Z","submitted_at":"2025-09-04T05:42:02Z","title":"Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":2,"verified_fuzzy":21},"total_outbound_references":35},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2509.03895."}