{"as_of":"2026-08-13T08:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:61fd0c819097b5f99fd1bb3f49936e3b54ff08115ebbb5b2609f211b0a9840b2","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:49:25.803786Z","state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2411.15931/citation-record","integrity":"/paper/2411.15931/integrity","json":"/paper/2411.15931/citation-record.json","paper":"/paper/2411.15931"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2105.04906","last_updated":"2022-01-28T12:23:37Z","snapshot_observed_at":"2026-08-12T14:02:29.797842Z","submitted_at":"2021-05-11T09:53:21Z","title":"VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.04906","snapshot_observed_at":"2026-08-12T13:49:25.760735Z","title":"VI- CReg: Variance-invariance-covariance regulariza- tion for self-supervised learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.760735Z"},"links":{"cited_paper":"/paper/2105.04906","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:4a289a90e9e5b0462ab418f300248a99a8845c6b8f6dafcd52efb132bdd03865","observation_id":"132023f8-4370-4e9f-9bff-2a801212f943","resolution":{"observed_at":"2026-08-12T13:49:25.760735Z","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":"2026-08-12T13:49:25.888879Z","title":null,"venue":null,"work_id":"5a775633-0a45-4471-b947-e10f6c88ed63","year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.803786Z"},"links":{"citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:84f60909926833f9c5b90517e96e5dda3ebf87ae33fe6b4d8725ce5515e597e2","observation_id":"7b27a28c-0f6c-4026-8603-9636d5c87a29","resolution":{"observed_at":"2026-08-12T13:49:25.892745Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:49:25.917008Z","title":null,"venue":null,"work_id":"840cd53a-32ad-46e4-93f3-43859a3e8b41","year":2021},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.794486Z"},"links":{"citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:b688e93147f304c167098c702fd7d8ab71ba20f43e10a1a487227864bfe54a10","observation_id":"f59b4268-68ce-4712-80c0-04f0fca3cec1","resolution":{"observed_at":"2026-08-12T13:49:25.920313Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.00789","last_updated":"2023-03-08T13:34:28Z","snapshot_observed_at":"2026-07-06T13:37:22.319940Z","submitted_at":"2022-07-28T08:06:24Z","title":"Self-supervised learning with rotation-invariant kernels","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.00789","snapshot_observed_at":"2026-08-12T13:49:25.785312Z","title":"Self-supervised learn- ing with rotation-invariant kernels.arXiv preprint arXiv:2208.00789,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.785312Z"},"links":{"cited_paper":"/paper/2208.00789","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:d734f94984f0800f0e2859e8fcb3aa425f8801e62bb4a66bfda7527c2f34267c","observation_id":"acb29ea9-6d87-41f8-9440-59712b64dd90","resolution":{"observed_at":"2026-08-12T13:49:25.785312Z","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":"2026-08-12T13:49:25.906715Z","title":"For SimSiam, the semi-supervised experiments were not conducted in the original paper, and therefore we skip this in our experiments","venue":null,"work_id":"3bf49ce4-fb49-4c35-a46c-65e8b67fae86","year":2020},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.797549Z"},"links":{"citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:00151e0745f5e4fd4ca54f0bb6fb45047949a7274485f1d8d8996be1fbdcd3b3","observation_id":"63d95287-08ad-4e73-a24e-2fdc364a1ee9","resolution":{"observed_at":"2026-08-12T13:49:25.910901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:49:25.898150Z","title":null,"venue":null,"work_id":"3f09c5f7-79b0-4394-ba40-c385fb4e177b","year":2007},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.800508Z"},"links":{"citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:39b503170131a3cab9ddb61d36173f86e370a966eb2dc22b69c0995c8d73511d","observation_id":"c4e21e06-317a-4f46-96df-f0e75d8b5f4b","resolution":{"observed_at":"2026-08-12T13:49:25.900798Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:49:25.926572Z","title":null,"venue":null,"work_id":"17d8a8c5-b745-4357-85f3-30dd4eaa785a","year":2023},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.791284Z"},"links":{"citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:9fb61a4298a4c8c35274a99ab080e2ed6fd38c6511757a715efc0867fe292510","observation_id":"da8c0acf-74cf-40a6-83c5-29f21457168e","resolution":{"observed_at":"2026-08-12T13:49:25.929765Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14905","last_updated":"2024-02-14T15:31:56Z","snapshot_observed_at":"2026-08-10T17:46:09.966900Z","submitted_at":"2022-09-29T16:13:10Z","title":"Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14905","snapshot_observed_at":"2026-08-12T13:49:25.767166Z","title":"Variance covariance regularization enforces pairwise independence in self-supervised representa- tions","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":1947,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.767166Z"},"links":{"cited_paper":"/paper/2209.14905","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:8b9fee1186d097bb6f8dd28f647b1156538343a3ee576e8c4f2a6a76aba2893e","observation_id":"0d842627-b9d5-4095-97a8-2df1778f5b40","resolution":{"observed_at":"2026-08-12T13:49:25.767166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.03198","last_updated":"2019-08-30T12:54:38Z","snapshot_observed_at":"2026-08-12T01:10:15.882398Z","submitted_at":"2018-06-08T14:46:22Z","title":"Spreading vectors for similarity search","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.03198","snapshot_observed_at":"2026-08-12T13:49:25.772954Z","title":"Spreading vectors for similarity search.arXiv preprint arXiv:1806.03198,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.772954Z"},"links":{"cited_paper":"/paper/1806.03198","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:0d90dab1db57788f98a0dab56f99bf7eb15cb936cedf8fcb168c38781ca597ce","observation_id":"99831a16-b25d-42b8-9e72-d9da02418bc2","resolution":{"observed_at":"2026-08-12T13:49:25.772954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.06670","last_updated":"2019-02-22T18:38:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2018-08-20T19:52:51Z","title":"Learning deep representations by mutual information estimation and maximization","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.06670","snapshot_observed_at":"2026-08-12T13:49:25.764242Z","title":"Learning deep repre- sentations by mutual information estimation and maximization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.764242Z"},"links":{"cited_paper":"/paper/1808.06670","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:0b4fa5168e46378403ba218e9038835d51e24800f33942aa10237d86c1826149","observation_id":"8e86073d-adf6-4d3b-b5dc-8dcc5390b890","resolution":{"observed_at":"2026-08-12T13:49:25.764242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.09366","last_updated":"2024-06-13T17:49:56Z","snapshot_observed_at":"2026-08-12T23:43:20.252113Z","submitted_at":"2024-06-13T17:49:56Z","title":"Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.09366","snapshot_observed_at":"2026-08-12T13:49:25.775674Z","title":"Towards an improved understanding and utilization of maximum manifold capacity repre- sentations","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.775674Z"},"links":{"cited_paper":"/paper/2406.09366","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:78b815603df7898f9bdae3f081fa46d42b349c1637b5f18fb8d32c4a60c897f4","observation_id":"2fc6974b-60e1-4f21-a90e-c15236a99f44","resolution":{"observed_at":"2026-08-12T13:49:25.775674Z","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":"2026-08-12T13:49:25.936175Z","title":"For continued pretraining, our criterion is applied to the projector embeddingsZ before the cluster assignment layer and before normalization after mapping through the CDF function","venue":null,"work_id":"b3682663-3eda-4b99-ae6f-fffab7a32e67","year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.788381Z"},"links":{"citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:805274330e90271ac580e21d3c8f5abf98f13ae627ef4801282d7e16ab6887ea","observation_id":"2e1a7a9b-c2a5-431f-bef7-8e8cca6ae7a0","resolution":{"observed_at":"2026-08-12T13:49:25.939811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:49:25.946001Z","title":"A new class of entropy estimators for multi-dimensional densities","venue":null,"work_id":"c585ca45-bc5f-4483-b07e-5b1c45e26f19","year":2003},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.770258Z"},"links":{"citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:98b7e270b9817f887cef4b46184e417c4456dc0c07d15680a8b5bf284ee1f2e9","observation_id":"5ff25881-dcfd-4499-8b45-cbd8aeadd02d","resolution":{"observed_at":"2026-08-12T13:49:25.949263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.03977","last_updated":"2023-04-08T10:09:30Z","snapshot_observed_at":"2026-08-11T18:26:44.748281Z","submitted_at":"2023-04-08T10:09:30Z","title":"EMP-SSL: Towards Self-Supervised Learning in One Training Epoch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.03977","snapshot_observed_at":"2026-08-12T13:49:25.782273Z","title":"Emp-ssl: Towards self-supervised learning in one training epoch","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.782273Z"},"links":{"cited_paper":"/paper/2304.03977","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:9ab0b20514a5a8bd8be53ffb36514743dbeb6a61bf100c0d0378719499d554e7","observation_id":"b68e99e9-f2cb-4863-87b4-e8f260aae541","resolution":{"observed_at":"2026-08-12T13:49:25.782273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.00633","last_updated":"2024-05-02T03:58:14Z","snapshot_observed_at":"2026-08-11T16:51:36.301938Z","submitted_at":"2023-03-01T16:36:25Z","title":"An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.00633","snapshot_observed_at":"2026-08-12T13:49:25.778923Z","title":"An information-theoretic perspective on variance- invariance-covariance regularization.arXiv preprint arXiv:2303.00633,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-12T13:49:25.778923Z"},"links":{"cited_paper":"/paper/2303.00633","citing_paper":"/paper/2411.15931"},"observation_digest":"sha256:603763679812a36a1cabc1e01c9dadefcc878b6134ec06de4cf4e934e51d8be6","observation_id":"9718f461-1107-43fc-a41a-6887a0ce423a","resolution":{"observed_at":"2026-08-12T13:49:25.778923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.15931","last_updated":"2025-03-13T20:12:09Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T13:41:24.496128Z","submitted_at":"2024-11-24T17:38:23Z","title":"Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":0,"verified_fuzzy":3},"total_outbound_references":15},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2411.15931."}