{"as_of":"2026-08-18T10:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7fb12fecc1e3cb6ed65455592c7814344be20b2f8edbccf7ed16e93993596c44","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T15:01:41.380506Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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/2411.14765/citation-record","integrity":"/paper/2411.14765/integrity","json":"/paper/2411.14765/citation-record.json","paper":"/paper/2411.14765"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T15:01:42.241627Z","title":"In particu- lar, we avoid specifying any particular kernel and allow our attention mechanism to learn the bias-causing interactions","venue":null,"work_id":"bf356f14-1e07-4094-a619-1be9ac7de181","year":2022},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.354656Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:2f324c71d1b1c93f1bc92a7b34cd83019724c8c7cfb89b2dd70a5393795415d6","observation_id":"9f32bd27-a2e7-4836-a552-39be5c64fbfb","resolution":{"observed_at":"2026-08-12T15:01:42.247886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.174654Z","title":"log ef (x,ypos) ef (x,ypos) + Pb i=1 ef (x,yneg,i) # , (21) and FAREContrast is given as: sup f E{(xi,yi,zi)}b i=1∼P ⊗b XY Z","venue":null,"work_id":"7eb7b2df-4e9a-4e81-a7b8-d257be981c51","year":2021},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.368880Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:3ecdf77c04f78db7c82ff9d73757d6fcf645d736781d3e2a226c921dd8668d77","observation_id":"c6c68782-0fe8-44a6-a60c-d3dc075d932d","resolution":{"observed_at":"2026-08-12T15:01:42.187523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.473154Z","title":null,"venue":null,"work_id":"2619981c-c49e-4611-890b-e292e4996e10","year":2017},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.282544Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:8a3e9441297a6ddb1436719b409beb70325672014a9a3d88d15caaf3092d3b0f","observation_id":"d0ecc7a2-97e6-4da5-a617-504783f19e06","resolution":{"observed_at":"2026-08-12T15:01:42.479456Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.676865Z","title":null,"venue":null,"work_id":"b6af03eb-7700-4132-b595-08f953b27d42","year":2019},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.033202Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:e8294c22576c65d9f977c5489ec364e1b6850e7149eaef892a1cc793d7637e89","observation_id":"281bbc3a-127f-4072-ba97-81cf66ce3740","resolution":{"observed_at":"2026-08-12T15:01:42.687560Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:41.040115Z","title":"doi: 10.18653/v1/W19-4828","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.040115Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:6567e11efd49341a22f3cedb0fb39cf626097435543ef4b79ffe0524b11a0a69","observation_id":"94c931aa-dfc3-4c92-bb6d-19fa75eae003","resolution":{"observed_at":"2026-08-12T15:01:41.040115Z","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":"2026-08-12T15:01:42.655092Z","title":"Fairness metrics: A comparative analysis","venue":null,"work_id":"b3aacc17-0e9d-4684-b907-4d943d88dd8a","year":2020},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.051157Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:d30a9763986f2e66c074f010116e3d03d85673e7064199b25de98aec267e0131","observation_id":"ca83523d-4787-4385-ba5f-55aee424ac10","resolution":{"observed_at":"2026-08-12T15:01:42.660462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.627024Z","title":"Designing and interpreting probes with control tasks","venue":null,"work_id":"5414d253-122d-46fc-8e84-6f355140ab38","year":2019},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.061614Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:cb55894196c1c79362c1be28d31b39e6086b704ceac4e448f414dd3f7dfb7757","observation_id":"fd34df9e-d7bc-40f4-8f7a-345940913d1a","resolution":{"observed_at":"2026-08-12T15:01:42.636126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1808.06670","last_updated":"2019-02-22T18:38:15Z","snapshot_observed_at":"2026-08-14T18:39:08.324821Z","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":"2026-08-12T15:01:41.069132Z","title":"doi: 10.18653/v1/D19-1275","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.069132Z"},"links":{"cited_paper":"/paper/1808.06670","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:c04fe6f66ac15cb97246b5f790a8c982f225ecc540126eb1e90617d51896e5b2","observation_id":"54e01caf-3b95-467d-8db1-a45312c5ae5d","resolution":{"observed_at":"2026-08-12T15:01:41.069132Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.04451","last_updated":"2020-02-18T16:01:18Z","snapshot_observed_at":"2026-07-06T08:50:12.690900Z","submitted_at":"2020-01-13T18:38:28Z","title":"Reformer: The Efficient Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.04451","snapshot_observed_at":"2026-08-12T15:01:41.077306Z","title":"Reformer: The efficient transformer","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.077306Z"},"links":{"cited_paper":"/paper/2001.04451","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:a43b06357010fa5926c42f88a8da83befa8649ec09271bbf9538460853f0c239","observation_id":"bbe24fb0-c2ba-4d04-af8e-92768968fd91","resolution":{"observed_at":"2026-08-12T15:01:41.077306Z","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":"2026-08-12T15:01:42.592445Z","title":"Large-scale celebfaces attributes (celeba) dataset","venue":null,"work_id":"b7c67e24-d6d6-478c-b5a8-02d9dfbdd00e","year":2018},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.092427Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:e06d7abfae3fb97a0cef5d86efa8d444282fd080b877d8b3e90157569dd13a7f","observation_id":"76a570ce-b36e-471a-97da-0680be8d2472","resolution":{"observed_at":"2026-08-12T15:01:42.607518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.567355Z","title":"Duet: A tuning-free device-cloud collaborative parameters generation frame- work for efficient device model generalization","venue":null,"work_id":"f13eb5ee-8660-4739-9f3e-fda123b3593a","year":2023},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.108395Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:873ae15171666e4af1f6b28afa6187f438b407731c8252286c9e109f2d32473b","observation_id":"44e711f8-7943-4295-a96c-43f5fd0d4e3a","resolution":{"observed_at":"2026-08-12T15:01:42.576070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-08-14T18:53:38.574749Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-08-12T15:01:41.116027Z","title":"Representation learning with contrastive predictive coding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.116027Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:f402ff56135fc94e2e451c875a5cb97470a439c8efafe16d880fa129ad6fc96f","observation_id":"e43f135f-7676-4e8e-b83d-b3df90adf186","resolution":{"observed_at":"2026-08-12T15:01:41.116027Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.04592","last_updated":"2021-01-24T22:19:30Z","snapshot_observed_at":"2026-08-16T19:14:40.873636Z","submitted_at":"2020-10-09T14:18:53Z","title":"Contrastive Learning with Hard Negative Samples","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.04592","snapshot_observed_at":"2026-08-12T15:01:41.143868Z","title":"Contrastive learning with hard negative sam- ples","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.143868Z"},"links":{"cited_paper":"/paper/2010.04592","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:56769b0864d7500b8704f5072f11d35c27553cb51aa8f18bcdb60f13e0b6b06b","observation_id":"a8aaca57-ed3c-4f6e-858d-abeb877e65de","resolution":{"observed_at":"2026-08-12T15:01:41.143868Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.10645","last_updated":"2021-09-22T10:47:51Z","snapshot_observed_at":"2026-08-16T17:54:54.980318Z","submitted_at":"2021-09-22T10:47:51Z","title":"Contrastive Learning for Fair Representations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.10645","snapshot_observed_at":"2026-08-12T15:01:41.183024Z","title":"Contrastive learning for fair representa- tions","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.183024Z"},"links":{"cited_paper":"/paper/2109.10645","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:efce5f8aa926063c819537379cdabd632a60503ed910aed1d9b089f21a069641","observation_id":"1edf600b-2105-4520-b2b5-5e2c7323f50a","resolution":{"observed_at":"2026-08-12T15:01:41.183024Z","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":"2026-08-12T15:01:41.201916Z","title":"doi: 10.18653/v1/P19-1452","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.201916Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:df77a090e2429c9fe58df650e8a9a465578637f796ccdfaa74d9a0ead8c26739","observation_id":"afc92f09-99a5-413c-848b-9c40a94731e9","resolution":{"observed_at":"2026-08-12T15:01:41.201916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.11775","last_updated":"2019-11-11T21:51:11Z","snapshot_observed_at":"2026-08-17T15:16:33.375231Z","submitted_at":"2019-08-30T15:05:02Z","title":"Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.11775","snapshot_observed_at":"2026-08-12T15:01:41.216289Z","title":"Trans- former dissection: a unified understanding of transformer’s attention via the lens of kernel","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.216289Z"},"links":{"cited_paper":"/paper/1908.11775","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:531e9c52d9a3ff4e0ef4af7c327996af6b55b07089457ea619d8d5314cb8d2bd","observation_id":"f3859fdc-7c88-4593-ba55-b6387b086cfd","resolution":{"observed_at":"2026-08-12T15:01:41.216289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.11275","last_updated":"2021-04-12T19:14:34Z","snapshot_observed_at":"2026-08-16T18:37:32.609965Z","submitted_at":"2021-03-21T01:04:24Z","title":"Self-supervised Representation Learning with Relative Predictive Coding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.11275","snapshot_observed_at":"2026-08-12T15:01:41.223271Z","title":"Self-supervised representation learning with relative predictive coding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.223271Z"},"links":{"cited_paper":"/paper/2103.11275","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:e118442edc0b2b97d2b3dc91d6f9fbf195aaa04dd2c4f210450c49c35f88e656","observation_id":"69dbcb13-3bf0-453b-8bed-cb59c8d4b2ab","resolution":{"observed_at":"2026-08-12T15:01:41.223271Z","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":"2026-08-12T15:01:41.241125Z","title":"doi: 10.18653/v1/W19-4808","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.241125Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:779230c42ea816cf25adc3f4c76a3a116d6175ed78febe2953f9c026d119c150","observation_id":"01a2e37d-d8fc-4ffb-83ca-6cb49b9ba576","resolution":{"observed_at":"2026-08-12T15:01:41.241125Z","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":"2026-08-12T15:01:41.251595Z","title":"doi: 10.18653/v1/P19-1580","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.251595Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:89472b179b3750b8655525fe5591719687bf57401d2fc22a926d70b4379e64a5","observation_id":"ffcde1c3-7647-432d-bb49-32cb88ee25f7","resolution":{"observed_at":"2026-08-12T15:01:41.251595Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.01506","last_updated":"2021-06-02T23:24:06Z","snapshot_observed_at":"2026-08-16T18:20:06.916553Z","submitted_at":"2021-06-02T23:24:06Z","title":"Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.01506","snapshot_observed_at":"2026-08-12T15:01:41.260138Z","title":"Transformers are deep infinite-dimensional non-mercer binary kernel machines","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.260138Z"},"links":{"cited_paper":"/paper/2106.01506","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:4ff626e2cd2304531c1c36669d782ffa4f93e5f88854274fd7e5770a0af21f62","observation_id":"f7a6cbce-8fe0-4906-bcaf-98470e4b07f1","resolution":{"observed_at":"2026-08-12T15:01:41.260138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02037","last_updated":"2020-10-05T14:17:32Z","snapshot_observed_at":"2026-08-16T19:15:49.054597Z","submitted_at":"2020-10-05T14:17:32Z","title":"Conditional Negative Sampling for Contrastive Learning of Visual Representations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02037","snapshot_observed_at":"2026-08-12T15:01:41.265779Z","title":"Conditional negative sampling for contrastive learning of visual representations","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.265779Z"},"links":{"cited_paper":"/paper/2010.02037","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:89d7b9348ab551182e34057b1be2b2352bfad44912eac6186822104258ac120a","observation_id":"11763011-f7c5-4e15-824f-010fcc2be396","resolution":{"observed_at":"2026-08-12T15:01:41.265779Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.03888","last_updated":"2017-09-13T23:25:07Z","snapshot_observed_at":"2026-08-14T20:41:41.185318Z","submitted_at":"2017-08-13T11:01:57Z","title":"Large Batch Training of Convolutional Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.03888","snapshot_observed_at":"2026-08-12T15:01:41.271783Z","title":"Large batch training of convolutional networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.271783Z"},"links":{"cited_paper":"/paper/1708.03888","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:4812da2bf0c2561db532f1be8a4712c62863f3acc482909121fed5d120599053","observation_id":"63bd31c5-2bcf-44bc-8138-a74f6321030a","resolution":{"observed_at":"2026-08-12T15:01:41.271783Z","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":"2026-08-12T15:01:42.445105Z","title":"(2020), Robinson et al","venue":null,"work_id":"e10ba6ff-7ec7-41ec-a630-49df3808eeb5","year":2020},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.292898Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:e3f93aee1884304c0454c32184c323af64d1e37b39c06bbb3dff32e506af5900","observation_id":"f7e92f60-9f18-49d6-b4d4-257c07418d85","resolution":{"observed_at":"2026-08-12T15:01:42.457749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.371499Z","title":null,"venue":null,"work_id":"5f0c4c3f-88e7-43cc-be0b-a32d64ef7af7","year":2022},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.315815Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:93e70fcca99baa27fa74c268469074c49611e8d9cb69a8536bae34fdc01d3fb8","observation_id":"2c048c82-7461-4f6a-8c9a-50656cd99ed8","resolution":{"observed_at":"2026-08-12T15:01:42.382215Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.343165Z","title":null,"venue":null,"work_id":"f4f67d12-00ba-4eaf-94c1-7123998011b1","year":2022},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.324554Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:546e97840aa5e6182ebd90fb33afda7b0669f2f4198b526a428de0e5b71fc72c","observation_id":"205123e3-f4c2-45a8-b5fa-931eb4edb719","resolution":{"observed_at":"2026-08-12T15:01:42.350399Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.295744Z","title":null,"venue":null,"work_id":"00c5fc83-6cbb-47ff-b1d2-ba9937f10a33","year":2022},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.341152Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:a96b13454b41f6ece401084f2e325099814751a182c07cea174f4be5baa13e56","observation_id":"005cae64-3573-491a-9a95-7b3315548fb4","resolution":{"observed_at":"2026-08-12T15:01:42.307803Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.271188Z","title":null,"venue":null,"work_id":"5399bd39-661c-4c37-a26f-d5e7fa309f9e","year":2020},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.347688Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:e39893adb62d842b2ecb816a94a3231004633d2597020dc6f5807a1e7b7cf21c","observation_id":"95f0a089-ed0b-4373-bf95-98d6324be25f","resolution":{"observed_at":"2026-08-12T15:01:42.276951Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.214280Z","title":"Proof of kernel-based scoring function estimation","venue":null,"work_id":"a2f4a27e-6530-4c26-abcd-49c222e9e1fa","year":2013},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.360380Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:98f0c68203cf351c642060782dd47eb9dc4301ee8da4c67c84473b01b42622fb","observation_id":"c0f2bde3-369a-41a9-8ae6-7a2082f9001e","resolution":{"observed_at":"2026-08-12T15:01:42.225341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.140662Z","title":"Fare and SparseFARE in comparison with unsupervised and supervised models under partial sensitive label access","venue":null,"work_id":"85ccdcd2-da98-4e99-bc22-83425b2a2398","year":2022},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.375649Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:0e449261fa7722f8b0ecb44efa529831e8255eb10fd084e2c3d9c718e191404a","observation_id":"c6d89749-caa6-4698-9b5b-cdb8a579c964","resolution":{"observed_at":"2026-08-12T15:01:42.154642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.105133Z","title":null,"venue":null,"work_id":"41a5d4d0-e3db-4697-afc7-1019e270c00f","year":2022},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.380506Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:66a238d880761707696914ba05dc150025490b0e90ac664a8cade1b772e51f2a","observation_id":"90f4055a-8da5-409e-91d1-449ed5c26320","resolution":{"observed_at":"2026-08-12T15:01:42.112408Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.08731","last_updated":"2020-04-02T05:40:29Z","snapshot_observed_at":"2026-08-17T18:58:45.514336Z","submitted_at":"2019-11-20T06:43:41Z","title":"Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.08731","snapshot_observed_at":"2026-08-12T15:01:41.170173Z","title":"Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":1956,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.170173Z"},"links":{"cited_paper":"/paper/1911.08731","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:5fe5d037fd9ce3b8ae1e035cd0e94d9202ec664a7a5d34fd6813aed0e145674d","observation_id":"c4f39181-6ab9-4892-86d9-559cd498e856","resolution":{"observed_at":"2026-08-12T15:01:41.170173Z","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":"2026-08-12T15:01:42.524435Z","title":"Gradient reversal against discrimination: A fair neural network learning approach","venue":null,"work_id":"befa60a7-b014-4651-a536-9adcac99bd41","year":2018},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":1962,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.134335Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:15df9daf8e37b833acc0e10f8f940d79ff9b35ce141c088ba0a6ef53aeb84bb8","observation_id":"b11f960d-5f0e-4bc1-baf0-83a454e7e75a","resolution":{"observed_at":"2026-08-12T15:01:42.541381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.07040","last_updated":"2023-06-12T11:39:34Z","snapshot_observed_at":"2026-08-18T05:57:26.523579Z","submitted_at":"2023-06-12T11:39:34Z","title":"Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nystr\\\"om method","version":1},"cited_work":{"arxiv_id":"2306.07040","doi":null,"metadata_source":"pith","pith_arxiv_id":"2306.07040","snapshot_observed_at":"2026-08-12T15:01:41.703830Z","title":"Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nystr\\\"om method","venue":"cs.LG","work_id":"76a84b4a-754e-4c8a-90ee-8b289306c919","year":2023},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.193807Z"},"links":{"cited_paper":"/paper/2306.07040","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:9d1ccbdbd587c005dbe7b4e022c0daa8f3207bcc958edbb481f2151b21b93256","observation_id":"8c5eba28-3269-4c53-81e2-c75f958199b5","resolution":{"observed_at":"2026-08-12T15:01:41.714458Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.05568","last_updated":"2023-05-04T08:56:16Z","snapshot_observed_at":"2026-08-16T16:17:11.877142Z","submitted_at":"2022-11-10T13:44:57Z","title":"Unbiased Supervised Contrastive Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.05568","snapshot_observed_at":"2026-08-12T15:01:40.982759Z","title":"Unbiased supervised contrastive learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:40.982759Z"},"links":{"cited_paper":"/paper/2211.05568","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:2693c480a49f6493479d0f20c1534ed57d42837f9152a789970b6aadc05e1f17","observation_id":"ffdcc3d1-628a-4aa6-ab38-f770458c9a38","resolution":{"observed_at":"2026-08-12T15:01:40.982759Z","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":"2026-08-12T15:01:42.410715Z","title":null,"venue":null,"work_id":"73948347-3adb-42c4-a5c7-b08b7469b37d","year":2020},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.307341Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:fce45276a3c57cb1413adb63bb4f94c1d78a39b98094f08b5267555ed92e394f","observation_id":"d0e2bb20-4ff1-4a50-bab2-b1ac376b6248","resolution":{"observed_at":"2026-08-12T15:01:42.423087Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-12T15:01:42.501370Z","title":"Analyzing the structure of attention in a transformer language model","venue":null,"work_id":"ba8c13a8-3953-4ada-9ca5-286a99e36db1","year":2019},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.234405Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:2be32cf5eaa2c2e650a9476061ba1ace7729f8974b142608cbfd2f2d702fb1d7","observation_id":"4f876b86-8f6e-4c35-ac9b-981fd237d990","resolution":{"observed_at":"2026-08-12T15:01:42.509566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.00830","last_updated":"2017-08-10T03:07:31Z","snapshot_observed_at":"2026-08-14T22:25:06.246618Z","submitted_at":"2015-11-03T09:27:49Z","title":"The Variational Fair Autoencoder","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.00830","snapshot_observed_at":"2026-08-12T15:01:41.100185Z","title":"The variational fair autoencoder.arXiv preprint arXiv:1511.00830,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.100185Z"},"links":{"cited_paper":"/paper/1511.00830","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:f16d37259d81ac20fe0bcf26c5c99f3781167153b12d55d985a0b9634563a575","observation_id":"0f467cf9-0929-4782-909b-1cb845e4b663","resolution":{"observed_at":"2026-08-12T15:01:41.100185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.10509","last_updated":"2019-04-23T19:29:47Z","snapshot_observed_at":"2026-08-16T10:03:03.268538Z","submitted_at":"2019-04-23T19:29:47Z","title":"Generating Long Sequences with Sparse Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.10509","snapshot_observed_at":"2026-08-12T15:01:41.025669Z","title":"Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, and Stefanie Jegelka","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.025669Z"},"links":{"cited_paper":"/paper/1904.10509","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:ffba99c87c412d4f2f4e6506296ca44b9336717405891d21c473bc7fa3942136","observation_id":"6e6b2606-1b5f-4e13-8875-4708e027809b","resolution":{"observed_at":"2026-08-12T15:01:41.025669Z","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":"2026-08-12T15:01:41.005425Z","title":"On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.005425Z"},"links":{"citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:010b9eea448cbab5b7ce773dabadaad419c97b275e2aec07026f7c06c4928790","observation_id":"54c90435-3397-42c2-8769-9ca5bc3073ea","resolution":{"observed_at":"2026-08-12T15:01:41.005425Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.06413","last_updated":"2021-03-11T02:01:14Z","snapshot_observed_at":"2026-08-16T18:39:45.300959Z","submitted_at":"2021-03-11T02:01:14Z","title":"FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.06413","snapshot_observed_at":"2026-08-12T15:01:41.012591Z","title":"Fairfil: Contrastive neural debiasing method for pretrained text encoders","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:41.012591Z"},"links":{"cited_paper":"/paper/2103.06413","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:4b49257e057eecac9213929000c099f4939c5e1a6f2971056afce615d8e704ed","observation_id":"040d42a5-3667-4fa4-8ee3-ba7f5ff280ef","resolution":{"observed_at":"2026-08-12T15:01:41.012591Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.05150","last_updated":"2020-12-02T17:52:35Z","snapshot_observed_at":"2026-07-31T17:17:17.205582Z","submitted_at":"2020-04-10T17:54:09Z","title":"Longformer: The Long-Document Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.05150","snapshot_observed_at":"2026-08-12T15:01:40.993658Z","title":"Longformer: The long-document transformer","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-12T15:01:40.993658Z"},"links":{"cited_paper":"/paper/2004.05150","citing_paper":"/paper/2411.14765"},"observation_digest":"sha256:a306e03f3826f88d467f9bc1176d08ac7c4a30d54cfd15ac9d80ff5fa1ad0b96","observation_id":"096ee502-b977-483c-b18e-8ae8d928b33c","resolution":{"observed_at":"2026-08-12T15:01:40.993658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.14765","last_updated":"2024-11-22T07:11:35Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T13:25:05.385471Z","submitted_at":"2024-11-22T07:11:35Z","title":"An Attention-based Framework for Fair Contrastive Learning"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":29,"verified_exact":1,"verified_fuzzy":11},"total_outbound_references":41},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2411.14765."}