{"as_of":"2026-08-09T23:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2bde522422d27ee46adae98b9fbc479c9ab39bcf0e6ca9eceae2a8d0202d9aa7","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:03:25.019099Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2505.16675/citation-record","integrity":"/paper/2505.16675/integrity","json":"/paper/2505.16675/citation-record.json","paper":"/paper/2505.16675"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:03:26.984347Z","title":"Reformulation of OOD Generalization as Generalization on Task Distributions","venue":null,"work_id":"eb81ded1-ea1b-4a15-a63d-de5d78532d52","year":2017},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:25.019099Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:04d4bf2220c9639de69a51315808e7504a9a826ee16dde8e8e736f2535c0f1b6","observation_id":"818b06e1-791a-4bde-a0ab-5f3d8b0d3cca","resolution":{"observed_at":"2026-08-07T15:03:27.079772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:29.917804Z","title":"An empirical study of training self-supervised vision transformers","venue":null,"work_id":"0ccdf694-3274-4228-a4e1-596d655c9fb4","year":2009},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:21.940934Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:e88e5f1ebcd0c7f54b4c6659d5eba825edfafcdd862c90444089b26890545f4e","observation_id":"a18a587d-b6d3-44ea-b9b5-77410cc5fb85","resolution":{"observed_at":"2026-08-07T15:03:29.994118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:27.935042Z","title":"Even though we train a V AE, it does not affect other components of SimCLR’s training pipeline, including the training objective, network architecture, and optimization algorithm","venue":null,"work_id":"72f33434-bd74-44bc-ab1c-1fd68e142dd7","year":2020},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.426270Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:8df2da62d0cd6c82548476e540e5fed39c488c932e8676e45ee0d1952122c134","observation_id":"47e3bc42-6e4c-436c-9486-1d398b0b95dc","resolution":{"observed_at":"2026-08-07T15:03:28.046359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1705.06950","last_updated":"2017-05-19T12:07:01Z","snapshot_observed_at":"2026-08-08T17:46:50.107463Z","submitted_at":"2017-05-19T12:07:01Z","title":"The Kinetics Human Action Video Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.06950","snapshot_observed_at":"2026-08-07T15:03:22.269517Z","title":"Khemakhem, I., Kingma, D., Monti, R., and Hyvarinen, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.269517Z"},"links":{"cited_paper":"/paper/1705.06950","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:98a3894b2b38a186888eb66e210e5410a98a9a51992a6f1009d08bfad9225e18","observation_id":"279226c9-3728-450d-a7c8-0210cf6182d1","resolution":{"observed_at":"2026-08-07T15:03:22.269517Z","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":"2026-08-07T15:03:29.691800Z","title":null,"venue":null,"work_id":"4c59d7dc-9dd6-4ecd-be17-ae5cda7375cb","year":2017},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.461812Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:a7639075579791ab5ec567cbf90870cb401b39b928053e1cee0f207371999b0d","observation_id":"8b561ebe-6bb8-4adc-b2a3-f1952713905c","resolution":{"observed_at":"2026-08-07T15:03:29.813169Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:22.526830Z","title":"URL http: //dx.doi.org/10.1109/iccv.2017.591","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.526830Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:9c2c4e94029141900fdcdcbfa84d0a55f400cc1c09452a0c7cd2935f71ab08bc","observation_id":"631efc04-53dd-4e7e-8b25-9236d5059c46","resolution":{"observed_at":"2026-08-07T15:03:22.526830Z","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":"2026-08-07T15:03:29.481646Z","title":"A., and Doretto, G","venue":null,"work_id":"a0782796-fd61-4336-8672-3c5c83a12613","year":2017},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.590310Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:4bb0cc48c0c364e81d2eb6c2c98a13550f719778a8c410ce776cdb2b7eaca1f8","observation_id":"f1057133-6575-44f8-9496-d8eb4db01561","resolution":{"observed_at":"2026-08-07T15:03:29.576717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:22.652986Z","title":"2017.609","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.652986Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:980bba1c114abe1bb8c0bce0197cb405dba70a31e4d23ab4b2670d6efd4b1d46","observation_id":"99d6a298-13d2-4531-bb8b-94976baac580","resolution":{"observed_at":"2026-08-07T15:03:22.652986Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.08913","last_updated":"2023-07-19T14:18:00Z","snapshot_observed_at":"2026-07-06T15:55:06.149983Z","submitted_at":"2023-07-18T01:16:23Z","title":"Towards the Sparseness of Projection Head in Self-Supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.08913","snapshot_observed_at":"2026-08-07T15:03:22.855208Z","title":"Towards the sparseness of projection head in self- supervised learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.855208Z"},"links":{"cited_paper":"/paper/2307.08913","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:f7ce07f06dd613a176a12021dd4e55720d11d94dcdd0161a61c058aa64e7cf51","observation_id":"1b88c12a-1be5-4591-8b1c-c6f4db52f506","resolution":{"observed_at":"2026-08-07T15:03:22.855208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.05119","last_updated":"2022-11-03T19:38:38Z","snapshot_observed_at":"2026-08-07T02:52:04.663065Z","submitted_at":"2022-01-13T18:23:30Z","title":"Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.05119","snapshot_observed_at":"2026-08-07T15:03:23.089046Z","title":"Pushing the limits of self-supervised resnets: Can we outperform supervised learning without labels on imagenet? arXiv preprint arXiv:2201.05119,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.089046Z"},"links":{"cited_paper":"/paper/2201.05119","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:e35fe02a129fa9ca4d534ffdefecb93687a1b48d8efeaf23860515ab89416737","observation_id":"7e806cdd-2fbb-45e9-99cf-8cef7c826c01","resolution":{"observed_at":"2026-08-07T15:03:23.089046Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.05771","last_updated":"2024-05-29T09:30:00Z","snapshot_observed_at":"2026-08-02T01:30:36.692975Z","submitted_at":"2023-12-10T05:33:40Z","title":"Hacking Task Confounder in Meta-Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.05771","snapshot_observed_at":"2026-08-07T15:03:23.231500Z","title":"Hacking task confounder in meta-learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.231500Z"},"links":{"cited_paper":"/paper/2312.05771","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:f6882275cc0070b67d6732f6bd6daf561ecf22b795e4e4c105112ce07b1cfb00","observation_id":"9fbaad86-65f9-42e8-8bfb-023c0d54e6e8","resolution":{"observed_at":"2026-08-07T15:03:23.231500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.05263","last_updated":"2023-02-19T23:47:57Z","snapshot_observed_at":"2026-07-06T13:19:36.839011Z","submitted_at":"2022-06-10T17:59:11Z","title":"Causal Balancing for Domain Generalization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.05263","snapshot_observed_at":"2026-08-07T15:03:23.365508Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.365508Z"},"links":{"cited_paper":"/paper/2206.05263","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:291f9eb38267f1ccdb87e111880178d120aaff085afb0715c1bf9a3dcea95ffa","observation_id":"be4d2515-c5dd-4c33-829a-174c94274764","resolution":{"observed_at":"2026-08-07T15:03:23.365508Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14789","last_updated":"2024-02-22T18:46:22Z","snapshot_observed_at":"2026-07-06T17:34:11.950339Z","submitted_at":"2024-02-22T18:46:22Z","title":"Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning","version":1},"cited_work":{"arxiv_id":"2402.14789","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.14789","snapshot_observed_at":"2026-08-07T15:03:26.223146Z","title":"Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning","venue":"cs.LG","work_id":"1a77bce4-9e55-4a84-a08a-b3d54d8490bc","year":2024},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.433418Z"},"links":{"cited_paper":"/paper/2402.14789","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:a0a909fc618e072ca5b8d147ba1a89ecb845782c677c7b5da4ac2b54eacad6f8","observation_id":"a4b98edb-903c-4b72-bdcc-3384601fab6d","resolution":{"observed_at":"2026-08-07T15:03:26.373498Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.03230","last_updated":"2021-06-14T14:09:43Z","snapshot_observed_at":"2026-08-06T19:59:22.675422Z","submitted_at":"2021-03-04T18:55:09Z","title":"Barlow Twins: Self-Supervised Learning via Redundancy Reduction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.03230","snapshot_observed_at":"2026-08-07T15:03:23.508145Z","title":"Barlow twins: Self-supervised learning via redundancy reduction","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.508145Z"},"links":{"cited_paper":"/paper/2103.03230","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:81f59d2d42a12dcc66dedc1ec639845f553ac231962db8670a5b1a36b1eba1c6","observation_id":"84059528-88cc-4e26-aaa1-cad02964f98b","resolution":{"observed_at":"2026-08-07T15:03:23.508145Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.16361","last_updated":"2023-11-29T23:19:30Z","snapshot_observed_at":"2026-07-06T16:53:31.770042Z","submitted_at":"2023-11-27T22:52:45Z","title":"Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling","version":2},"cited_work":{"arxiv_id":"2311.16361","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.16361","snapshot_observed_at":"2026-08-07T15:03:25.930148Z","title":"Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling","venue":"cs.LG","work_id":"276ba2c9-9eb7-4506-90c2-bffad2c7df89","year":2023},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.621117Z"},"links":{"cited_paper":"/paper/2311.16361","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:4671ddf68be8431a47b9e2d97512dcac567c97f71e4c2ad80f705e9f2e99cecf","observation_id":"b62ea652-71ef-45b7-b73c-17124cf4c648","resolution":{"observed_at":"2026-08-07T15:03:26.102812Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.01654","last_updated":"2021-06-03T07:50:50Z","snapshot_observed_at":"2026-07-06T11:15:30.045776Z","submitted_at":"2021-06-03T07:50:50Z","title":"Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statement","version":1},"cited_work":{"arxiv_id":"2106.01654","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.01654","snapshot_observed_at":"2026-08-07T15:03:25.589616Z","title":"Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statement","venue":"cs.CL","work_id":"47606892-a1b0-43f0-9ca8-5b103fabcb65","year":2021},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.758159Z"},"links":{"cited_paper":"/paper/2106.01654","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:a5a6218bd29844b3b68604fcf57d231cd07dbd9b9e3aa38e7a5176b49497216e","observation_id":"1ac2a90a-f615-43cb-b6fb-3e6722030d3d","resolution":{"observed_at":"2026-08-07T15:03:25.746203Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:29.300540Z","title":"Since this holds for all x ∈ R and h ̸= 0, we conclude that the distribution is not strongly exponential","venue":null,"work_id":"3e61e8fb-b309-4710-9a86-860e23698860","year":2020},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.852684Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:3a75aad5ecdd49f1312df71c0623d353e49b90df8a76b9dc02268bc8b9ddf68b","observation_id":"c6028c04-1fbf-469e-b37b-629e02d95cbd","resolution":{"observed_at":"2026-08-07T15:03:29.396719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:28.746322Z","title":null,"venue":null,"work_id":"299ed6f5-5d61-4dc5-b7b8-5a063c571e1a","year":2019},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.028999Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:34382214e5c284801ed787055040e2d967c6d71e79e529df73d21b5baa78b6a8","observation_id":"cbf83745-3af4-4ac8-87f2-68d330c50169","resolution":{"observed_at":"2026-08-07T15:03:28.825641Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:28.378794Z","title":"The ViT backbone is adapted for use with FPN (Lin et al., 2017)","venue":null,"work_id":"749fd584-f52b-4599-8c1d-67795e9bcaab","year":2014},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.226117Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:4528d3f8893027fbfa57f51d5dcf0a4acc4f39569c73e55d317bb17bb600f725","observation_id":"0dc17672-c1c3-4a44-95a3-2a1c5ab4d9b6","resolution":{"observed_at":"2026-08-07T15:03:28.458380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:28.158346Z","title":"Following the standard setting, we evaluate on top 60 common classes with mean Average Precision (mAP) as the metric","venue":null,"work_id":"1605c772-2ba4-446d-956d-2039060f31d0","year":2012},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.313890Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:9977fd3378311d3ad20f0d12b0ce5535116a27882350176fb894f2e31f10a676","observation_id":"6d213c5e-0d66-49e2-bbcb-f3069eb5775a","resolution":{"observed_at":"2026-08-07T15:03:28.255004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:27.742860Z","title":"During training, waterbirds (landbirds) are predominantly paired with water (land) backgrounds","venue":null,"work_id":"4bbddcae-535e-4ff0-806c-3bcb2d1d2ee2","year":2023},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.552233Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:ef44c6c190578b0356993e1f7a2716f8d904dc067ef59a156785c56d818758c1","observation_id":"b147348b-6e14-4d5a-9b41-0f18d16d062a","resolution":{"observed_at":"2026-08-07T15:03:27.832246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:27.507154Z","title":"Finally, for the Colored-MNIST dataset, we follow the experimental settings mentioned in (Huang et al., 2024)","venue":null,"work_id":"16974f77-c0b1-420c-89a4-3938edc52736","year":2024},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.697357Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:ca5aa81192709d3dff3b5c551e7563754ec6fa1da7e1aaf92e7097c082d9827f","observation_id":"daf6e109-e5f4-42c7-98f7-0e6faa351be7","resolution":{"observed_at":"2026-08-07T15:03:27.604025Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:29.097458Z","title":"For this experiment, we utilize several benchmark datasets to evaluate the model’s performance","venue":null,"work_id":"348636a8-efec-42bc-a2cc-4dc8fb5bb62e","year":2021},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":128,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.911644Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:b66dd0a719a86144e9db9e14ea71e232b2e8991cede32747a63428d5f753958e","observation_id":"a75b1fdd-2381-4e7e-9971-aee834fa0f53","resolution":{"observed_at":"2026-08-07T15:03:29.188891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.21236/ada114514","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:03:25.250677Z","title":"URL http://dx.doi.org/10.21236/ada114514","venue":null,"work_id":"979dcd45-af0a-4cd9-9d51-7d56c69bf1c7","year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":1981,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.758188Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:923deb884ced1ef4eab8ecdb4380d4f391a91d71d8ab0d24086def03b8f66914","observation_id":"aaddb983-cac0-48cb-a486-44bbb654a0b8","resolution":{"observed_at":"2026-08-07T15:03:25.431422Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:21.996249Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale.arXiv preprint arXiv:2010.11929,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:21.996249Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:ccfdc93640261b2638777c73b1ea83e8cb9fed9339d0298ecd4f65301b0b4f5d","observation_id":"4b729abc-4b70-49ea-81ff-5c3fabff0ae7","resolution":{"observed_at":"2026-08-07T15:03:21.996249Z","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":"2026-08-07T15:03:28.909833Z","title":"We also conduct experiments on a smaller version of Pascal VOC, the VOC 07 set (5K images), with a reduced number of iterations","venue":null,"work_id":"223c2481-14fd-445a-8263-e2dad3fc2241","year":2007},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:23.975504Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:8a4468cda7dae56b2e3b64baecfd702d442bd3831b13da78812c314d1e2bd607","observation_id":"88b1b4b2-a9e0-44f7-840d-8b9f24c7aacc","resolution":{"observed_at":"2026-08-07T15:03:29.016250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:28.536703Z","title":"The following section provides a comparison of the models","venue":null,"work_id":"3dc66d84-d8b5-4125-be5c-6ffde86174ad","year":2021},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.109025Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:8a6bcb6f979b1fda850359f3c48988e32e4867ed1163827e0e62fa7182bc4a4c","observation_id":"3d5b8c4b-ca61-4953-84ab-66661c06e367","resolution":{"observed_at":"2026-08-07T15:03:28.636290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:21.712912Z","title":"URL http://dx","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:21.712912Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:2c1bb85635b2c3841b70336a5980c68ab7a0ba89203eb83ca4006d8eff413236","observation_id":"e28d6268-5848-4e2c-8332-0cadff9eb0d7","resolution":{"observed_at":"2026-08-07T15:03:21.712912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.07733","last_updated":"2020-09-10T09:46:02Z","snapshot_observed_at":"2026-07-06T09:28:50.024490Z","submitted_at":"2020-06-13T22:35:21Z","title":"Bootstrap your own latent: A new approach to self-supervised Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.07733","snapshot_observed_at":"2026-08-07T15:03:22.139267Z","title":"Bootstrap your own latent-a new approach to self-supervised learning","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.139267Z"},"links":{"cited_paper":"/paper/2006.07733","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:d6eb8b47054ddd7c2fb486a64aae80a560cf5fc2d5b0bb1dbc2161a6b55b82fb","observation_id":"b420eecb-c581-4a41-9c26-6ec3bed7df84","resolution":{"observed_at":"2026-08-07T15:03:22.139267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-07T15:03:22.373962Z","title":"and Welling, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.373962Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:3e2dbf12cbd578b898b5d6018428f53c0b859e389a27801b149a5180f3ca752b","observation_id":"11f90b8b-9175-40b1-a106-d9aea043d833","resolution":{"observed_at":"2026-08-07T15:03:22.373962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.09882","last_updated":"2021-01-08T17:01:05Z","snapshot_observed_at":"2026-08-05T06:18:23.439795Z","submitted_at":"2020-06-17T14:00:42Z","title":"Unsupervised Learning of Visual Features by Contrasting Cluster Assignments","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.09882","snapshot_observed_at":"2026-08-07T15:03:21.798280Z","title":"Caron, M., Touvron, H., Misra, I., Jegou, H., Mairal, J., Bojanowski, P., and Joulin, A","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:21.798280Z"},"links":{"cited_paper":"/paper/2006.09882","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:35660c7f13dc1d08ddec6891ac144b949f42fdfc4fd8ccbafb527972ec6a49fb","observation_id":"9d1112ad-448c-4f5d-9cb6-a751de94a00c","resolution":{"observed_at":"2026-08-07T15:03:21.798280Z","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":"2026-08-07T15:03:21.875669Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:21.875669Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:71aedb9222e8e2de10f9811f5bda6a146ffddef46cbde80b395fd938fd1c73ab","observation_id":"4fcde2c8-2d1e-4f8a-9753-95aeac284d6b","resolution":{"observed_at":"2026-08-07T15:03:21.875669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1805.08136","last_updated":"2019-07-24T14:43:31Z","snapshot_observed_at":"2026-08-08T20:06:30.306939Z","submitted_at":"2018-05-21T15:44:51Z","title":"Meta-learning with differentiable closed-form solvers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.08136","snapshot_observed_at":"2026-08-07T15:03:21.626432Z","title":"F., Torr, P","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:21.626432Z"},"links":{"cited_paper":"/paper/1805.08136","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:d2df2f57798b024fe05b37acbd94f4ce712a7e7491e18c45ea49336407c7293e","observation_id":"98dd5ba9-6486-4771-a217-380bed063261","resolution":{"observed_at":"2026-08-07T15:03:21.626432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.13541","last_updated":"2025-08-04T06:37:59Z","snapshot_observed_at":"2026-08-03T16:04:05.101262Z","submitted_at":"2024-07-18T14:18:03Z","title":"On the Discriminability of Self-Supervised Representation Learning","version":2},"cited_work":{"arxiv_id":"2407.13541","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.13541","snapshot_observed_at":"2026-08-07T15:03:26.627458Z","title":"On the Discriminability of Self-Supervised Representation Learning","venue":"cs.CV","work_id":"4e0ef209-2484-41e3-bf7a-3dd80390a4a6","year":2024},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:22.923711Z"},"links":{"cited_paper":"/paper/2407.13541","citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:65fa42ffe32018713d772033c3b0b643a132e22173f16f8234b4e8c5bb40a1a9","observation_id":"9196c204-c906-4156-b39c-2acda55f30af","resolution":{"observed_at":"2026-08-07T15:03:26.703868Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T15:03:27.169739Z","title":null,"venue":null,"work_id":"040f380b-2692-43b5-84a6-84bd1e567ddf","year":2023},"citing_paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T15:03:24.865304Z"},"links":{"citing_paper":"/paper/2505.16675"},"observation_digest":"sha256:a750753c7cb59e94407ee295571eee43d3a853cbe8cce1a1f8292b9748a1c401","observation_id":"250bcebb-d883-433d-a753-ed3cb04ffbb5","resolution":{"observed_at":"2026-08-07T15:03:27.326523Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.16675","last_updated":"2025-05-22T13:40:00Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T14:55:01.207058Z","submitted_at":"2025-05-22T13:40:00Z","title":"On the Out-of-Distribution Generalization of Self-Supervised Learning"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":17,"verified_exact":4,"verified_fuzzy":12},"total_outbound_references":35},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2505.16675."}