{"as_of":"2026-08-08T12:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f68fad4b8c4d52fec589e74f40cc866dc0e56e4c90e017a1e568d4c3f5573a34","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:00:07.248665Z","state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.11943/citation-record","integrity":"/paper/2507.11943/integrity","json":"/paper/2507.11943/citation-record.json","paper":"/paper/2507.11943"},"outbound":[{"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":"2026-08-06T17:00:06.359174Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.359174Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:9c9f7672ef310c1dca37589497b0347d4f440d9f4919508ed8e043ad406494f8","observation_id":"1d91b406-5da0-4861-a886-7677b368e664","resolution":{"observed_at":"2026-08-06T17:00:06.359174Z","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":"2026-08-06T17:00:06.429887Z","title":"Vision-language models for vision tasks: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.429887Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:7cf0c364e04bafb31c9eed5fd3768dc10d18bff3c877de73ed5fac894dc3afa2","observation_id":"9a0f0962-f014-4f62-9884-a5065176707f","resolution":{"observed_at":"2026-08-06T17:00:06.429887Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.09958","last_updated":"2020-12-17T22:33:14Z","snapshot_observed_at":"2026-08-08T07:03:53.580492Z","submitted_at":"2020-12-17T22:33:14Z","title":"Toward Transformer-Based Object Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.09958","snapshot_observed_at":"2026-08-06T17:00:06.519431Z","title":"Toward transformer-based object detection,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.519431Z"},"links":{"cited_paper":"/paper/2012.09958","citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:55731a9dc35c1c813c98a94f980e141491f3fb1ee4ed631711dd970473efbf09","observation_id":"ac8fa8c0-157d-4cec-8837-d66d5b273700","resolution":{"observed_at":"2026-08-06T17:00:06.519431Z","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":"2026-08-06T17:00:08.905299Z","title":"Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers,","venue":null,"work_id":"37815bf1-5877-49c8-a323-e3cd4f385d42","year":2021},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.580973Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:6af32b6db4a7336a0d1a3ea6c1eee3aa250c642cda0d829747e690a51500823a","observation_id":"ef57e44f-df98-4b9f-91cc-1b63ccbea7ef","resolution":{"observed_at":"2026-08-06T17:00:08.990551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-07T07:43:16.294957Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-06T17:00:06.662424Z","title":"Lora: Low-rank adaptation of large language models,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.662424Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:a2775f642535b3f4b22eedb51c4033b8d0212ae70a42cd6485e23dc3a8faae6f","observation_id":"9c9e2f77-7bfc-4c17-b142-f2155771ccdc","resolution":{"observed_at":"2026-08-06T17:00:06.662424Z","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":"2026-08-06T17:00:08.736265Z","title":"Melo: Low-rank adaptation is better than fine-tuning for medical image diagnosis,","venue":null,"work_id":"40bf9850-08e9-4eae-b73c-b24d23242580","year":2024},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.723328Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:94e1be91cc1a962234a49aac9c16354a83cf4879319233042914ce782af95d76","observation_id":"b5e00cd4-800c-4a74-a065-c83fca192c33","resolution":{"observed_at":"2026-08-06T17:00:08.790021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T17:00:08.515505Z","title":"An overview of compressible and learnable image transformation with secret key and its applications,","venue":null,"work_id":"fa45678e-2cee-4f4e-9a8f-e539dd461b31","year":2022},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.801348Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:d459e0e2aba375d9aba97291f53fa4ed4ed979cc733409f940e41fbb7f582055","observation_id":"7d968c71-2d71-46da-9f72-afd358a2b963","resolution":{"observed_at":"2026-08-06T17:00:08.656853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T17:00:08.313054Z","title":"Grayscale-based block scrambling image encryption for social network- ing services,","venue":null,"work_id":"b1fc9dee-7901-4c1f-b1ae-1e9ba57c9ab0","year":2018},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.863227Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:09f350b958f2fe1f185d72aafe707fdb7bd45e07e88710f08fca615b0f8c2fc7","observation_id":"4f26d0ae-0304-4856-aea0-e578ca60f839","resolution":{"observed_at":"2026-08-06T17:00:08.401383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T17:00:08.118843Z","title":"Privacy-preserving content-based image retrieval using compressible encrypted images,","venue":null,"work_id":"51394b41-2faf-43de-95e5-17a942049531","year":2020},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:06.942228Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:963106d4d4140ba274a7c72255eb9e2d8624689266cdab9afab81d3667a8e183","observation_id":"78fbbe2f-db0c-465f-acff-7b6fba7f9cef","resolution":{"observed_at":"2026-08-06T17:00:08.204443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T17:00:07.923782Z","title":"A protection method of trained cnn model with a secret key from unauthorized access,","venue":null,"work_id":"fd16ee8d-22ff-4fce-af20-6d2aa1380b9d","year":2021},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:07.031191Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:fc516593f233f9bf1e334fa0e03be491c05c91261db7082cd6cc8a1038ae72dc","observation_id":"f53c251e-0577-4383-a4e1-0183f1ef48f1","resolution":{"observed_at":"2026-08-06T17:00:07.996197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T17:00:07.777718Z","title":"Encryption inspired adversarial defense for visual classification,","venue":null,"work_id":"f91903d7-a697-4123-8572-82e10816c0dc","year":2020},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:07.099657Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:a939be26e7033f1411edfdf457abd11f764ad1bdd8e3f527845a7603080880a8","observation_id":"2efe996a-4f44-41ce-b41d-bd5c45e8b48f","resolution":{"observed_at":"2026-08-06T17:00:07.831871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T17:00:07.602417Z","title":"A random ensemble of encrypted vision transformers for adversarially robust defense,","venue":null,"work_id":"a0c2a43b-8e18-4ea1-9df1-32b09e3f5192","year":2024},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:07.162092Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:6c2524275f4aa5d0e2ba1526b6c38f6f9120252134700a90e3edc28cda257e16","observation_id":"7871c795-3aca-4d72-b4df-ecebb6c1b596","resolution":{"observed_at":"2026-08-06T17:00:07.683615Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T17:00:07.429817Z","title":"Domain adaptation for efficiently fine-tuning vision transformer with encrypted images,","venue":null,"work_id":"9ab6ddc9-0562-4ff3-a6ad-cd3238df3f64","year":2023},"citing_paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T17:00:07.248665Z"},"links":{"citing_paper":"/paper/2507.11943"},"observation_digest":"sha256:1dcaffb75eb132c7897b1f9e26431fcb13bf12f2bdb16124879937d694100894","observation_id":"266121ba-0196-45e4-81cb-9bc5d439a979","resolution":{"observed_at":"2026-08-06T17:00:07.489677Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.11943","last_updated":"2025-07-16T06:18:52Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-06T16:55:32.196244Z","submitted_at":"2025-07-16T06:18:52Z","title":"Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":9},"total_outbound_references":13},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2507.11943."}