{"as_of":"2026-08-08T10:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e88c3cd91a90827aadb41cba07fc5f8a0742492a08a629500cb26f53f42d1cd1","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:03:57.574610Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T21:34:48.709465Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-14T20:39:27.701693Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.00718","snapshot_observed_at":"2026-07-14T21:34:48.709465Z","title":"arXiv preprint arXiv:2506.00718 (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.13994","last_updated":"2026-07-09T15:26:35Z","snapshot_observed_at":"2026-08-06T21:42:03.113909Z","submitted_at":"2026-03-14T15:43:10Z","title":"Human-like Object Grouping in Self-supervised Vision Transformers","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-14T21:34:48.709465Z"},"links":{"cited_paper":"/paper/2506.00718","citing_paper":"/paper/2603.13994"},"observation_digest":"sha256:be2b9d7ce5ea3f6b2f98e42e85c39c4253b7c8c28262f4fff03625adca872327","observation_id":"136f44b0-0019-4248-a29c-237c99b2deb2","resolution":{"observed_at":"2026-07-14T21:34:48.709465Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"cited_work":{"arxiv_id":"2506.00718","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.00718","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"9b396bc3-e301-456a-9e16-2d20c356e1ba","year":2025},"citing_paper":{"arxiv_id":"2605.13047","last_updated":"2026-05-13T06:11:47Z","snapshot_observed_at":"2026-08-03T14:19:44.395808Z","submitted_at":"2026-05-13T06:11:47Z","title":"Revealing the Gap in Human and VLM Scene Perception through Counterfactual Semantic Saliency","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-14T20:35:08.286755Z"},"links":{"cited_paper":"/paper/2506.00718","citing_paper":"/paper/2605.13047"},"observation_digest":"sha256:272a4f80af0ce002cbd624803678bc95d75d81c054d394abe7d07543f7637a97","observation_id":"0baa2d9b-f328-472b-87cb-11e3afeae8e8","resolution":{"observed_at":"2026-05-14T20:39:27.707162Z","resolver_source":"arxiv_id","status":"verified_exact"},"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"}}],"links":{"evidence":"/evidence","html":"/paper/2506.00718/citation-record","integrity":"/paper/2506.00718/integrity","json":"/paper/2506.00718/citation-record.json","paper":"/paper/2506.00718"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:04:05.002314Z","title":"A century of gestalt psychology in visual perception: I","venue":null,"work_id":"9c40655f-3733-4ca8-a39b-b21361b2826b","year":2012},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:50.808915Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:836e19d3433246e5a31c237e620faba66053070f9fa816cb50165ffc8f070ca3","observation_id":"0d7c9f32-8a05-4bb1-9129-cfa8e792641a","resolution":{"observed_at":"2026-08-07T12:04:05.051994Z","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":"2026-08-07T12:04:04.816158Z","title":"A century of gestalt psychology in visual perception: Ii","venue":null,"work_id":"cd221a96-0ca1-4ccf-95e7-d6ff5ec8bd12","year":2012},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:50.902252Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:040f984e828caf5eb0f47ae6d1255242493497039a211bfac3adc7d405195831","observation_id":"e7ed026d-7165-4721-81ed-e4a786cdb43a","resolution":{"observed_at":"2026-08-07T12:04:04.915639Z","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":"2026-08-07T12:04:04.432135Z","title":"Untersuchungen zur lehre von der gestalt, ii.Psychologische Forschung, 4:301–350, 1923","venue":null,"work_id":"8f92434a-92a9-49a1-bb06-b814a34947dc","year":1923},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:51.044209Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:2d9903ebc8440e41d0a24b0b05548c5a5f26888079e8c30cec5fdb1d81f0654d","observation_id":"2538ede7-4e67-4072-b59f-692098689aff","resolution":{"observed_at":"2026-08-07T12:04:04.576852Z","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":"2026-08-07T12:04:04.047646Z","title":"Subjective contours.Scientific American, 234(4):48–52, 1976","venue":null,"work_id":"bb1b9eda-fd45-4c37-b95a-514130b91688","year":1976},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:51.245137Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:8cc89a6228205411d2ec39899f8b4afa6408e6170a9d2995a0a85ef5c6ad78f9","observation_id":"0c88592d-d919-498d-9073-29384da002ec","resolution":{"observed_at":"2026-08-07T12:04:04.249562Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:03:51.402206Z","title":"Masked autoencoders are scalable vision learners","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:51.402206Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:dee46d03dc9ee6178ade3e9006134ef1cafb7a49258edfd6a04cbf8101d5e5e9","observation_id":"538fb759-d63c-44a6-8f6f-008e02e137bd","resolution":{"observed_at":"2026-08-07T12:03:51.402206Z","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":"2026-08-07T12:04:03.691859Z","title":"Univ of California Press, 1972","venue":null,"work_id":"4ee41dcf-774a-4be3-a3cb-097cbca8f5a9","year":1972},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:51.568451Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:00728fc187df5e99c6d0516f3e33e33370c92adf605e3a527c91322e74d3a30f","observation_id":"f9086773-e385-4dda-90ec-48d59edd84ab","resolution":{"observed_at":"2026-08-07T12:04:03.843622Z","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":"2026-08-07T12:04:03.349068Z","title":"Convexity and symmetry in figure-ground organization","venue":null,"work_id":"f109c18c-9bfe-4fc8-8476-7d07d878dc00","year":1976},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:51.790530Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:ccf1b27a046557029e9cbc52a945b73850a1532ec96aea053d613229715a575c","observation_id":"55c7dd91-28d9-4e83-bdfd-c960e6d0bd03","resolution":{"observed_at":"2026-08-07T12:04:03.484051Z","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":"2026-08-07T12:04:03.054789Z","title":"Inhibitory competition in figure-ground perception: Context and convexity.Journal of Vision, 8(16):4–4, 2008","venue":null,"work_id":"aed7893f-1122-4d0e-9488-c86162bf8555","year":2008},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:51.981800Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:2c5faa23c0351c3dcc26aa0c8bb2ea0db3da57df3d6175905da6e6c9e6528c25","observation_id":"99ac48d1-f1d2-4753-9879-6bff55147f4f","resolution":{"observed_at":"2026-08-07T12:04:03.155200Z","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":"2026-08-07T12:04:02.837881Z","title":"Who owns the contour of a visual hole?Perception, 35(7):883–894, 2006","venue":null,"work_id":"f4e8b858-9c6e-4af2-b580-024ace3907ca","year":2006},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:52.146730Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:8802f115ecd169ea0664d9a1460cc38a6e9f630a99ac2d6d07ce14a42fcedfe5","observation_id":"00aac2fa-01e9-4232-b8f1-a106f43da6cd","resolution":{"observed_at":"2026-08-07T12:04:02.921121Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:03:52.278191Z","title":"A convnet for the 2020s","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:52.278191Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:5eeb89ac21a61fc7a5a8c16438b4b258eec53ee262bbb3747e889f451da51064","observation_id":"077f4ac2-f175-4394-8496-171d996472ed","resolution":{"observed_at":"2026-08-07T12:03:52.278191Z","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":"2026-08-07T12:03:52.443953Z","title":"Convnext v2: Co-designing and scaling convnets with masked autoencoders","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:52.443953Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:25bd070283fb4591e7175cd40c7602b87ec3749cd200cffafbf8bd4cf368f243","observation_id":"c5a15848-4579-445e-94b4-12edab864444","resolution":{"observed_at":"2026-08-07T12:03:52.443953Z","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":"2026-08-07T12:04:02.563297Z","title":"Texture synthesis using convolutional neural networks.Advances in neural information processing systems, 28, 2015","venue":null,"work_id":"f2a2e976-e531-47f1-b5e4-9c33e955c768","year":2015},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:52.585383Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:9fef3b437b6216bcba8226e4647be53d9fefc1188d006bdb14e3e7f4ce80e309","observation_id":"ff8ee730-0f15-4d10-8d6b-c343a8efd1a8","resolution":{"observed_at":"2026-08-07T12:04:02.650173Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:03:52.728414Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:52.728414Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:53267eca72cf3e77215ee7ec73784d32a2230c5b0eb8c2e0e79f2ee201dfb7f5","observation_id":"0c345c29-98c5-46dc-8e4f-9bc8092df174","resolution":{"observed_at":"2026-08-07T12:03:52.728414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-06T05:58:29.182448Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-07T12:03:52.931824Z","title":"Dinov2: Learning robust visual features without supervision.arXiv preprint arXiv:2304.07193, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:52.931824Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:5f4a7e0dd7e203a369c2b06a02ce611a88e2e893c3cf9635e0d35a9adac9799e","observation_id":"4347e6e6-241b-4535-834a-bea59983e441","resolution":{"observed_at":"2026-08-07T12:03:52.931824Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.01936","last_updated":"2023-03-23T23:21:38Z","snapshot_observed_at":"2026-08-03T09:40:32.201832Z","submitted_at":"2022-10-04T22:13:25Z","title":"When and why vision-language models behave like bags-of-words, and what to do about it?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.01936","snapshot_observed_at":"2026-08-07T12:03:53.099753Z","title":"When and why vision-language models behave like bags-of-words, and what to do about it?arXiv preprint arXiv:2210.01936, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:53.099753Z"},"links":{"cited_paper":"/paper/2210.01936","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:23325bd9f53f0d1212d3e1fb8766b856d23ee19e01709f039080ec5e311a052e","observation_id":"21d5b03d-47ce-423f-916d-6834d1354101","resolution":{"observed_at":"2026-08-07T12:03:53.099753Z","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":"2026-08-07T12:04:02.368203Z","title":"Emergence of shape bias in convolutional neural networks through activation sparsity.Advances in Neural Information Processing Systems, 36:71755–71766, 2023","venue":null,"work_id":"ebb1eeed-7848-460b-877f-163cacf189dc","year":2023},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:53.244732Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:728bd8b3c514f65f7931ad8afa15c35e614f6c3b89ca27655489ed2385751879","observation_id":"39cfa9f6-2b86-4a72-9823-c7e3d4a0b01e","resolution":{"observed_at":"2026-08-07T12:04:02.424348Z","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":"2026-08-07T12:04:02.190659Z","title":"Large-scale two-photon imaging revealed super-sparse population codes in the v1 superficial layer of awake monkeys.Elife, 7:e33370, 2018","venue":null,"work_id":"53478d76-b62e-4ad5-984e-65d481ccb9d5","year":2018},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:53.405811Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:0166c5cf35bf10fd9b57a459fbb698e0d8869f66e5734345ea74be069d49ff71","observation_id":"6721d0cb-8bd3-4920-a15a-6f39d1d4bc8c","resolution":{"observed_at":"2026-08-07T12:04:02.261629Z","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":"2026-08-07T12:04:02.006140Z","title":"Surfgen: Adversarial 3d shape synthesis with explicit surface discriminators","venue":null,"work_id":"c5058d0a-c516-4e3a-ab7b-ef7841face9f","year":2021},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:53.555489Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:9d3500ac8d417768d9991b058f6ad9e43af075f368a43d86e9ba13689e9fbd6a","observation_id":"c43a076c-04dd-4e6c-b07a-cea0e2935cc7","resolution":{"observed_at":"2026-08-07T12:04:02.095770Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:03:53.710415Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:53.710415Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:d159ce1bfa774d9326e0e81a12280a1b0094f0c890fc6c7135fe2e9148b7624c","observation_id":"0d418c06-aa1d-4e59-99aa-43e89a578c19","resolution":{"observed_at":"2026-08-07T12:03:53.710415Z","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":"2026-08-07T12:03:53.893549Z","title":"Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:53.893549Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:62afa7a0321967f2dd586fc9b32261ea7608f68e8e5828c2510f53ee94785617","observation_id":"954c0556-a0ad-4b7c-a348-19db48bfc5fd","resolution":{"observed_at":"2026-08-07T12:03:53.893549Z","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":"2026-08-07T12:04:01.739974Z","title":"Robust category-level 6d pose estimation with coarse-to-fine rendering of neural features","venue":null,"work_id":"371e203e-53bf-413b-b63d-90cf4566bb85","year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:54.066000Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:9398fd0caf49f321f879ad89d42e660a509a3bdb2a13dd178c57513ee6096dd1","observation_id":"d6a294e7-8987-4789-b884-c00d77f0d087","resolution":{"observed_at":"2026-08-07T12:04:01.817405Z","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":"2026-08-07T12:04:01.481600Z","title":"Hallucination improves the performance of unsupervised visual representation learning","venue":null,"work_id":"16ad5e48-cd4e-49e2-a167-9349a9518c93","year":2023},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:54.271077Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:f30ba4655c5cf369106d58c5c59370caf8faa99230775f0d08c5b6fd69479acd","observation_id":"89217749-676f-47ba-903c-6014fedd3963","resolution":{"observed_at":"2026-08-07T12:04:01.596266Z","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":"2106.02869","last_updated":"2021-06-05T11:01:15Z","snapshot_observed_at":"2026-07-06T11:16:13.546683Z","submitted_at":"2021-06-05T11:01:15Z","title":"Integrating Auxiliary Information in Self-supervised Learning","version":1},"cited_work":{"arxiv_id":"2106.02869","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.02869","snapshot_observed_at":"2026-08-07T12:03:58.623755Z","title":"Integrating Auxiliary Information in Self-supervised Learning","venue":"cs.LG","work_id":"8a4ad963-bc10-4cb0-bd4a-5d7723e9fdcb","year":2021},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:54.487182Z"},"links":{"cited_paper":"/paper/2106.02869","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:c4be108ed63f34f618699dd7007a4585f46754624d901108f911afbb53aa10c3","observation_id":"d8212223-5aa7-493f-92b8-10697e9dc6eb","resolution":{"observed_at":"2026-08-07T12:03:58.729453Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-07T12:04:01.159045Z","title":"Hierarchical interdisciplinary topic detection model for research proposal classification.IEEE Transactions on Knowledge and Data Engineering, 35(9):9685–9699, 2023","venue":null,"work_id":"64e928bb-e450-4e8b-8a33-7405a07ab2cd","year":2023},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:54.636982Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:441bd7f1f3593071d720d611df029d2bf79c5511795836e83e1d1be766634126","observation_id":"a994a18d-b15d-432c-b29e-f58dd1b70b7d","resolution":{"observed_at":"2026-08-07T12:04:01.282256Z","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":"2026-08-07T12:04:00.869913Z","title":"A deep learning framework based on dynamic channel selection for early classification of left and right hand motor imagery tasks","venue":null,"work_id":"69da1e40-4fd1-4300-b607-4dd7af402628","year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:54.778344Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:a0838513a2a9876bd285fa123afe507f3ebb6918b6e3989cd385b12862e8b340","observation_id":"4a0adae1-5d88-4137-aa88-6083c33b40d0","resolution":{"observed_at":"2026-08-07T12:04:00.997181Z","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":"2202.06670","last_updated":"2022-02-18T11:49:01Z","snapshot_observed_at":"2026-08-06T13:02:03.064923Z","submitted_at":"2022-02-14T12:57:31Z","title":"Learning Weakly-Supervised Contrastive Representations","version":2},"cited_work":{"arxiv_id":"2202.06670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2202.06670","snapshot_observed_at":"2026-08-07T12:03:58.310600Z","title":"Learning Weakly-Supervised Contrastive Representations","venue":"cs.LG","work_id":"899b9e3d-c427-4a25-ab5b-7e3eef5f78a1","year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:54.924668Z"},"links":{"cited_paper":"/paper/2202.06670","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:d84281d360e2cd9346becbb58dd6ec04c5f4fe1d7d5e79d362a337fb762cfdd9","observation_id":"907eb8a4-d560-4b04-b76d-2837b61a57a5","resolution":{"observed_at":"2026-08-07T12:03:58.457846Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-07T12:04:00.588130Z","title":"Prototype memory and attention mechanisms for few shot image generation","venue":null,"work_id":"a6be9a05-6108-42ae-82b3-684b3717fc14","year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:55.099159Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:a5040152cdbe0d42422b140fcedfbdd2ae2c503b6588986d1c09ca7fca32736d","observation_id":"cc5254dc-2458-43de-b496-d4ac750c6846","resolution":{"observed_at":"2026-08-07T12:04:00.727497Z","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":"2202.05458","last_updated":"2022-03-15T06:08:14Z","snapshot_observed_at":"2026-08-02T14:57:50.894078Z","submitted_at":"2022-02-11T05:37:54Z","title":"Conditional Contrastive Learning with Kernel","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.05458","snapshot_observed_at":"2026-08-07T12:03:55.254411Z","title":"Conditional contrastive learning with kernel.arXiv preprint arXiv:2202.05458, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:55.254411Z"},"links":{"cited_paper":"/paper/2202.05458","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:44f6a1dd54ff54bb73c1eccae39405be43c8bd1340be3e6b7f2c1316b7a2b92a","observation_id":"711472b3-a901-4e48-bbd6-57da38cc8358","resolution":{"observed_at":"2026-08-07T12:03:55.254411Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.00639","last_updated":"2022-11-28T00:27:22Z","snapshot_observed_at":"2026-07-06T12:14:14.045497Z","submitted_at":"2021-12-01T16:42:38Z","title":"A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.00639","snapshot_observed_at":"2026-08-07T12:03:55.417106Z","title":"A systematic review of ro- bustness in deep learning for computer vision: Mind the gap?arXiv preprint arXiv:2112.00639, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:55.417106Z"},"links":{"cited_paper":"/paper/2112.00639","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:922983b0bc9aec3dc92279bc24d0cd566a73ce685c23a46ad2a77c5ef46c40db","observation_id":"b8e79915-b529-4624-bef2-114a8d6db8d1","resolution":{"observed_at":"2026-08-07T12:03:55.417106Z","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":"2026-08-07T12:04:00.354632Z","title":"Opening the black box: the promise and limitations of explainable machine learning in cardiology.Canadian Journal of Cardiology, 38(2):204–213, 2022","venue":null,"work_id":"c10b39cf-417e-465a-8017-d00e34853c88","year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:55.592462Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:442c4a21bbb0e9c00cd4680b0904b68f43010558ecf339475a2f89273c71b616","observation_id":"cba2da16-f7e0-4895-b97e-fcf7b311e157","resolution":{"observed_at":"2026-08-07T12:04:00.444146Z","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":"2026-08-07T12:04:00.106451Z","title":"Explaining explanations: An overview of interpretability of machine learning","venue":null,"work_id":"a8ebbd69-d6f6-47e4-a67a-5a18a50d8cb6","year":2018},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:55.763870Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:9bb6478e30dc938535b918ba0c9e4718c8c99b8da1fd73dc16c912b3160298fc","observation_id":"d0f334b9-4a85-4b74-95a8-ce8564650101","resolution":{"observed_at":"2026-08-07T12:04:00.250211Z","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":"2026-08-07T12:03:59.835265Z","title":"Assessing neural network representations during training using data diffusion spectra.ICML workshop on TAG-ML, 2023","venue":null,"work_id":"d684ecba-3d48-4b0c-ac16-d4110db60763","year":2023},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:55.903643Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:14901952bd5071eb208c7176960b30ad7524802a58cea3f5d3cbc0c1964c7637","observation_id":"f064788f-6f91-45a8-98f1-3ff994bff1c8","resolution":{"observed_at":"2026-08-07T12:03:59.949980Z","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":"2026-08-07T12:03:59.661888Z","title":"Neural networks trained on natural scenes exhibit gestalt closure.Computational Brain & Behavior, 4(3):251–263, 2021","venue":null,"work_id":"c4228143-21f8-4037-b3f3-3835462a2f4a","year":2021},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:56.048059Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:843ae676ab4d174f10f16c4cfc83c815a9480dc8f5cc96473de017afbf27644e","observation_id":"d2abc5e3-5234-4f77-b52a-da1add6e06a3","resolution":{"observed_at":"2026-08-07T12:03:59.732821Z","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":"2305.19889","last_updated":"2023-05-31T14:24:35Z","snapshot_observed_at":"2026-07-06T15:36:00.361429Z","submitted_at":"2023-05-31T14:24:35Z","title":"Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits","version":1},"cited_work":{"arxiv_id":"2305.19889","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.19889","snapshot_observed_at":"2026-08-07T12:03:58.028410Z","title":"Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits","venue":"cs.LG","work_id":"c8e33911-5f5c-4eb7-90b5-6fd7f03d2097","year":2023},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:56.233722Z"},"links":{"cited_paper":"/paper/2305.19889","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:376262022b4d47caba2de26604ac69daa3e47558cf88fea4392fc719cc9cf442","observation_id":"7edb45e1-d174-4e43-b91b-df03c0e165e1","resolution":{"observed_at":"2026-08-07T12:03:58.100010Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:03:56.444955Z","title":"Vision transformers with self-distilled registers.arXiv preprint arXiv:2505.21501, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:56.444955Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:a796db58250441cd608d731ae7c72b8b9e31a4392916e6f31a0b3abf0c3c478f","observation_id":"f51480cd-2698-466a-a80c-47e32d46c229","resolution":{"observed_at":"2026-08-07T12:03:56.444955Z","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":"2026-08-07T12:03:56.642954Z","title":"Visualizing and understanding convolutional networks","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:56.642954Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:4190435f93667de11e7482ec2e1dd0c311b727bfcffbedc9df5dd674cfdf3934","observation_id":"6abc1f00-e7f8-4b64-bc15-901db9e88320","resolution":{"observed_at":"2026-08-07T12:03:56.642954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12231","last_updated":"2022-11-09T23:15:15Z","snapshot_observed_at":"2026-08-02T03:51:09.933624Z","submitted_at":"2018-11-29T15:04:05Z","title":"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12231","snapshot_observed_at":"2026-08-07T12:03:56.785903Z","title":"Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness.arXiv preprint arXiv:1811.12231, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:56.785903Z"},"links":{"cited_paper":"/paper/1811.12231","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:3cf98692f10a984376ebad2a61eb920358297fb9553b43d9fb8b08af5751ed66","observation_id":"49cd2271-cb87-49a3-8835-00895539d129","resolution":{"observed_at":"2026-08-07T12:03:56.785903Z","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":"2026-08-07T12:03:59.449235Z","title":"Partial success in closing the gap between human and machine vision.Advances in Neural Information Processing Systems, 34:23885– 23899, 2021","venue":null,"work_id":"6d7a9502-c6c4-4ee6-963e-7acae6dfba30","year":2021},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:56.895420Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:4dad1b67997bcdd69102994fa6b5060a7d5c3957e98be9e6032f3a7b94e67de2","observation_id":"1cbebdbd-58c4-43b7-aa90-5d5c7186448c","resolution":{"observed_at":"2026-08-07T12:03:59.539768Z","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":"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":"2026-08-07T12:03:56.976332Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale.arXiv preprint arXiv:2010.11929, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:56.976332Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:fa471940b7bc3f214f5656b8f9605ecbd7528619276c451e9cd4f86ddca758a0","observation_id":"85837ed1-1b79-410d-a789-de192f04b193","resolution":{"observed_at":"2026-08-07T12:03:56.976332Z","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":"2026-08-07T12:03:57.098968Z","title":"Vision transformers are robust learners","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:57.098968Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:2a02e80841fb7c825064f5734fdf0596a68e545f67baa8c7aa9f8ef1c3dd9387","observation_id":"452b9f90-a144-4b1d-bcdc-7bddcf8ebb58","resolution":{"observed_at":"2026-08-07T12:03:57.098968Z","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":"2026-08-07T12:03:57.237121Z","title":"Imagenet: A large- scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:57.237121Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:eeea0ea7992f774d9d962ab71341df3d720135f52a554c0c29faf4f469ad903f","observation_id":"d1479110-2c12-49d6-b298-4dd54d0de2a2","resolution":{"observed_at":"2026-08-07T12:03:57.237121Z","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":"2026-08-07T12:03:59.201260Z","title":"Deit iii: Revenge of the vit","venue":null,"work_id":"66ecb2ee-eee3-4fae-98a2-4d5aa9a437da","year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:57.403064Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:0c4c6ee6a5c7b0cbf53b7906f0b48fb3347a1339b3fa2a207a8650144eb34421","observation_id":"ad57b297-cd41-40bd-bbd8-c5158bcf6532","resolution":{"observed_at":"2026-08-07T12:03:59.272200Z","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":"2026-08-07T12:03:58.989761Z","title":"given-up","venue":null,"work_id":"e3e55301-05dd-48fb-9314-bcf927b5bbc8","year":2022},"citing_paper":{"arxiv_id":"2506.00718","last_updated":"2025-05-31T21:35:54Z","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T12:03:57.574610Z"},"links":{"citing_paper":"/paper/2506.00718"},"observation_digest":"sha256:5954439ecf74ed61948ba9bd8620862ab23aae7680d415e7e3c9944a3cf5b890","observation_id":"1f165c69-9e5f-44c1-84f3-f21900e71df4","resolution":{"observed_at":"2026-08-07T12:03:59.079968Z","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":"2506.00718","last_updated":"2025-05-31T21:35:54Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T17:04:28.567918Z","submitted_at":"2025-05-31T21:35:54Z","title":"From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":3,"verified_fuzzy":24},"total_outbound_references":43},"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 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2506.00718."}