{"as_of":"2026-08-23T17:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0d817896119407c8d410469e3c1c10c28e9168df831fc36fd2be8d4924439c74","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T22:22:49.388523Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2606.07102/citation-record","integrity":"/paper/2606.07102/integrity","json":"/paper/2606.07102/citation-record.json","paper":"/paper/2606.07102"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T22:22:49.388523Z","title":"Out-of- distribution detection: A task-oriented survey of recent advances,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:4a651a95e1bd57e2197d72aa27c6463b9c6b861e159bd10990a83087884828fa","observation_id":"434d773f-ebdc-4b18-acc5-91f6ae75c5a1","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:16fd700ae0985e119fcb980eef293401110437239eeacce07f1281d764335d6c","observation_id":"54bb9c4f-539c-43af-8059-c4fea3da80c5","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Learning transferable visual models from natural language supervi- sion,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:ed1389f394258cb3e603473d81589626390df9e3e7de3a04a75b33cb77053d17","observation_id":"94122c7f-2a40-4d7e-b472-197079266140","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Learning to prompt for vision- language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:f0b79255212f9cea4a675812a2c5747daaa678a4cf8292c13276419c85b9b33d","observation_id":"5069d0e2-9447-4091-a386-87ddf9fc792c","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Locoop: Few-shot out- of-distribution detection via prompt learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:3506e3ab14e0a552fcd82f83bc8f0adcb97df7d2b34ce9d1f54c0434bb06e521","observation_id":"422266e1-c564-4a7a-9a89-138e4a41d7d1","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Clipn for zero-shot ood detection: Teaching clip to say no,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:985fb6750bcb9b6fa375c4a7beaa307722205640c936137b129696c51fab130e","observation_id":"d6e89b16-05ac-4f0e-aca1-ead77ee79bcd","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:37b1a29b55d6203617de387063db51e02664b2b4e4f665b57d202a1d0c7a362f","observation_id":"51e04e83-deed-4a8e-923e-633555dc2b9a","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.20918","last_updated":"2024-12-30T12:57:31Z","snapshot_observed_at":"2026-08-17T02:24:28.125169Z","submitted_at":"2024-12-30T12:57:31Z","title":"Uncertainty-Aware Out-of-Distribution Detection with Gaussian Processes","version":1},"cited_work":{"arxiv_id":"2412.20918","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.20918","snapshot_observed_at":"2026-07-02T16:47:09.938266Z","title":"Uncertainty- aware out-of-distribution detection with gaussian processes,","venue":null,"work_id":"afb95fcd-846c-4510-b7aa-872abaa0499b","year":2024},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"cited_paper":"/paper/2412.20918","citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:f4a0b5d16a13135fe748b6ec99d4d52b106ada9633cac4e1ce06a1aa1976bd83","observation_id":"18ca1463-2356-4990-a1e2-07c86485ce7f","resolution":{"observed_at":"2026-07-02T16:47:09.939667Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-06-27T22:22:49.388523Z","title":"Ima- genet: A large-scale hierarchical image database,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:f7601cd38599eb2ba021beb3a105c22ed016b9fba765b87d7b32b5d96d071382","observation_id":"60bf9644-a347-4f5e-9722-a0fdeb05b516","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"A baseline for detecting misclassified and out-of-distribution examples in neural networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:4b6b136de9eb222cd247073edc93b438853b17411cc7cc929631690498bdb713","observation_id":"bd240a55-6df7-4a01-b5e1-1d333ca53881","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Energy-based out-of- distribution detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:2ea88849b5f3fd777d56b17aaa59a8966ce0e1e13977cb091df29af1be0cac96","observation_id":"b6687c64-2d89-42f6-add0-fb475bc9a33b","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Vim: Out-of-distribution with virtual-logit matching,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:2bc226d9a6f8ad53a206d92e862a6d9946a9f5cb0a2ca415964f821a73c180ae","observation_id":"6ca66029-15ef-4c45-90f8-06569e062eee","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Out-of-distribution detection with deep nearest neighbors,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:82764d4813ea88ab87e6e2cdee480c9461bf371e5f2699502c540e1eac7707a7","observation_id":"e11dadbc-a17a-4d36-979e-bb58b7d72921","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Extending binary neural networks to bayesian neural networks with probabilistic interpretation of binary weights,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:4dbfd7c4a135a967262efe2d755e5a88bb17aa29836b6b618f88f35579f83b38","observation_id":"dd8a3c41-563c-4556-b416-bf034715c955","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Out-of- distribution data detection using bayesian convolutional neural network with variational inference,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:ea21601a2276efa0207acc11dacfd920d0d0d57964b73078f518a06136351b07","observation_id":"564e7696-881a-427f-a6e2-2072fc9972c8","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Delving into out-of-distribution detection with vision-language representations,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:edbe34d2ff076c0806cfa82af1505f9455da9d82b795fbe6da385ccec2e820e1","observation_id":"db0fd1c6-1588-4d96-ab3c-f714d684700d","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Gl-mcm: Global and local maximum concept matching for zero-shot out-of-distribution detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:4a2a2db4873ecd000be49e9c68b2df1c194bc2248e8a5a2abefc30568458a61c","observation_id":"959b4e85-55d5-4008-88a2-80c4386cdee7","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Tip-adapter: Training-free adaption of clip for few-shot classification,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:de9edbca829a37ebf7e6f6008e474c5e09d2f54e39f7d2fa58ea683581d77a5b","observation_id":"91ff66a6-a1dc-4132-ac5d-a5312eba884a","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16146","last_updated":"2024-05-25T09:34:59Z","snapshot_observed_at":"2026-08-18T15:49:54.283951Z","submitted_at":"2024-05-25T09:34:59Z","title":"Dual-Adapter: Training-free Dual Adaptation for Few-shot Out-of-Distribution Detection","version":1},"cited_work":{"arxiv_id":"2405.16146","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.16146","snapshot_observed_at":"2026-07-02T16:47:09.940619Z","title":"Dual-adapter: Training-free dual adaptation for few-shot out-of-distribution detection,","venue":null,"work_id":"6f2927c8-c247-41f8-ac53-831502d1816b","year":2024},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"cited_paper":"/paper/2405.16146","citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:4625d98c1ad6ba7d53df3db0156fba7ce00fb84254c9cc197050b93cdd155fa1","observation_id":"b40b4ff5-1278-459e-98aa-12d34f16bfc5","resolution":{"observed_at":"2026-07-02T16:47:09.942523Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-06-27T22:22:49.388523Z","title":"Non-parametric outlier synthesis,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:65ab6328bc569e52e4f9d28d7a88f92992d2a45e02d1fb4e2d9dcfea8e91a593","observation_id":"567bab5f-b2dd-4474-844b-4afb12fe0bc2","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Setar: Out-of-distribution detection with selective low-rank approximation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:48ce4a08cd731c4ccffbdb135a2d6d6de7bf31cf99c954c637210aef14bcc321","observation_id":"013ec0f1-cc0e-4339-a9e9-2f62421edfde","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Exploring the limits of out- of-distribution detection,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:5452164cf498f63f02e0ef4ad90ec99e6a2bee42dad389b1430dcde7f6a3ae29","observation_id":"74bfbc6b-3a08-401a-9aa0-6a61efe1a685","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Enhancing the reliability of out-of- distribution image detection in neural networks,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:048c2b9ed9ad74a865a5873fed22dcd24438c34d1c59ea4c55a4411e440aeb6a","observation_id":"792df806-bd51-4bf3-a8c3-7a1643372156","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"The inaturalist species classification and detection dataset,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:6c22bec5b9b11ed3fe001cb66bfb8a4125f9cb36f5a38dbc70cd307942380732","observation_id":"0a0e1a3e-adc9-476e-b603-9715ee5edb7f","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Sun database: Large-scale scene recognition from abbey to zoo,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:38ff72597f75f259b9d3e45a5d5b5e78cd37604b58505e2432959598f7aa6531","observation_id":"fc970cc3-e9b6-499d-9332-ee196d7eeb49","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Places: A 10 million image database for scene recognition,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:2ff369f063315a868a6d2596849d20dea3fe7f49f088a18e45f7d6743570dfa1","observation_id":"c1ca8484-032c-4334-8ee2-260f5995f81d","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Describing textures in the wild,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:65b83d68438c794270917b7004511b4214489932d27bbe7253347ed1b3924c83","observation_id":"ff9307b1-aa5d-49fa-8bc3-fc70eb3697a1","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:02ec487c888bf15cc3f8648a95ea2124044ac579eaccc37fa08f9c740eb360df","observation_id":"744d6ccb-42ed-4a28-88c8-9763e4f62e5f","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","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":"2026-06-27T22:22:49.388523Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-27T22:22:49.388523Z"},"links":{"citing_paper":"/paper/2606.07102"},"observation_digest":"sha256:12f3957f2adf8274d40cf8e0aac664638123702de34c48b39728fe9cfe2a06c8","observation_id":"b1b5f8bd-742d-4c54-8f17-e9a73833d42d","resolution":{"observed_at":"2026-06-27T22:22:49.388523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.07102","last_updated":"2026-06-05T09:53:30Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T17:44:42.415971Z","submitted_at":"2026-06-05T09:53:30Z","title":"GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":2,"verified_fuzzy":0},"total_outbound_references":29},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2606.07102."}