{"as_of":"2026-08-13T12:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d6d772abb2f61c568d9110602d1009826013444b67cb6671707360b72b128c59","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:30:28.054866Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2505.21920/citation-record","integrity":"/paper/2505.21920/integrity","json":"/paper/2505.21920/citation-record.json","paper":"/paper/2505.21920"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:30:21.664744Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:21.664744Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:725cea5b1129de743bc53122539708016520725ad39370c85b10bc3623a2a033","observation_id":"5c36f711-080a-406d-a188-17547f875cd7","resolution":{"observed_at":"2026-08-07T13:30:21.664744Z","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":"2026-08-07T13:30:37.206425Z","title":"X., Damianou, A., Lawrence, N","venue":null,"work_id":"a44a4ad2-dd25-4f52-a523-7e993ef767a0","year":2019},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:21.814832Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:b5c72f403d19031f1f985a0e02b0d13c7a804680d3168da03e780d3511ccde76","observation_id":"02dc8277-12ab-4522-95d2-b874665451ca","resolution":{"observed_at":"2026-08-07T13:30:37.344746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:36.977408Z","title":"B it F it: Simple parameter-efficient fine-tuning for transformer-based masked language-models","venue":null,"work_id":"324739c9-5d3c-4592-83ae-6f6e0c84cca5","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:21.935249Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:e57058cb7a162bea6dc874962e34a3ce5afa8d8e63c60b9468beafb1d7e3bb8b","observation_id":"ef60692b-03df-4e7e-96d0-3dbe1e775b42","resolution":{"observed_at":"2026-08-07T13:30:37.064178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:22.064824Z","title":"J., Fern \\'a ndez-Esparrach, G., Gil, D., Rodr \\' guez, C., and Vilari \\ n o, F","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.064824Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:54a01d1ae78b8fb7612cd69f37a159cc7cd4d7f66f274483667a800765ce21a7","observation_id":"97a067f9-ebb1-47e4-80f9-02830be53cfd","resolution":{"observed_at":"2026-08-07T13:30:22.064824Z","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":"2026-08-07T13:30:36.746303Z","title":"Infinitely divisible matrices","venue":null,"work_id":"e4df0df9-98b5-4ed6-8fe3-7e4cc6917bc4","year":2006},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.234834Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:4a8aede9e9698341f5d6e883fb14d3dfa38ad4d4ddd80ab76e3d41568a87c486","observation_id":"9dd5c072-951e-4b23-bb16-068c6e664730","resolution":{"observed_at":"2026-08-07T13:30:36.832939Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:36.580953Z","title":"Convex optimization","venue":null,"work_id":"f4c91b2d-544e-4892-b7db-eaf5503252bf","year":2004},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.332040Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:c43326e3d709c0c407d783510fb06f05737471e84abf8690819d76f5892ab8b4","observation_id":"cb0bd8a6-838f-4126-9085-1b013de9e36d","resolution":{"observed_at":"2026-08-07T13:30:36.670677Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:36.385859Z","title":"Pkd: General distillation framework for object detectors via pearson correlation coefficient","venue":null,"work_id":"1841e624-8f62-4086-b88d-5d54fffbc918","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.440539Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:df17a1acb9a895f83dc538f2eb69df64addd40b8771c64256c68f0a45c673d92","observation_id":"72bafcc3-ff0e-4b45-908c-af9b65076120","resolution":{"observed_at":"2026-08-07T13:30:36.482669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:36.149306Z","title":"All about structure: Adapting structural information across domains for boosting semantic segmentation","venue":null,"work_id":"ebb9b6d9-567f-4ba8-ad96-b71c8a0155e0","year":1900},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.562353Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:99b4c45ef5ba7b72824a952d33f145d038a9f2a7ada1c8898d538cd4f1ddde20","observation_id":"1ceff2a6-4037-4034-9df2-f9726d9d16e2","resolution":{"observed_at":"2026-08-07T13:30:36.281621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:35.974887Z","title":"Cross-layer distillation with semantic calibration","venue":null,"work_id":"77bc91eb-cf35-43db-b7f7-a33697d024fb","year":2021},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.664235Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:1a9c85cb917b1e8b85baf3ac25be51550101616ef74f380e041c7bb86b19bfc6","observation_id":"6628f75b-7dc8-42b6-82ef-a3bdf122c3b6","resolution":{"observed_at":"2026-08-07T13:30:36.034343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:35.779714Z","title":"Distilling knowledge via knowledge review","venue":null,"work_id":"a127c37b-9952-4ab9-86c2-6d063dbe69c7","year":2021},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.746601Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:5841eaa6276697da8dbfd5df13329e38c69edddabb487d9104812f0331be62cc","observation_id":"553a294b-5e63-4da2-88b9-46b5e74ef16f","resolution":{"observed_at":"2026-08-07T13:30:35.889609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:22.825613Z","title":"Adaptformer: Adapting vision transformers for scalable visual recognition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.825613Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:89536bf61a1905aa3e98662bb62bca2ee3175b514a8c36254f4b285cb138ce4a","observation_id":"e7eb9969-e2b5-4d27-89b2-84740c10a13e","resolution":{"observed_at":"2026-08-07T13:30:22.825613Z","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":"2026-08-07T13:30:35.640892Z","title":"Sam-adapter: Adapting segment anything in underperformed scenes","venue":null,"work_id":"95b99bf1-06ee-4985-b736-b62cb6a1f5f2","year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:22.921892Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:f6fbda3e9a6325b00cbfed1d1f6f57b372d9021da6c3f40551caa8e0a71b7d6f","observation_id":"5c2f106b-85a0-4bad-8e42-63819d5992e4","resolution":{"observed_at":"2026-08-07T13:30:35.701345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:35.395757Z","title":"C., Gutman, D., Celebi, M","venue":null,"work_id":"53ee236a-4237-4c86-848e-e73590e10077","year":2017},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.010703Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:a75c02075d7cb71a6a0cd05119f871848fcfcdfebed0361cd0de15d157fad2be","observation_id":"8461accf-b2a8-4ed6-a229-2d6b4dfa32d3","resolution":{"observed_at":"2026-08-07T13:30:35.526071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:35.189950Z","title":"An efficient segment anything model for the segmentation of medical images","venue":null,"work_id":"698abc5e-8bef-47d6-90e0-c0433b5f1e3d","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.112684Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:69834f41c254e8cd5193bf748571d0a5db40e97c160c929a0b6f28bfb067ae9c","observation_id":"cbc5fb27-7706-4425-8317-94113456f849","resolution":{"observed_at":"2026-08-07T13:30:35.292656Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:34.992291Z","title":"Optimal randomized approximations for matrix-based r \\'e nyi’s entropy","venue":null,"work_id":"017f3bd4-6b7f-4051-a24f-c895d39fdfba","year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.218137Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:108abf91c7e3f222c544ffd6c3da7fa51878e1cfc03dc841139f285ecf5b4340","observation_id":"3ac66ef4-c97d-478a-b620-d1e5e89100b7","resolution":{"observed_at":"2026-08-07T13:30:35.106794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:34.828540Z","title":"Camouflaged object detection","venue":null,"work_id":"49951b02-0f09-49de-a23a-a5cb63045909","year":2020},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.310057Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:b8376c3434a9c6c2b8b723866f99b347fe012e999507f04d6c101a45eac84da8","observation_id":"1e57c501-92e2-41fb-b0e7-7bb75d477c75","resolution":{"observed_at":"2026-08-07T13:30:34.911989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:34.592889Z","title":"Pranet: Parallel reverse attention network for polyp segmentation","venue":null,"work_id":"b8af0f62-eadc-4d88-82ff-28816ae92baa","year":2020},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.423856Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:7183d49a80a47e37dc877279f6cd042fa8b11d652e4e2a9ec15f13f9c9629dd2","observation_id":"296415be-9324-49ed-9095-72d1be71fa93","resolution":{"observed_at":"2026-08-07T13:30:34.699345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:34.410754Z","title":"Computationally efficient approximations for matrix-based r \\'e nyi's entropy","venue":null,"work_id":"76a1b0a4-97e1-463b-ba88-73fe45e64ffd","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.508836Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:33cbf3e066ae595804e2f0ffcdac15af775766256d538c13ff575465859340af","observation_id":"20a13996-6da4-40c3-b387-6853e5ad7e52","resolution":{"observed_at":"2026-08-07T13:30:34.502933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:34.248661Z","title":"J., and Tao, D","venue":null,"work_id":"fbfe0b9e-b3dc-467c-851b-bc792a404ff6","year":2021},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.644890Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:927ef21746ec185c7c36d9aad89d3073bf3da93bdc86e331586952050b93e745","observation_id":"44204db4-da0e-4fd6-ae13-ad0dd5ea61b7","resolution":{"observed_at":"2026-08-07T13:30:34.345889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:23.733961Z","title":"Cycada: Cycle-consistent adversarial domain adaptation","venue":null,"work_id":null,"year":1989},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.733961Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:2ec37a8bffd5bf250f61de60580bb7beabeb6b6575fb749abecff89dc241d217","observation_id":"0ad622ae-8f78-49ca-aada-dfbaea0ce161","resolution":{"observed_at":"2026-08-07T13:30:23.733961Z","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":"2026-08-07T13:30:34.009497Z","title":"J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., Chen, W., et al","venue":null,"work_id":"70f0b11c-8589-4e32-87d8-804045885d83","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.812965Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:4f90344b1cd8c5234e0a3631a264819d9e6fd6b424a23597638586b83425bb47","observation_id":"a4bf06c2-f4a9-4887-bdda-b207adbdace6","resolution":{"observed_at":"2026-08-07T13:30:34.049185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:33.820423Z","title":"Multi-level adversarial network for domain adaptive semantic segmentation","venue":null,"work_id":"1185513e-263b-44c9-a373-69477a5c3a1a","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.937824Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:16973f8b3f84474a236ef3dc8308ab5e7b4e94ad66ac91dd147538fa17e93e7c","observation_id":"58169081-2562-4e48-9a36-e45b42742a59","resolution":{"observed_at":"2026-08-07T13:30:33.896424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:33.662971Z","title":"H., Riegler, M","venue":null,"work_id":"6ef5ff62-8eac-4802-93e0-48e65a0ec352","year":2020},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:23.989153Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:e92f94b3966738834e76e9133ea75b0c28ee2cef0d96bfb376b83be1f33a73e6","observation_id":"ac64dd48-8620-46dd-b796-439ee23f49f3","resolution":{"observed_at":"2026-08-07T13:30:33.733755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:33.467412Z","title":"Segment anything is not always perfect: An investigation of sam on different real-world applications, 2024","venue":null,"work_id":"e7c1e9c7-3b01-41e5-a95b-c999dd2e668a","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.055538Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:836ba23f6578d3fc707deae9c9430cd8fe3a09e8a64f8a09077df8c1da24abe6","observation_id":"671803da-9cdc-417c-931d-e36d005d89de","resolution":{"observed_at":"2026-08-07T13:30:33.571564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:33.267017Z","title":"Segment anything in high quality","venue":null,"work_id":"22d56071-69e7-499a-9ac9-336745fe94b2","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.121004Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:9e198845438d2be40bab3d643967af4dc58b76570ccfe77429fb5481837862f4","observation_id":"97df1376-6dc3-4e28-9cc6-3be56e18c7a7","resolution":{"observed_at":"2026-08-07T13:30:33.370932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:33.059156Z","title":"Qr decomposition on gpus","venue":null,"work_id":"ba40b2d7-3ebf-400c-bee1-f1bde99cdea7","year":2009},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.192602Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:1ffe532a03e7cbc8e00858a49f58444a257fe3dfbc960968f24899abdc54788a","observation_id":"ecd16b16-7969-4b25-8e57-b870504bc57f","resolution":{"observed_at":"2026-08-07T13:30:33.160098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:24.245824Z","title":"C., Lo, W.-Y., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.245824Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:8c89e92500fcc099f131a6d85c7d5665c47f1d3ec8c32f2044b808a80432e0a0","observation_id":"c8c6b2b4-9869-4a75-ac46-efb2a0a0fa18","resolution":{"observed_at":"2026-08-07T13:30:24.245824Z","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":"2026-08-07T13:30:32.839359Z","title":"Improving adversarial robustness via information bottleneck distillation","venue":null,"work_id":"19471e56-7c7f-4bc5-8b5c-be639726c210","year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.304984Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:e9653ca8461a31da9756f2e61def54a5c074161ddff5e25ea5f9f5f1d73c796b","observation_id":"1986c729-53f6-4cae-94b7-e95a373c5c5c","resolution":{"observed_at":"2026-08-07T13:30:32.925823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:32.598896Z","title":"V., Nie, Z., Tran, M.-T., and Sugimoto, A","venue":null,"work_id":"a547c3b5-bff9-48a6-8ae1-802b7cbc4b9e","year":2019},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.378580Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:09428364363b7d7ce5d957b799d2d8758ff9bbfc586774deb71b7cd151c9bc41","observation_id":"f1471d50-2630-4a40-a90f-cdf31d356c0e","resolution":{"observed_at":"2026-08-07T13:30:32.674364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:32.345252Z","title":"Invariant information bottleneck for domain generalization","venue":null,"work_id":"e298c0fb-fbab-455d-bb83-ddfa1eda265a","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.604912Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:a2d465295a7d4ba2e258950eec2e5c659a0950641015e29981504da9a4639b74","observation_id":"27645bcd-2369-41b1-98d6-ad8e93484018","resolution":{"observed_at":"2026-08-07T13:30:32.472289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:32.176772Z","title":"A stepwise domain adaptive segmentation network with covariate shift alleviation for remote sensing imagery","venue":null,"work_id":"c8af65e5-db66-42c2-b502-4a41b8aaa987","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.669026Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:fd237e8ad151428b235f0d81b1c08b8fe7a515819eaab66550f416ab75f53e95","observation_id":"fb7908b2-ca73-4893-8c2d-dd244be6df05","resolution":{"observed_at":"2026-08-07T13:30:32.278071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:31.978432Z","title":"Decomposition-based unsupervised domain adaptation for remote sensing image semantic segmentation","venue":null,"work_id":"e251e365-0921-4f8d-be41-33809f9719cd","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.771157Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:19e69ead9e1ad5f6dcd95aa59c264faf20c74fe892e858e4c30f25fd6f415166","observation_id":"55069a30-11db-42aa-a76e-311e0af55447","resolution":{"observed_at":"2026-08-07T13:30:32.057791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:31.720322Z","title":"K., Manganelli, B., and Sa \\`a -Garriga, A","venue":null,"work_id":"95fb0687-71d3-4cbd-b097-a4805baccbef","year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.815166Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:04081edaff2c55f1c8693fde9cd50cab7df39331278ee4a5ff0a1a362caf1ba9","observation_id":"076a0d6f-e793-4326-ad60-74f936079ad0","resolution":{"observed_at":"2026-08-07T13:30:31.869782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:31.486182Z","title":"Machine learning for aerial image labeling","venue":null,"work_id":"609c2e93-014f-4e0d-b83d-bd58243d3e25","year":2013},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:24.925408Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:ecef7d9181e789d05ae7e00a4b10a7e37aa7f4e815c5b5649d35524e061ee0c9","observation_id":"edb9fd26-6833-460c-8b81-5749a34a5cba","resolution":{"observed_at":"2026-08-07T13:30:31.586201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:31.284963Z","title":"Probabilistic knowledge transfer for lightweight deep representation learning","venue":null,"work_id":"286b224d-858c-4d4b-8ea1-0740c9b2be8e","year":2020},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:25.025837Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:bb245556e9afc957ed127a053b2f11e224b855a2fc34ac3d9d17760b2ee2796d","observation_id":"397a7a44-bfa3-4a50-92f4-f0d7b3fd87c5","resolution":{"observed_at":"2026-08-07T13:30:31.387589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:31.139749Z","title":"Learning to adapt sam for segmenting cross-domain point clouds","venue":null,"work_id":"c6eb10f1-d396-4a81-968a-68a20c52081d","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:25.232212Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:87a43355c083fe2d54cf0e95e4a45f1991edb66f762b3884e909331f7f4c3e05","observation_id":"9536da5f-a7b6-4c4e-ac4d-b52ca2839a46","resolution":{"observed_at":"2026-08-07T13:30:31.215752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:30.942673Z","title":"Parameter efficient fine-tuning via cross block orchestration for segment anything model","venue":null,"work_id":"02831a42-56ef-42e7-981c-69bbdc214bb0","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:25.374844Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:82a4c32e2c2becdc374b5da94ad0f466bf4355ce678d7684200828e9f708af40","observation_id":"ad34329c-f1d1-4d87-92e7-b00ee9707e14","resolution":{"observed_at":"2026-08-07T13:30:31.004770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:30.757913Z","title":null,"venue":null,"work_id":"a1ef5ad7-35cb-4783-9151-bee1f7948a6b","year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:25.630023Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:590116459e113ddc7a63bfb7ac526d8493dde2c77c03ee6fba1751b071f155d4","observation_id":"3436b5b9-13da-4e15-93da-aba1eb2b4225","resolution":{"observed_at":"2026-08-07T13:30:30.887040Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:30.554604Z","title":"Sam 2: Segment anything in images and videos","venue":null,"work_id":"14725524-c11b-4953-a946-3eab15764d25","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:25.744124Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:240b98db9053804103f49e5e968206cda653601f453e883112e0e43be7c8b845","observation_id":"f4c6d994-048a-4f26-b8bf-3f93f6cdb4a1","resolution":{"observed_at":"2026-08-07T13:30:30.664757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:30.411488Z","title":"Fastsam3d: An efficient segment anything model for 3d volumetric medical images","venue":null,"work_id":"64c9c932-4207-4a91-8fac-c09d31a741a6","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:25.854858Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:3f4cce2e09f0b00f0a846edb14f953c0cac5a8d5f3069558ae15f76cd591e02b","observation_id":"6147f86a-7f6a-4784-8d81-350f5abad755","resolution":{"observed_at":"2026-08-07T13:30:30.469938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:30.269850Z","title":"Tinysam: Pushing the envelope for efficient segment anything model","venue":null,"work_id":"847f9d11-d134-4acf-97c8-8f88ef4d5809","year":2025},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:26.000659Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:f089abcf7917c62906490f45db75508ce0302aa66709dd0c688d1c36fde41b51","observation_id":"7b580c7c-e118-4cd1-904d-4ed7a76c57e2","resolution":{"observed_at":"2026-08-07T13:30:30.296258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:30.049036Z","title":"Animal camouflage analysis: Chameleon database","venue":null,"work_id":"a6718df4-19d0-48b8-84f7-154ee1d6e09e","year":2018},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:26.124959Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:87a57f44e38f053951bce7f4f59997ced8013653a6f7f28364a6d308f10114f6","observation_id":"42a0e7b1-9158-4f3e-aaa8-afd06cbb8ced","resolution":{"observed_at":"2026-08-07T13:30:30.172683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.17803","last_updated":"2024-07-29T08:43:48Z","snapshot_observed_at":"2026-08-13T04:30:14.328412Z","submitted_at":"2024-01-31T12:53:11Z","title":"SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenes","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.17803","snapshot_observed_at":"2026-08-07T13:30:26.254954Z","title":"Simada: A simple unified framework for adapting segment anything model in underperformed scenes","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:26.254954Z"},"links":{"cited_paper":"/paper/2401.17803","citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:8ab3b7f724a4bfc3467caee2f562a45b75fa24d4d64f98e3827f1b54f9e7015f","observation_id":"c1200353-8478-4e67-92f4-faffa0db0a81","resolution":{"observed_at":"2026-08-07T13:30:26.254954Z","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":"2026-08-07T13:30:26.394894Z","title":"and Zaslavsky, N","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:26.394894Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:3db529ef94be7a2af92185b50b4d1ed8a82a615ca1ef65feaf71cc7083a7a932","observation_id":"ca91978c-1206-47f7-a227-95695c2183d3","resolution":{"observed_at":"2026-08-07T13:30:26.394894Z","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":"2026-08-07T13:30:26.470952Z","title":"Samcl: Empowering sam to continually learn from dynamic domains","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:26.470952Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:11fb2deb7e00ea489ddca6930475a0bc5a79a37eca9ac0b88db0876a326193cd","observation_id":"2cb95d32-6e5a-4a59-aeab-fe4ece7ef222","resolution":{"observed_at":"2026-08-07T13:30:26.470952Z","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":"2026-08-07T13:30:29.861677Z","title":"Medical sam adapter: Adapting segment anything model for medical image segmentation","venue":null,"work_id":"3a3bc171-5502-47ce-8588-cc44da17b7c5","year":2025},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:26.665293Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:1fe308767e8c64584bbd4650fec5f79b59afd9a45fa448ce824ec8d7073b7a34","observation_id":"33bee818-b6e5-4feb-9096-d51bc622624c","resolution":{"observed_at":"2026-08-07T13:30:29.922288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:29.673439Z","title":"Cat-sam: Conditional tuning for few-shot adaptation of segment anything model","venue":null,"work_id":"feeb2014-e106-494f-85b8-51447805e6c1","year":2025},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:26.974915Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:da1e656626c3bd6e8bc12264fec25860faa307ef5d280fd203d995f9afbd1024","observation_id":"17e0f2a9-9c70-440b-92fc-e499b4f41969","resolution":{"observed_at":"2026-08-07T13:30:29.734746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:29.518097Z","title":"Dirl: Domain-invariant representation learning for generalizable semantic segmentation","venue":null,"work_id":"ef0606a9-a245-416f-9072-ce77a43c2f32","year":2022},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:27.129686Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:c6cdb213a64c8670eab42c2ccf4458409b56ed9c29438fbd4be0607154f7fc69","observation_id":"249e0e24-2f82-4f5d-aebd-9d0d71dae45c","resolution":{"observed_at":"2026-08-07T13:30:29.616550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:29.303627Z","title":null,"venue":null,"work_id":"46595677-c209-47f5-92ed-226e8117811b","year":2019},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:27.257221Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:3e3b9297754291766ede0fd63cd6c8504d3f83490b1d5239c7a4c460f36a70b7","observation_id":"3b516f58-c18f-4f25-a7d9-a59f742d2e7a","resolution":{"observed_at":"2026-08-07T13:30:29.409367Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.14289","last_updated":"2023-07-01T07:26:22Z","snapshot_observed_at":"2026-08-12T07:11:05.316372Z","submitted_at":"2023-06-25T16:37:25Z","title":"Faster Segment Anything: Towards Lightweight SAM for Mobile Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.14289","snapshot_observed_at":"2026-08-07T13:30:27.445076Z","title":"U., Bae, S.-H., Lee, S., and Hong, C","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:27.445076Z"},"links":{"cited_paper":"/paper/2306.14289","citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:ee424d9ea7521f10884400d0aa2d4bdfd899f34b7d3e048aca1eabcb8a7642cd","observation_id":"81f43965-ed0f-49d7-aa31-04dba26f3694","resolution":{"observed_at":"2026-08-07T13:30:27.445076Z","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":"2026-08-07T13:30:29.076099Z","title":"Blo-sam: Bi-level optimization based finetuning of the segment anything model for overfitting-preventing semantic segmentation","venue":null,"work_id":"c1141200-3d59-440f-aabb-09a910365903","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:27.584938Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:b870732ca2a361abf7b6297cefba99c9c60d8f99f4cfc6be77d9292b50e29011","observation_id":"33d94eb0-e15c-47f1-a909-6cc7bab4453a","resolution":{"observed_at":"2026-08-07T13:30:29.173006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:28.918543Z","title":"Distilling semantic priors from sam to efficient image restoration models","venue":null,"work_id":"b7f7712e-f7a9-4bcd-b43f-693ea6c79675","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:27.675262Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:74b2843d9d6bd364b1c445f87c33a27f31aea13260f24d01996a085264d8875a","observation_id":"2082b952-5aa8-4128-88e4-e738813f8653","resolution":{"observed_at":"2026-08-07T13:30:28.938367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:28.814435Z","title":"Learning shape-invariant representation for generalizable semantic segmentation","venue":null,"work_id":"10c5e4e7-59ce-48ed-9187-d6f5edcec925","year":2023},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:27.859488Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:fd52d7628a9429c70131dbec27a4957e0bc2d0d5680f4f591b5f92a67f264ad4","observation_id":"233c5e49-464a-4234-a7fd-8d4e88888de0","resolution":{"observed_at":"2026-08-07T13:30:28.845165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:28.692227Z","title":"Convolution meets lo RA : Parameter efficient finetuning for segment anything model","venue":null,"work_id":"3e3e47b2-b861-4373-8b78-dae5ca1d104b","year":2024},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:27.964753Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:44fc0935aa1d6ef3f5f4d864d5065358bcd38fa279d1fb582ee976c2a7aee4ad","observation_id":"1175ea38-f9f4-4d5f-9923-23cd7a06b67e","resolution":{"observed_at":"2026-08-07T13:30:28.739790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-07T13:30:28.527809Z","title":"Knowledge distillation by on-the-fly native ensemble","venue":null,"work_id":"f62dc543-3217-4279-8503-26c0055c3e34","year":2018},"citing_paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T13:30:28.054866Z"},"links":{"citing_paper":"/paper/2505.21920"},"observation_digest":"sha256:e8bf18bee35eed5199b9925dbe4c173e1032b762004676d81546cce40f37ed37","observation_id":"9feb730c-cfe0-4e72-b9dc-9ba4bd2efa04","resolution":{"observed_at":"2026-08-07T13:30:28.580618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.21920","last_updated":"2025-06-03T06:01:35Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T17:36:02.840860Z","submitted_at":"2025-05-28T03:09:22Z","title":"InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":44},"total_outbound_references":55},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2505.21920."}