{"as_of":"2026-08-13T04:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:73007f767f5e517e519d24c69b242c9121e0fc2a7348259f601afcc849a0bad3","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T14:03:32.144556Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2411.15736/citation-record","integrity":"/paper/2411.15736/integrity","json":"/paper/2411.15736/citation-record.json","paper":"/paper/2411.15736"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.801659Z","title":"Clipood: Generalizing clip to out-of-distributions,","venue":null,"work_id":"b37a01d8-7751-41ca-888e-c47946458ecf","year":2023},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.547151Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:1cd73bfc97ab41bbee3f8e7f6ac1ee629131b275990e1aafd6ca3ce696253e58","observation_id":"68161752-d774-4985-b459-7908c6d417b6","resolution":{"observed_at":"2026-08-12T14:03:32.805240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.02136","last_updated":"2018-10-03T07:32:57Z","snapshot_observed_at":"2026-08-02T06:41:33.803920Z","submitted_at":"2016-10-07T04:06:01Z","title":"A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.02136","snapshot_observed_at":"2026-08-12T14:03:31.566837Z","title":"A baseline for detecting misclassified and out-of-distribution examples in neural networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.566837Z"},"links":{"cited_paper":"/paper/1610.02136","citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:abe40db70ef226dba6b147a2baa832578cc376816535e95f639dd3de24373337","observation_id":"92c22080-4c77-4dfb-88a4-f26c440f5598","resolution":{"observed_at":"2026-08-12T14:03:31.566837Z","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":"2026-08-12T14:03:31.579924Z","title":"Learning transferable visual models from natural language supervision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.579924Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:f8a2385f816750523d36aadb2ff1f221249e47d581c6ffeefa1bb38fea4177b6","observation_id":"09197296-b061-4259-b8dd-cef361fc1986","resolution":{"observed_at":"2026-08-12T14:03:31.579924Z","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":"2026-08-12T14:03:31.584649Z","title":"Delving into out-of- distribution detection with vision-language representations,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.584649Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:309b519ab5ba5a75281987a048167d4da9e0fa4a06f2c79d51a14504b2cf1a66","observation_id":"a7c47a80-b304-41b3-ae16-912daa493a6a","resolution":{"observed_at":"2026-08-12T14:03:31.584649Z","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":"2026-08-12T14:03:32.718611Z","title":"Enhancing the reliability of out-of- distribution image detection in neural networks,","venue":null,"work_id":"1bfe1119-85b9-4c79-8c8c-5b7645ea7f2a","year":2018},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.589175Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:bc6cd7e06813bb36b3d70df41c467805adb0bf9d5ed5316d33cec58cdf36bdd3","observation_id":"78f0e9cc-cb2e-479b-9b26-77c6ca48eba7","resolution":{"observed_at":"2026-08-12T14:03:32.779157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.614074Z","title":"Vim: Out-of-distribution with virtual-logit matching,","venue":null,"work_id":"d8ee6414-22d3-4d4b-a609-8e9b8e029a28","year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.686389Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:a7861207fed73e38c54e90eeb8cc125255ce5040270ca61aabe0a00a68eb6348","observation_id":"5e012c01-3672-4765-8af1-bb73f2bbe191","resolution":{"observed_at":"2026-08-12T14:03:32.684221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.579090Z","title":"Out-of-distribution detection with deep nearest neighbors,","venue":null,"work_id":"7079df78-09b4-4dcc-b9a7-135ef34cf649","year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.771913Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:826a581f9f135b9caf31fc0f0a7676e2ff805af5d6667085ecb4f6e9e8a6597f","observation_id":"8c5ee34f-d2be-42c7-91b4-e377b6171d69","resolution":{"observed_at":"2026-08-12T14:03:32.582966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.566930Z","title":"Non-parametric outlier synthesis,","venue":null,"work_id":"bfcb77dd-fd04-4aac-8045-a9934537788a","year":2023},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.776349Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:bd03f3b857fd25eccbd72185d4f36e7f267774ad8cfd483580875a32c3c90430","observation_id":"44e40fc7-9189-4814-8054-f56c9351caf8","resolution":{"observed_at":"2026-08-12T14:03:32.571109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.555944Z","title":"Locoop: Few-shot out- of-distribution detection via prompt learning,","venue":null,"work_id":"e3e2cc11-1818-4603-a398-adea71c80d34","year":2024},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.781190Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:ba5b75422733b4adc9e4e879d55e31ba0a5b17346ee59ccd667e83dc6679680e","observation_id":"b57c5ab4-7bf4-4a4b-916c-f5aa673ed507","resolution":{"observed_at":"2026-08-12T14:03:32.559249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.543814Z","title":"Id-like prompt learning for few-shot out-of-distribution detection,","venue":null,"work_id":"3cd4d75d-99a0-412b-a85b-6ee64937b5eb","year":2024},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.785253Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:18f893c26891a301c0d665b9d42b3d6af98df63c905824159fbd5c45b7c58dd5","observation_id":"0932f8de-7add-4936-8398-e7eff4981647","resolution":{"observed_at":"2026-08-12T14:03:32.548010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.531750Z","title":"Invariant learning via probability of sufficient and necessary causes,","venue":null,"work_id":"de569b3f-65ad-408d-ad24-749d0f8a9cca","year":2023},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.788734Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:3809ebcbbbcf1cd2c6506e7b04c883c8feaf9afe77c0832011700556235b9f2b","observation_id":"7d17bb96-2d7d-4042-9c74-68911f6d664d","resolution":{"observed_at":"2026-08-12T14:03:32.536284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.519634Z","title":"Fd-align: feature discrimination alignment for fine-tuning pre-trained models in few-shot learning,","venue":null,"work_id":"9cbb8b2d-70c6-4919-b1db-56d67264c933","year":2024},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.792007Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:57e7bd2c078568b414180ade4f4c3467cdfbefe7d3957b7f4799177f3a976555","observation_id":"fb947c95-3cb0-4c7b-ae9f-25e7e3f56e5a","resolution":{"observed_at":"2026-08-12T14:03:32.524115Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.507215Z","title":"Learn to rectify the bias of clip for unsupervised semantic segmentation,","venue":null,"work_id":"f401b72e-92c6-4e63-b8b2-5500868b820e","year":2024},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.795106Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:31e45ff7056f7e87be957ab23a59949de109662625beb9b9fc103292c7c209a6","observation_id":"c06244e4-1f7e-43f1-899f-e0fea75a19a6","resolution":{"observed_at":"2026-08-12T14:03:32.511032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.03557","last_updated":"2019-08-09T17:57:13Z","snapshot_observed_at":"2026-08-07T01:39:40.489262Z","submitted_at":"2019-08-09T17:57:13Z","title":"VisualBERT: A Simple and Performant Baseline for Vision and Language","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.03557","snapshot_observed_at":"2026-08-12T14:03:31.798309Z","title":"Visualbert: A simple and performant baseline for vision and language,","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.798309Z"},"links":{"cited_paper":"/paper/1908.03557","citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:b9e1bb46ca4aea6e7e69e1d17d84ed4793fd7629deb479aa12735246544b1c4f","observation_id":"f97ff2f2-e49a-4077-b53c-7d950cff9b08","resolution":{"observed_at":"2026-08-12T14:03:31.798309Z","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":"2026-08-12T14:03:31.818972Z","title":"Vilt: Vision-and-language transformer without convolution or region supervision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.818972Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:23da5930131ef5a0fb618b9d472ad19544554a91f0d5f5c8ca82eb2f19197a41","observation_id":"433f1e1f-5371-4751-b44e-5ad4e40ac08b","resolution":{"observed_at":"2026-08-12T14:03:31.818972Z","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":"2026-08-12T14:03:32.437786Z","title":"Filip: Fine-grained interactive language-image pre-training,","venue":null,"work_id":"067d2e83-e0e4-451f-9200-7f791693c7f3","year":2021},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.848080Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:c4d1ca32e5a630305dafbc26128c7485ea77f45a85b977406aa176d2bd014c43","observation_id":"11deae5f-d29c-42d1-a1e0-4395feafa641","resolution":{"observed_at":"2026-08-12T14:03:32.465469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:31.935616Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:31.935616Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:8472a413f043943177d9b49d17c3a0a7eb30085596d32008e1b80f34b01e5904","observation_id":"56a1ab1e-a8db-459e-8561-b13983976c70","resolution":{"observed_at":"2026-08-12T14:03:31.935616Z","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":"2026-08-12T14:03:32.039264Z","title":"Learning to prompt for vision- language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.039264Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:ab1503bba38ef5b873933d3b342a146ae0d692dcafa845c5a09b15c433a6849b","observation_id":"2c3a5230-723c-4d46-b55e-9c8a0912b30d","resolution":{"observed_at":"2026-08-12T14:03:32.039264Z","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":"2026-08-12T14:03:32.091113Z","title":"Visual prompt tuning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.091113Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:3a74c6fe4adce7735d03727962070d60e5b439573562cb08787a7ec7393ab726","observation_id":"577d1cac-80a5-49bf-8083-4060c5b519ca","resolution":{"observed_at":"2026-08-12T14:03:32.091113Z","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":"2026-08-12T14:03:32.100637Z","title":"Maple: Multi-modal prompt learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.100637Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:2057c33af31f2d2d2bcdccc6937d36a25b5af416f4c0a817f24b9d88bed327f6","observation_id":"f5013914-ad39-4e41-8b35-27e8d651b7e8","resolution":{"observed_at":"2026-08-12T14:03:32.100637Z","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":"2026-08-12T14:03:32.103790Z","title":"What does a platypus look like? generating customized prompts for zero-shot image classification,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.103790Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:72e7736a0f873e65656e03b863cbb1e3bce15f0f254d3ee68436cebf76d68152","observation_id":"67889131-65ce-4577-b439-420af660df8f","resolution":{"observed_at":"2026-08-12T14:03:32.103790Z","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":"2026-08-12T14:03:32.325259Z","title":"Exploring the limits of out- of-distribution detection,","venue":null,"work_id":"0109128a-c925-4d3a-8a0a-dec5f0ac4e87","year":2021},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.108497Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:ba78afe6be66c3720c66ae70eb3ea4ae942e87394c59c6e67e365d6dd38f0c39","observation_id":"2568c39d-f085-4a05-92e0-26858d723787","resolution":{"observed_at":"2026-08-12T14:03:32.351623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.268697Z","title":"V os: Learning what you don’t know by virtual outlier synthesis,","venue":null,"work_id":"428fe312-e52b-4269-8778-6cf606c92ac8","year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.112419Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:573ab9159cc2dc6bd848207ec6e7100648a83b389c93418d02bcf8d4bd0694fe","observation_id":"72530f0d-6053-46ed-81f1-e7c6025a3319","resolution":{"observed_at":"2026-08-12T14:03:32.272455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.115320Z","title":"Amu-tuning: Effective logit bias for clip-based few-shot learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.115320Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:d2e24fdc1d4f1ff5d5255823d242b641a79e6f636f0b577c67a66f982c360304","observation_id":"bca922a0-0649-4996-b357-da6edbf2ea4d","resolution":{"observed_at":"2026-08-12T14:03:32.115320Z","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":"2026-08-12T14:03:32.118709Z","title":"Extract free dense labels from clip,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.118709Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:17f6adc6da4b6c8bf303d03e56d4685d838b98efcc122494f3b80790b285bd06","observation_id":"e9c78ab0-1e5d-428b-9eac-110ab5178883","resolution":{"observed_at":"2026-08-12T14:03:32.118709Z","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":"2026-08-12T14:03:32.122356Z","title":"Universal domain adaptation through self supervision,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.122356Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:8ce10aaac9f8f2616c85c75ccd56c112b9c426b29898422612e3bcfd720cd041","observation_id":"dd306e65-ce7f-4fa9-8c90-2b07cc9b2948","resolution":{"observed_at":"2026-08-12T14:03:32.122356Z","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":"2026-08-12T14:03:32.125888Z","title":"Prompt-aligned gradient for prompt tuning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.125888Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:b25463f730645e91522c285c308b0dea5c24aef21b65ecd2a3477794563f60bf","observation_id":"1d04b792-e842-4d9b-ba0b-1916b6a44f57","resolution":{"observed_at":"2026-08-12T14:03:32.125888Z","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":"2026-08-12T14:03:32.129815Z","title":"Imagenet: A large-scale hierarchical image database,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.129815Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:976232bfe996d8c47724c64e4de9009dea046189d1485138cf93fefd531043bf","observation_id":"82f82e20-f87c-4f4f-b115-f825025e14d7","resolution":{"observed_at":"2026-08-12T14:03:32.129815Z","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":"2026-08-12T14:03:32.133362Z","title":"The inaturalist species classifi- cation and detection dataset,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.133362Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:9f40c9fce89fc0059de2ed57bebabe29c22059e5f45a5ee8c50c37b9a29e3bc1","observation_id":"ea430d75-e9ef-44fb-978d-c60a08644177","resolution":{"observed_at":"2026-08-12T14:03:32.133362Z","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":"2026-08-12T14:03:32.137996Z","title":"Sun database: Large-scale scene recognition from abbey to zoo,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.137996Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:a3af5fac2afedde03f26cdb5819dfd940911a211f7e13b732cce020b9f386b81","observation_id":"7a975984-7177-4e07-8667-975c5fe92948","resolution":{"observed_at":"2026-08-12T14:03:32.137996Z","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":"2026-08-12T14:03:32.203342Z","title":"Places: A 10 million image database for scene recognition,","venue":null,"work_id":"828eb519-10e0-4905-8aba-d82785f0248b","year":2017},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.141304Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:0c1a522d9b10a3cfca7f93c24ccd83e19a7e4c49e0ed1edfe6c8c86e736b09dc","observation_id":"ff4bd18a-b841-4cd2-8f5e-c083a46d8f79","resolution":{"observed_at":"2026-08-12T14:03:32.208525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:03:32.144556Z","title":"Describing textures in the wild,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T14:03:32.144556Z"},"links":{"citing_paper":"/paper/2411.15736"},"observation_digest":"sha256:f623b395a17d53fc928066186c268713ee2692cdad3240b2918265d06d046ecb","observation_id":"a177b9a6-316e-4a62-879e-2f93cd970716","resolution":{"observed_at":"2026-08-12T14:03:32.144556Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.15736","last_updated":"2024-11-24T06:51:34Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T13:55:16.310790Z","submitted_at":"2024-11-24T06:51:34Z","title":"Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context Optimization"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":0,"verified_fuzzy":14},"total_outbound_references":32},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2411.15736."}