{"as_of":"2026-08-13T20:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:316eb45b6e6661be0b4feeacade5b24875190706d286070d846b9a48f3eb4549","coverage":[{"denominator":64,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":64,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:39:58.689879Z","state":"measured"},{"denominator":64,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":64,"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/2507.12998/citation-record","integrity":"/paper/2507.12998/integrity","json":"/paper/2507.12998/citation-record.json","paper":"/paper/2507.12998"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.09540","last_updated":"2023-03-22T17:22:35Z","snapshot_observed_at":"2026-08-06T15:07:40.203199Z","submitted_at":"2023-03-16T17:53:24Z","title":"SemDeDup: Data-efficient learning at web-scale through semantic deduplication","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.09540","snapshot_observed_at":"2026-08-06T16:39:52.461048Z","title":"Semdedup: Data-efficient learning at web-scale through semantic deduplication","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:52.461048Z"},"links":{"cited_paper":"/paper/2303.09540","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:e7dca6f76df5bbffe0c025da7511cc0263f39ba18cf713484682cde37f2dce2b","observation_id":"10a30e41-5a56-4d87-987c-6163f146bf66","resolution":{"observed_at":"2026-08-06T16:39:52.461048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.06481","last_updated":"2016-04-16T19:40:08Z","snapshot_observed_at":"2026-08-13T05:32:35.936349Z","submitted_at":"2015-11-20T03:09:43Z","title":"Variance Reduction in SGD by Distributed Importance Sampling","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.06481","snapshot_observed_at":"2026-08-06T16:39:52.530890Z","title":"Variance reduction in sgd by distributed importance sampling","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:52.530890Z"},"links":{"cited_paper":"/paper/1511.06481","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:36daa76f68bd2b3865f9c7bda83a20e9b0f40ac9e449af99053feb0b5714c939","observation_id":"3dcd97a5-fa3f-45e4-9690-8075366973b5","resolution":{"observed_at":"2026-08-06T16:39:52.530890Z","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":"2026-08-06T16:40:08.019774Z","title":"Vqa: Visual question answering","venue":null,"work_id":"852d2efa-cc80-4a5f-a34e-91b192222c4a","year":2015},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:52.656235Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:38b653fc5c12f7cb6a7c7a12c52ef45a6f546c6de4d9d37ab2590c32793863c3","observation_id":"c25eea3a-8b91-4a52-9040-bbb26e260491","resolution":{"observed_at":"2026-08-06T16:40:08.143988Z","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":"2026-08-06T16:40:07.783163Z","title":"Conceptual 12m: Pushing web-scale image-text pre- training to recognize long-tail visual concepts","venue":null,"work_id":"9a4db7c3-b129-4c5e-bbf3-3a41bea9d18d","year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:52.752443Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:233518268a848ea5af7d97419e9c45ffa9aeb69e34bd28fcb4eebd9d11d780af","observation_id":"2eee9609-0458-4371-94df-6af5e9ee740c","resolution":{"observed_at":"2026-08-06T16:40:07.897905Z","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":"2026-08-06T16:40:07.576422Z","title":"En- hanced multimodal representation learning with cross-modal kd","venue":null,"work_id":"cd071d27-457d-4dc4-99e9-e7eb65607527","year":null},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:52.855848Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:269f64fd8ba0e24984e8a9c7cdb41c46373632c9feebc795572e08ffe812c3a0","observation_id":"e0dcbfed-7c12-4ef7-bfe9-64acd7695ae1","resolution":{"observed_at":"2026-08-06T16:40:07.671182Z","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":"2026-08-06T16:40:07.342661Z","title":"Multi-modal medical diagnosis via large-small model collaboration","venue":null,"work_id":"edaf2206-f8aa-4a51-92b3-aa1c1e1f91a1","year":2025},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:52.927226Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:b87f73abec170034f9f13c0b202d2a0c9cd6723522b933b2a12783e2e4b03d45","observation_id":"959881ed-d8a9-423d-ac24-b7a0c58bbf10","resolution":{"observed_at":"2026-08-06T16:40:07.470249Z","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":"2026-08-06T16:40:07.089475Z","title":"Reproducible scal- ing laws for contrastive language-image learning","venue":null,"work_id":"f16c9b9f-b097-4a40-a684-3b51c9f34d48","year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.001994Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:0f13dce32e315b7af00ec5fa9fed58cb4494925b1191afbce4712620366813e8","observation_id":"9c1ef63b-a486-40e6-8ac3-a8865a9d18a0","resolution":{"observed_at":"2026-08-06T16:40:07.222610Z","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":"1906.11829","last_updated":"2020-10-27T00:52:20Z","snapshot_observed_at":"2026-07-06T08:03:24.054624Z","submitted_at":"2019-06-26T23:01:47Z","title":"Selection via Proxy: Efficient Data Selection for Deep Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.11829","snapshot_observed_at":"2026-08-06T16:39:53.073154Z","title":"Selection via proxy: Efficient data se- lection for deep learning","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.073154Z"},"links":{"cited_paper":"/paper/1906.11829","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:cd14ec3a3620dff8cedd60258394ceb295c1f0405a72446a7f67e9662469971e","observation_id":"928f4bd5-d955-4d7e-b8a8-72f2c52a9186","resolution":{"observed_at":"2026-08-06T16:39:53.073154Z","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":"2026-08-06T16:40:06.876366Z","title":"Unichest: Conquer-and-divide pre-training for multi-source chest x-ray classification","venue":null,"work_id":"f376d4be-55cd-4a3f-a27e-01cd15b4df1a","year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.149675Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:fca25135011f5919e9aa483a316452e6902e37306b9e24c75c5047c9296facaa","observation_id":"0f80758d-5fb7-44ae-aa9e-6342fbc01ce5","resolution":{"observed_at":"2026-08-06T16:40:06.978153Z","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":"2411.09126","last_updated":"2024-11-14T01:53:17Z","snapshot_observed_at":"2026-08-12T20:57:39.539477Z","submitted_at":"2024-11-14T01:53:17Z","title":"SCAN: Bootstrapping Contrastive Pre-training for Data Efficiency","version":1},"cited_work":{"arxiv_id":"2411.09126","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.09126","snapshot_observed_at":"2026-08-06T16:39:59.209828Z","title":"SCAN: Bootstrapping Contrastive Pre-training for Data Efficiency","venue":"cs.CV","work_id":"bc4981c8-6153-4314-93a1-15aac70c8917","year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.252726Z"},"links":{"cited_paper":"/paper/2411.09126","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:1ccfb3047d1fbac92deabdc0ba647c0f8b717182c2962e5c891b5015bb908300","observation_id":"253de328-8edc-4946-8784-483e30e37744","resolution":{"observed_at":"2026-08-06T16:39:59.292646Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-06T16:40:06.639607Z","title":"Co- teaching: Robust training of deep neural networks with ex- tremely noisy labels","venue":null,"work_id":"26181695-f7f5-4097-a8d9-7dc7820c43d4","year":2018},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.387731Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:4400b603409a6ec94fe089f07d64e6f79d836e4ee4763ee217897484a82c042a","observation_id":"d9f467c1-4e9c-44d4-8d02-ccffe147a4a7","resolution":{"observed_at":"2026-08-06T16:40:06.752633Z","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":"2026-08-06T16:40:06.345943Z","title":"Trustworthy machine learning: From data to models","venue":null,"work_id":"3a846e16-53cf-48f4-8b3f-3e840cb16940","year":2025},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.442840Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:5233e4a777440d5c53c3a4b74b3df38a015698ca70ca4df50c6044d8b7ef2704","observation_id":"d8e5fc33-e240-468d-910d-b88f4ff988ac","resolution":{"observed_at":"2026-08-06T16:40:06.467071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:39:53.525787Z","title":"Momentum contrast for unsupervised visual rep- resentation learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.525787Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:39a1b4ed7509e63a323866a2b90f38087310979a6a5e91c2b7be7a8e5b2d63f7","observation_id":"45a42984-21bb-42f4-b331-5da167f182e0","resolution":{"observed_at":"2026-08-06T16:39:53.525787Z","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":"2026-08-06T16:40:06.097724Z","title":"Large- scale dataset pruning with dynamic uncertainty","venue":null,"work_id":"462e3ad5-2082-443b-9f4e-5e64dbcb5019","year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.622480Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:20bce50c13d3087325c2e6a4cef88e641add4ccc3b31e4746272a50d5674ce96","observation_id":"ffe65d37-279c-4e56-9443-fefd531f5af8","resolution":{"observed_at":"2026-08-06T16:40:06.200797Z","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":"2104.08718","last_updated":"2022-03-23T19:47:21Z","snapshot_observed_at":"2026-07-06T11:01:02.207193Z","submitted_at":"2021-04-18T05:00:29Z","title":"CLIPScore: A Reference-free Evaluation Metric for Image Captioning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08718","snapshot_observed_at":"2026-08-06T16:39:53.698259Z","title":"Clipscore: A reference-free evaluation met- ric for image captioning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.698259Z"},"links":{"cited_paper":"/paper/2104.08718","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:8993b67ac71cf166b526b2bd03b25214e6f5aba4e1d54b15be08b68a2b97a957","observation_id":"36bf5d9e-1302-4409-a14d-12c04e928fb8","resolution":{"observed_at":"2026-08-06T16:39:53.698259Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04872","last_updated":"2024-06-07T12:12:20Z","snapshot_observed_at":"2026-08-12T23:47:56.275006Z","submitted_at":"2024-06-07T12:12:20Z","title":"Diversified Batch Selection for Training Acceleration","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04872","snapshot_observed_at":"2026-08-06T16:39:53.803023Z","title":"Diversified batch selection for training acceleration","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.803023Z"},"links":{"cited_paper":"/paper/2406.04872","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:b2118f128a2bd044da4d506b30ac70b56eaebe6b3634d4e5eaa1f2a61256946d","observation_id":"f79f7a7a-bfda-4a90-8fe2-1c90fd238621","resolution":{"observed_at":"2026-08-06T16:39:53.803023Z","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":"2026-08-06T16:40:05.836269Z","title":"Learning with noisy correspondence for cross-modal matching.Advances in Neu- ral Information Processing Systems, 34:29406–29419, 2021","venue":null,"work_id":"702011dc-7ddd-484d-a9d4-11982a32fff4","year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.892105Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:0e950b1bb00cdd2a2fabe616fd3f17c6919bd48fd808f938b7654d113f196d4f","observation_id":"ecda78c8-bba6-45f3-bcc8-1b914d2f7ae3","resolution":{"observed_at":"2026-08-06T16:40:05.936712Z","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":"2026-08-06T16:40:05.547669Z","title":"Open- clip, 2021","venue":null,"work_id":"ae0bb5ae-21ef-4d50-9df9-46fd09a60976","year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:53.969391Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:d697b24a3536b670e4c0ea1330aebc24fe0e1039a9d7af52bcdf0a86ef9c12d9","observation_id":"4d50d930-74f7-4d02-99ae-28e0a2010a2e","resolution":{"observed_at":"2026-08-06T16:40:05.671632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:39:54.052698Z","title":"Scaling up visual and vision-language representa- tion learning with noisy text supervision","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.052698Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:dba3b93b6f69aa4db4ab9f1d1c1160cdc729ede2c2697ba44fbedfbd2f219e91","observation_id":"6243a609-73de-40a7-8bfc-00474f36de72","resolution":{"observed_at":"2026-08-06T16:39:54.052698Z","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":"2026-08-06T16:40:05.306530Z","title":"In-datacenter perfor- mance analysis of a tensor processing unit","venue":null,"work_id":"a6c5f27a-8753-44a6-8040-91f1ce0a96d0","year":2017},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.123535Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:ab103a41f45264d53a1792d5761aa0a2f2b69467c28c6fd6de303755289e958d","observation_id":"30a075b9-8e3f-4de7-8e51-71ef1effd41f","resolution":{"observed_at":"2026-08-06T16:40:05.428284Z","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":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-08-13T17:41:53.092611Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-06T16:39:54.218346Z","title":"Scaling laws for neural language models","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.218346Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:c223582e5b00d7df612e66a4097acf456c60649ee23e1e73be2ffdbd057c8dca","observation_id":"255f6736-488b-408b-bd07-b09e53b06ac3","resolution":{"observed_at":"2026-08-06T16:39:54.218346Z","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":"2026-08-06T16:40:05.063719Z","title":"Deep visual-semantic align- ments for generating image descriptions","venue":null,"work_id":"22d41d26-6bb3-4417-ac03-044ae6db18ea","year":2015},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.303861Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:f20b4be40c13cf019019af1f602fdf3f9c6ebc2bc50426f7cd5508c617c7ccac","observation_id":"653dbccc-c956-43ac-b4f7-4eff9b2a2440","resolution":{"observed_at":"2026-08-06T16:40:05.178712Z","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":"2026-08-06T16:40:04.762082Z","title":"Vilt: Vision- and-language transformer without convolution or region su- pervision","venue":null,"work_id":"8090df3e-8637-4d91-98a4-1aa20417eb92","year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.378091Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:3da38f5c2437a1064a3fd689868a9a08806b9f61de90b62bf3b6a21ce1c2d390","observation_id":"32ad8ff2-2c81-4788-96ee-cc55c38a086c","resolution":{"observed_at":"2026-08-06T16:40:04.924941Z","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":"1610.02242","last_updated":"2017-03-15T14:22:41Z","snapshot_observed_at":"2026-08-01T18:35:12.430501Z","submitted_at":"2016-10-07T12:15:42Z","title":"Temporal Ensembling for Semi-Supervised Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.02242","snapshot_observed_at":"2026-08-06T16:39:54.448520Z","title":"Temporal ensembling for semi- supervised learning","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.448520Z"},"links":{"cited_paper":"/paper/1610.02242","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:fed072f36680400837fae219b64cd59bbb13dbf866ce1c108e5f2f4e61ec69b7","observation_id":"b0af26f1-370a-4452-9061-84ff082487d8","resolution":{"observed_at":"2026-08-06T16:39:54.448520Z","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":"2026-08-06T16:40:04.512751Z","title":"Clip benchmark, 2023","venue":null,"work_id":"5b8fd476-ac11-47cb-8ac9-f1f362fc8ce6","year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.524008Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:db25f0b3d58511159f2372cea33ebf693757cdf31a29ef846c4c2ebb56da2f19","observation_id":"af36b614-68e6-4721-b3f0-a102343681ec","resolution":{"observed_at":"2026-08-06T16:40:04.620588Z","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":"2002.07394","last_updated":"2020-02-18T06:20:06Z","snapshot_observed_at":"2026-08-06T03:18:08.960708Z","submitted_at":"2020-02-18T06:20:06Z","title":"DivideMix: Learning with Noisy Labels as Semi-supervised Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.07394","snapshot_observed_at":"2026-08-06T16:39:54.659004Z","title":"Dividemix: Learning with noisy labels as semi-supervised learning","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.659004Z"},"links":{"cited_paper":"/paper/2002.07394","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:15ba3fac0fcdf7f48c2c15b2fac3e3d89499f6631974535989744264548d63be","observation_id":"44aa778d-664b-4a4d-99c9-7f0189571158","resolution":{"observed_at":"2026-08-06T16:39:54.659004Z","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":"2026-08-06T16:40:04.245324Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation","venue":null,"work_id":"b357bdf2-ff56-488a-9345-26c711f382e8","year":2022},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.730003Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:0bfafb81b320aa99c45ce67f27645a05007afb06ed80e24e93a660046aceafbe","observation_id":"4b5cd590-907c-4079-a034-9c026beb59b9","resolution":{"observed_at":"2026-08-06T16:40:04.384547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:39:54.816815Z","title":"Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.816815Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:fffd39b4eab54ae9c9a01995f31ea1daecb5fa51b1e49fab3ba0fd0bea5d4f9e","observation_id":"db6965f2-db48-4cbf-8828-936944773216","resolution":{"observed_at":"2026-08-06T16:39:54.816815Z","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":"2026-08-06T16:40:03.945720Z","title":"Visual semantic reasoning for image-text matching","venue":null,"work_id":"c33182f1-b6e2-46a7-aa0c-c524ece46b9e","year":2019},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:54.924547Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:69a096d088a15dc6dd4e74499cb4a08db13dc0f666e577309fc1a835ed4e39db","observation_id":"3089ca8d-ab0d-4077-b965-f8af41c9cbe2","resolution":{"observed_at":"2026-08-06T16:40:04.096217Z","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":"2026-08-06T16:40:03.698888Z","title":"Tsang, and Zhenwen Ren","venue":null,"work_id":"c65f3439-41f8-4df0-af8e-aa8970f20d01","year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.006063Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:c91cc463dae04c8b1bbd22c2cd494b772b9cfe5f555b06970ca3b3118b424b3a","observation_id":"9090583a-cff7-445c-81ff-02955907d076","resolution":{"observed_at":"2026-08-06T16:40:03.805923Z","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":"2026-08-06T16:40:03.435135Z","title":"Tsang, and Zhenwen Ren","venue":null,"work_id":"39f60d4d-ad95-4aef-b740-956afe1b245f","year":2025},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.106659Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:cb1e7d8f85e2a8f0119efb30ad01e2f38dc24fc4a3ea5324a90ecd72e9a940c8","observation_id":"85998084-434c-4ff4-9653-4d7b3bc7917f","resolution":{"observed_at":"2026-08-06T16:40:03.580020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:39:55.203226Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.203226Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:cb246e6b7884b476be6e3fbfe9222773ebf5548a5b9220619d3da055e8b57622","observation_id":"92ae14ab-9398-4ea7-a3ec-b2e73febde3f","resolution":{"observed_at":"2026-08-06T16:39:55.203226Z","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":"2026-08-06T16:40:03.146256Z","title":"Early-learning regularization pre- vents memorization of noisy labels","venue":null,"work_id":"feb4a6c3-b29a-4d02-8b82-d1edab9b3024","year":2020},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.307608Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:6945cd8165562aa6608da1d19230ec41ce9b15254cadc33db26c1b1ca5cef71f","observation_id":"99482494-1f1d-43e3-8f39-b0f3b133d486","resolution":{"observed_at":"2026-08-06T16:40:03.297756Z","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":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-08-09T20:34:52.923500Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-06T16:39:55.389627Z","title":"Decoupled weight decay regularization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.389627Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:feb2d695a6a29744bbffe2807d174a1c5f233ed92f3746a466c160d6f059f371","observation_id":"caeee8e5-dd30-41bb-aab2-da50f9f1fca8","resolution":{"observed_at":"2026-08-06T16:39:55.389627Z","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":"2026-08-06T16:40:02.897859Z","title":"Sieve: Multimodal dataset pruning using image captioning models","venue":null,"work_id":"8ac6c9e5-7be0-4a6c-a6d5-43a95450528b","year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.532820Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:974cc1dd6ac4fef670ee0d364bb3add27a2da9c7bc121401445913e5e327e510","observation_id":"60460e17-f380-4d0e-ab0d-325f8667185d","resolution":{"observed_at":"2026-08-06T16:40:02.980296Z","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":"2026-08-06T16:40:02.556936Z","title":"Prioritized training on points that are learnable, worth learning, and not yet learnt","venue":null,"work_id":"fc886d1f-1d11-4dfc-b7a5-d509a212eea4","year":null},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.610054Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:7dcaa7e04afbf419e1090bcbddc2bed169aeef5d46510eec597c58bce47e487d","observation_id":"e3cbc7c1-7127-4d67-a715-3cf06ebd6764","resolution":{"observed_at":"2026-08-06T16:40:02.722173Z","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":"2026-08-06T16:40:02.231171Z","title":"Improving multimodal datasets with image captioning","venue":null,"work_id":"1e9bf1ce-34e3-4e9f-a4f4-6ace33b3a9b1","year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.717072Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:6343b89c9fb304c9583de5e22a4d4b7403a369da99d86f84ba221a1d331ebab9","observation_id":"1ca8e387-34c3-4653-ba9e-ad30059afbec","resolution":{"observed_at":"2026-08-06T16:40:02.365819Z","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":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-07-06T06:49:24.960992Z","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":"2026-08-06T16:39:55.837722Z","title":"Repre- sentation learning with contrastive predictive coding","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.837722Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:c124f93403028d95bd3f64fdd18075936e06080498cfe4ac4d4baaf739422d42","observation_id":"20ee0b9a-d310-4cd5-ab97-b45a04e97a62","resolution":{"observed_at":"2026-08-06T16:39:55.837722Z","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":"2026-08-06T16:40:01.960645Z","title":"Active learning is a strong baseline for data subset selection","venue":null,"work_id":"ba686b7f-2f81-43ac-92a8-f449bd0ed5f9","year":2022},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:55.965433Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:8e777818a577ccf2026fbd52f6ba1f1f47465da047b130765d823472beb9c95d","observation_id":"e4014080-d724-4410-89c4-80a27d9b9be9","resolution":{"observed_at":"2026-08-06T16:40:02.020081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:39:56.071287Z","title":"Pytorch: An im- perative style, high-performance deep learning library","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.071287Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:91fab2b3e958c388c5de20e97558b26e1a67672f85644ecbc5f77d8a9d66ed3a","observation_id":"f4ecfed7-c958-4939-998a-b063772ee0d1","resolution":{"observed_at":"2026-08-06T16:39:56.071287Z","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":"2026-08-06T16:40:01.692042Z","title":"Deep learning on a data diet: Finding important ex- amples early in training","venue":null,"work_id":"ce448799-5803-4b96-8cdb-2386072be6f5","year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.164064Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:c16b1a86110401185c882ba9ce3215b04ad8bc537c9e61ff3a241d2d064ac26c","observation_id":"90985c85-2556-496d-af2e-902c70d1ae70","resolution":{"observed_at":"2026-08-06T16:40:01.813071Z","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":"2303.04947","last_updated":"2023-10-20T04:38:34Z","snapshot_observed_at":"2026-08-13T12:28:44.429589Z","submitted_at":"2023-03-08T23:40:47Z","title":"InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.04947","snapshot_observed_at":"2026-08-06T16:39:56.268656Z","title":"Infobatch: Lossless training speed up by unbiased dynamic data pruning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.268656Z"},"links":{"cited_paper":"/paper/2303.04947","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:053059870c8f836660c85f69daac678ea69c56cfecdc6caae7d829392f610f4a","observation_id":"655cd42e-e420-43ac-8fd0-072efa711d96","resolution":{"observed_at":"2026-08-06T16:39:56.268656Z","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":"2026-08-06T16:39:56.367171Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.367171Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:dfa1145204f99b063cc70713230ab55c84365288228d200790303702055ef8a2","observation_id":"a51a8dcf-ee8c-4ebb-bc23-a128fe176185","resolution":{"observed_at":"2026-08-06T16:39:56.367171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.12621","last_updated":"2021-11-24T16:47:34Z","snapshot_observed_at":"2026-08-13T17:28:17.663028Z","submitted_at":"2021-11-24T16:47:34Z","title":"Accelerating Deep Learning with Dynamic Data Pruning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.12621","snapshot_observed_at":"2026-08-06T16:39:56.466975Z","title":"Accelerat- ing deep learning with dynamic data pruning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.466975Z"},"links":{"cited_paper":"/paper/2111.12621","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:b112608b7407ca93f711d7eca6772db8c5cee43e1e0a072821a24186c6cf2077","observation_id":"db60d80e-3350-45de-97c4-a14092878c6e","resolution":{"observed_at":"2026-08-06T16:39:56.466975Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.02114","last_updated":"2021-11-03T10:16:39Z","snapshot_observed_at":"2026-08-02T08:12:49.547570Z","submitted_at":"2021-11-03T10:16:39Z","title":"LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.02114","snapshot_observed_at":"2026-08-06T16:39:56.580874Z","title":"Laion-400m: Open dataset of clip-filtered 400 million image-text pairs","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.580874Z"},"links":{"cited_paper":"/paper/2111.02114","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:215cda8f16194ae235af9ba7d1be9f7d2fc12aab5df34115797b78268982e931","observation_id":"27721489-6858-4ab8-97a0-6cbd8731e71a","resolution":{"observed_at":"2026-08-06T16:39:56.580874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.00489","last_updated":"2018-06-01T10:17:23Z","snapshot_observed_at":"2026-07-06T05:53:39.440274Z","submitted_at":"2017-08-01T19:50:53Z","title":"Active Learning for Convolutional Neural Networks: A Core-Set Approach","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.00489","snapshot_observed_at":"2026-08-06T16:39:56.656179Z","title":"Active learning for convolu- tional neural networks: A core-set approach","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.656179Z"},"links":{"cited_paper":"/paper/1708.00489","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:97e4df5f2be329e0c750b97427b2ba0ed26cdd63f84ed94e84868f736e8a871e","observation_id":"594569fc-edcd-46a6-8154-e8c10e62ad54","resolution":{"observed_at":"2026-08-06T16:39:56.656179Z","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":"2026-08-06T16:40:01.415906Z","title":"Machine learning and deep learning: A review of methods and applications","venue":null,"work_id":"25544a63-d268-4336-99b9-12dbe4ad11dd","year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.731753Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:662fb4d302a4617367bd6cbb50723bdf70cbdbc48e212d8c710a07a2cbd6d481","observation_id":"8d83c38a-7b5a-4cf1-a357-4b7a76aa944d","resolution":{"observed_at":"2026-08-06T16:40:01.547622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:39:56.808998Z","title":"Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.808998Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:4936f165484a5cef4b69d5bcc55bcfdb3941ac2e225eaf8075d334d214eab5c0","observation_id":"8408b420-3a29-48ca-97b9-270bdbe20916","resolution":{"observed_at":"2026-08-06T16:39:56.808998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.00491","last_updated":"2019-07-21T05:26:36Z","snapshot_observed_at":"2026-08-01T22:56:26.162617Z","submitted_at":"2018-11-01T16:47:44Z","title":"A Corpus for Reasoning About Natural Language Grounded in Photographs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.00491","snapshot_observed_at":"2026-08-06T16:39:56.886717Z","title":"A corpus for reasoning about natural language grounded in photographs","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.886717Z"},"links":{"cited_paper":"/paper/1811.00491","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:e163db40cc9952dd7706e18c3bbe2e5ceb57cd6e70420c85081dcd846adea58c","observation_id":"3a3b4376-8b6e-44e3-8af3-a1cd0444c63e","resolution":{"observed_at":"2026-08-06T16:39:56.886717Z","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":"2026-08-06T16:39:56.971625Z","title":"Yfcc100m: The new data in multimedia research","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:56.971625Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:a3ce240e92ee0ced3e9393ff6cf676b06f1ec94bb14ea41a9b91aecf0bf0dbd5","observation_id":"16174e04-189c-4429-be81-44d7a0efe445","resolution":{"observed_at":"2026-08-06T16:39:56.971625Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.05159","last_updated":"2019-11-15T17:08:30Z","snapshot_observed_at":"2026-08-13T03:43:32.324740Z","submitted_at":"2018-12-12T21:24:15Z","title":"An Empirical Study of Example Forgetting during Deep Neural Network Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.05159","snapshot_observed_at":"2026-08-06T16:39:57.069582Z","title":"An empirical study of example forget- ting during deep neural network learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.069582Z"},"links":{"cited_paper":"/paper/1812.05159","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:9d37ddff2d9d090153cab1f725e66ad696815f9f99dc8457afabf93ce0dcf691","observation_id":"3ac38b87-291d-4736-ac47-05c462c1cf4a","resolution":{"observed_at":"2026-08-06T16:39:57.069582Z","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":"2026-08-06T16:40:01.148717Z","title":"Too large; data reduction for vision-language pre-training","venue":null,"work_id":"87f7c2c6-064d-477e-b883-a5e01ecbd1e9","year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.151274Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:9dd4994faec9191722d1c7c4b608a0c031a8a43600becdf685c0bb77bbbb7589","observation_id":"ad117ec9-99d2-4cb1-ac95-7632e806a089","resolution":{"observed_at":"2026-08-06T16:40:01.290850Z","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":"2026-08-06T16:40:00.817079Z","title":"Cliploss and norm-based data selection methods for multimodal con- trastive learning","venue":null,"work_id":"2ee51bff-79c3-425d-924d-34b634f0bb9d","year":2025},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.203491Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:06fbb509346b1e30328e67f98d2c8cb0ddf0e27ad617f225d90ffc3745ac98c5","observation_id":"f9058c8a-2d40-42d0-b76d-b8bbee122f67","resolution":{"observed_at":"2026-08-06T16:40:00.976043Z","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":"2406.03880","last_updated":"2024-06-06T09:17:40Z","snapshot_observed_at":"2026-08-12T23:48:59.076541Z","submitted_at":"2024-06-06T09:17:40Z","title":"Memorization in deep learning: A survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03880","snapshot_observed_at":"2026-08-06T16:39:57.272815Z","title":"Memorization in deep learning: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.272815Z"},"links":{"cited_paper":"/paper/2406.03880","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:4bee626001bb9d3bf97615efd59075b48c95e276b2e3d2cf1f78f30bd7ddb710","observation_id":"62ae9cf0-c8c6-446b-9615-11b22448e936","resolution":{"observed_at":"2026-08-06T16:39:57.272815Z","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":"2026-08-06T16:39:57.415821Z","title":"Icons: Influence consensus for vision-language data selection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.415821Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:b0736b4081817edf87ef980774c72501a8ea2eabb660d02f88c502913676607b","observation_id":"6830b7ae-56eb-4eb5-beff-56e26506db22","resolution":{"observed_at":"2026-08-06T16:39:57.415821Z","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":"2026-08-06T16:40:00.548538Z","title":"Moderate coreset: A universal method of data selection for real-world data-efficient deep learning","venue":null,"work_id":"16a2a6c5-a702-4b29-839f-7f26cecf830b","year":2022},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.551605Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:64a04b6629f0ba03e6b205e6289b494f55a290fd6119676ff97902fdeb489c30","observation_id":"d24cd1ce-284b-4dbb-8e99-52af002ff122","resolution":{"observed_at":"2026-08-06T16:40:00.659249Z","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":"2026-08-06T16:40:00.394730Z","title":"Bicro: Noisy correspon- dence rectification for multi-modality data via bi-directional cross-modal similarity consistency","venue":null,"work_id":"f63cfa2b-d209-423e-8ed7-26de9f496f04","year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.686859Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:4e07782d67eded76ab214dd2c50202271ce5a1dd3719818c10500f5369dd58d5","observation_id":"940e6adc-721b-4b9c-9337-507a30102f38","resolution":{"observed_at":"2026-08-06T16:40:00.466499Z","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":"2026-08-06T16:40:00.157360Z","title":"Latent class-conditional noise model","venue":null,"work_id":"ab16ee55-e0b0-4cdb-90e4-edf9b84ee88e","year":2023},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.778546Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:53b2ee6d049783b6af25184322fe2a6d762c5811be7a9d9c0bedbb86e3129d77","observation_id":"162a73ca-1670-48b0-8e20-c81364edc06f","resolution":{"observed_at":"2026-08-06T16:40:00.318510Z","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":"2026-08-06T16:40:00.019406Z","title":"On early stopping in gradient descent learning","venue":null,"work_id":"670b2935-bc42-4a22-ab14-106c82ac3fd5","year":2007},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:57.876911Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:55e3f35471bd1a870b6f2695b6fa79ee86b16d87ddcd3e8b8c6c104a3e0e0ff6","observation_id":"b34a92ab-b7f3-478b-a09f-b59afbacf53a","resolution":{"observed_at":"2026-08-06T16:40:00.087421Z","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":"2026-08-06T16:39:59.831678Z","title":"From image descriptions to visual denotations: New similarity metrics for semantic inference over event descrip- tions","venue":null,"work_id":"bbf72626-224c-47b9-af0e-e85924ba9d1c","year":2014},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:58.066586Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:99b606baab3e3d40f79cc11c35d2249e9d40cb6f1285ce2a2d8fdd159cc23bc3","observation_id":"39f06a3c-8916-42cf-b9e1-08ac95d31347","resolution":{"observed_at":"2026-08-06T16:39:59.895072Z","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":"2026-08-06T16:39:59.636007Z","title":"Mitigating noisy corre- spondence by geometrical structure consistency learning","venue":null,"work_id":"2adb454d-a7aa-4156-b76a-134f91587074","year":2024},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:58.227093Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:8da6e2419cb78217441b91dfaffca969a6e202c7df7c58d8fd1d1b9183596f22","observation_id":"5f0c6063-136d-4356-8a35-b1172640bbda","resolution":{"observed_at":"2026-08-06T16:39:59.760581Z","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":"2210.15809","last_updated":"2023-03-06T04:54:25Z","snapshot_observed_at":"2026-08-13T13:54:51.936665Z","submitted_at":"2022-10-28T00:14:00Z","title":"Coverage-centric Coreset Selection for High Pruning Rates","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.15809","snapshot_observed_at":"2026-08-06T16:39:58.368301Z","title":"Coverage-centric coreset selection for high pruning rates","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:58.368301Z"},"links":{"cited_paper":"/paper/2210.15809","citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:9536c9d234c9fc66d198841d32e2d093561aea62f2963426b13ff558043082f7","observation_id":"674260a7-b5ff-42bc-9d39-00cdaec04f00","resolution":{"observed_at":"2026-08-06T16:39:58.368301Z","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":"2503.22215","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:39:58.800437Z","title":"Learn- ing to instruct for visual instruction tuning","venue":null,"work_id":"b1cbb22f-2ba5-4f6f-855b-8b58ba861cb1","year":2025},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:58.527732Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:4c555a1ab65022f9110422f922f8cab65aea6599b1aa3014621f4115bc45013b","observation_id":"6f39a56c-16bf-4166-b1e7-ae9b36d0a875","resolution":{"observed_at":"2026-08-06T16:39:58.908079Z","resolver_source":"raw_fallback","status":"verified_exact"},"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":"2026-08-06T16:39:59.396663Z","title":"Uncover the balanced geometry in long-tailed contrastive language-image pretraining","venue":null,"work_id":"1ee343af-6c3f-4d35-8744-2ca8ba57c1af","year":2025},"citing_paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T16:39:58.689879Z"},"links":{"citing_paper":"/paper/2507.12998"},"observation_digest":"sha256:adeff9fc2763874a849e10b72e461829fa4dbfe0c9e52ab353d504a3ca055cb1","observation_id":"660fdd27-c0e4-4ef9-825f-dc32dd361601","resolution":{"observed_at":"2026-08-06T16:39:59.491818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.12998","last_updated":"2025-07-17T11:13:44Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T11:10:26.427821Z","submitted_at":"2025-07-17T11:13:44Z","title":"Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning"},"reference_resolution":{"displayed":64,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":2,"verified_fuzzy":35},"total_outbound_references":64},"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 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2507.12998."}