{"as_of":"2026-08-18T06:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0817ca7517b382053a429ed870cdc8042f66225c8b6a9b88845a84519c5fe47f","coverage":[{"denominator":70,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":70,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T20:50:32.704284Z","state":"measured"},{"denominator":70,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":70,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2506.01987/citation-record","integrity":"/paper/2506.01987/integrity","json":"/paper/2506.01987/citation-record.json","paper":"/paper/2506.01987"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T20:50:32.364665Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.364665Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:2122bc564766c1ea976dcccdb6b3c2a7833c67bfb6dd5292813db599c5717d8f","observation_id":"13e6047b-56a6-4688-942b-64f9c4df197f","resolution":{"observed_at":"2026-08-15T20:50:32.364665Z","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":"2026-08-15T20:50:32.370339Z","title":"Emerging properties in self-supervised vision transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.370339Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:f0adda6809429aa31463ca57f4949a79efdb84e1704365995c4ff2dcc1c09fbb","observation_id":"c57b2196-4d00-4f6a-aa1c-ea2199dddf85","resolution":{"observed_at":"2026-08-15T20:50:32.370339Z","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":"2026-08-15T20:50:33.695561Z","title":"Semi- supervised knowledge distillation for model compression","venue":null,"work_id":"4496407e-385f-43ae-a2c1-d32efe3dc19b","year":2020},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.375144Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:c7231b3eba84006bd29a267e6d0107960c63f060199a8cf465ba873408c11921","observation_id":"0ea1fd40-7260-400d-a668-2dcb220b3d03","resolution":{"observed_at":"2026-08-15T20:50:33.700568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.381025Z","title":"A simple framework for contrastive learning of visual representations","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.381025Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:7240f9ca60d5b14a93db425f9557a779c635bfdcda0243995a77b1c15777916f","observation_id":"8ae60da6-ecba-4438-88cd-ba7ae77624a5","resolution":{"observed_at":"2026-08-15T20:50:32.381025Z","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":"2026-08-15T20:50:32.385832Z","title":"An empirical study of training self-supervised vision transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.385832Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:94f5f6ba03c6222c71ad38a95a57a8a53d26a000017b816caec69f5aa68e107e","observation_id":"c81c9ffe-bd02-4f55-9c44-26e64e0b6a89","resolution":{"observed_at":"2026-08-15T20:50:32.385832Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1710.09282","last_updated":"2020-06-14T19:10:03Z","snapshot_observed_at":"2026-08-14T20:21:05.078282Z","submitted_at":"2017-10-23T20:16:55Z","title":"A Survey of Model Compression and Acceleration for Deep Neural Networks","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.09282","snapshot_observed_at":"2026-08-15T20:50:32.391662Z","title":"A survey of model compression and acceleration for deep neural networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.391662Z"},"links":{"cited_paper":"/paper/1710.09282","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:2dd0a4c595cf5444a149ce34bed6d24f480c4b103867f3cd1111c113c2d88059","observation_id":"ba9c1090-111d-416b-94f4-b82b7664c2ff","resolution":{"observed_at":"2026-08-15T20:50:32.391662Z","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":"2026-08-15T20:50:33.659311Z","title":"Robust locally weighted regression and smoothing scatterplots","venue":null,"work_id":"96cf2342-0aa3-49c3-ad86-7ca53d97c306","year":1979},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.397482Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:db4d523cd2e3b8a7c186cfa1a4954703530d53d1b495da56fd1cfbe677149841","observation_id":"1fe0ebc7-cc34-40a1-a7ff-0e15688c40cd","resolution":{"observed_at":"2026-08-15T20:50:33.664171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.643818Z","title":"Dc-bench: Dataset condensation bench- mark","venue":null,"work_id":"49ee1309-2135-466c-adc5-530df259e9c6","year":2022},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.402773Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:96e02b01cd116d2b1b5ee1225a24ab45faca7a6ea803aeaedb9b55bbef105683","observation_id":"2f2ce208-b557-480d-bb01-34a2eb91b132","resolution":{"observed_at":"2026-08-15T20:50:33.648849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.407181Z","title":"Imagenet: A large- scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.407181Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:edced0f1684ca606d9c42cbf73ef725104a45d3ca1ec5297709a658cd1c23df2","observation_id":"dfb2c368-3083-4e0c-bdec-c949b6d12704","resolution":{"observed_at":"2026-08-15T20:50:32.407181Z","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":"2026-08-15T20:50:33.618187Z","title":"Imagenet: A large- scale hierarchical image database","venue":null,"work_id":"17a363b4-2107-4435-be9d-6f37aea1ff2d","year":2009},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.411653Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:9c176b5cfec6675798a556d20a680289353b081bee235246e040cdf73eb56740","observation_id":"a6540a8e-d526-47ae-ac8e-615b80c8f543","resolution":{"observed_at":"2026-08-15T20:50:33.623431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.417089Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.417089Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:942706291fec203f7dc8ae37686d5776e0cf408aeb04131079519542252afdcf","observation_id":"0726f5b4-f70c-44b2-862d-f6c781000aae","resolution":{"observed_at":"2026-08-15T20:50:32.417089Z","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":"2026-08-15T20:50:33.592963Z","title":"Scaling laws of synthetic images for model training","venue":null,"work_id":"1c569283-b81e-4902-95a3-696e8e561e7c","year":2024},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.421713Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:d6466d0102bf4c354fa806e051b273f367e87e140b20b1012fd29078f0bde550","observation_id":"89726db7-ddff-474d-a191-56d89987e9e9","resolution":{"observed_at":"2026-08-15T20:50:33.597753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.06441","last_updated":"2023-03-31T00:08:46Z","snapshot_observed_at":"2026-08-16T16:24:44.649752Z","submitted_at":"2022-10-12T17:42:01Z","title":"How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.06441","snapshot_observed_at":"2026-08-15T20:50:32.426143Z","title":"How much data are augmentations worth? an investigation into scaling laws, invariance, and implicit regularization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.426143Z"},"links":{"cited_paper":"/paper/2210.06441","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:c6976089e4c349b49b9e3adfd78724bf09cd06362741d09ba1e9956cff4c0365","observation_id":"03f07747-c3a0-44d1-a209-531a759197e5","resolution":{"observed_at":"2026-08-15T20:50:32.426143Z","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":"2026-08-15T20:50:32.431570Z","title":"Knowledge distillation: A survey","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.431570Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:e01ca3fbe1a777fafefa56e4eaa5034e58aa2169a3d00e671d0aba38d061bf96","observation_id":"fc7ca5e1-fc27-4081-b86f-cbd61835be47","resolution":{"observed_at":"2026-08-15T20:50:32.431570Z","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":"2026-08-15T20:50:32.436227Z","title":"Bootstrap your own latent-a new approach to self-supervised learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.436227Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:a4a7659a58f24e20730fb5a511f66b19b1ba1d25c467b19b00f61e8504c17657","observation_id":"0ec3d483-4528-4b40-88c6-70e20e8c26e2","resolution":{"observed_at":"2026-08-15T20:50:32.436227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-15T12:33:55.451951Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-15T20:50:32.441682Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.441682Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:d5fea31c27275074d36cec01bf1064b32ee454ab3f61d02fcc3d5081509bbef4","observation_id":"fa4bc89a-0884-481e-93b2-3867bf232598","resolution":{"observed_at":"2026-08-15T20:50:32.441682Z","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":"2026-08-15T20:50:33.555943Z","title":"To- wards lossless dataset distillation via difficulty-aligned trajectory matching","venue":null,"work_id":"602b034d-3d96-453a-b4c1-5587f1417a22","year":2024},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.446560Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:eea5b8d534cccfd7d5819fe5c7b1842c79cb5dae501c85429a075a682726aad1","observation_id":"ed595c9a-71af-4173-a71c-e80e41e88af1","resolution":{"observed_at":"2026-08-15T20:50:33.561286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.539341Z","title":"Clip and complementary methods","venue":null,"work_id":"c002f92b-abbf-435c-8459-0faab89ee2c7","year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.451647Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:e00b2d9e61678d46371c6ea163425fce7194af1c4e47809ba27e88718f299b36","observation_id":"60299f54-7b49-4f07-acd2-65b92795bc1f","resolution":{"observed_at":"2026-08-15T20:50:33.544570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.456452Z","title":"Momentum contrast for unsupervised visual representation learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.456452Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:ef6952f9e8cc2d3ad5929fca7c29d8bbe0ff437d87e874186952e3a848dc071f","observation_id":"d279a424-5265-47b0-bc4d-0fade30ff693","resolution":{"observed_at":"2026-08-15T20:50:32.456452Z","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":"2026-08-15T20:50:33.511940Z","title":"Deep residual learning for im- age recognition","venue":null,"work_id":"3562c314-73f6-4062-b11f-f5fcc6ecec44","year":2016},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.461574Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:938c7f2cf78bcec76c096deb400716b0f2e9995d4cd843458bf56b7e5d17c111","observation_id":"471dae49-be9c-4d60-9d01-058e44a8856f","resolution":{"observed_at":"2026-08-15T20:50:33.516888Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.495874Z","title":"Knowledge adaptation: Teaching to adapt","venue":null,"work_id":"e7318123-e0b0-4ff7-8099-0621f4e6c27c","year":2020},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.466233Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:f3eb01a32b95ccfaa1df5e190e2600274afa13b6f3217e3794f9ff907265ec64","observation_id":"48a323c5-b6a4-4a58-93f5-37a136613d66","resolution":{"observed_at":"2026-08-15T20:50:33.500894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1712.00409","last_updated":"2017-12-01T17:13:14Z","snapshot_observed_at":"2026-08-14T02:46:56.838057Z","submitted_at":"2017-12-01T17:13:14Z","title":"Deep Learning Scaling is Predictable, Empirically","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.00409","snapshot_observed_at":"2026-08-15T20:50:32.471143Z","title":"Deep learning scaling is predictable, empirically","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.471143Z"},"links":{"cited_paper":"/paper/1712.00409","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:5695e2052d413e8272b7d8b2d26e0b2b9d46609efbc470ed1e0d656eafa215f7","observation_id":"bc362be3-2c1d-4261-818e-076d4d1052ee","resolution":{"observed_at":"2026-08-15T20:50:32.471143Z","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":"2026-08-15T20:50:32.476140Z","title":"Distilling the knowledge in a neural network","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.476140Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:cb53f27a5c93981b890d0b6223ae62ff83e735636fb4d3a1a545d7309da35201","observation_id":"c4ebba1f-1dee-4848-adc7-737ce8bf9626","resolution":{"observed_at":"2026-08-15T20:50:32.476140Z","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":"2026-08-15T20:50:32.480664Z","title":"Densely connected convolutional networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.480664Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:89e2ec9e49cf5c8a32ade8dc9f4229f28fb00ab3b2f822fc74e694c566f0b56b","observation_id":"477a86c3-3b38-40c8-90a2-33cf8e408838","resolution":{"observed_at":"2026-08-15T20:50:32.480664Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-15T20:50:32.485334Z","title":"Scaling laws for neural language models","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.485334Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:f94cdd13f86e7a7d473aee01d1e8867c80f62557e9965c6d2a81191810706b57","observation_id":"885d8c1a-4b59-4361-9a60-749f6556dbbc","resolution":{"observed_at":"2026-08-15T20:50:32.485334Z","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":"2026-08-15T20:50:32.490229Z","title":"Supervised contrastive learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.490229Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:5379fb4bea4e6f250001d761960d0eca9992f442be936beca5927b77a6bc85af","observation_id":"c0b73dd0-59e7-4488-8f20-15fc62d2a6c9","resolution":{"observed_at":"2026-08-15T20:50:32.490229Z","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":"2026-08-15T20:50:32.494751Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.494751Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:904041b9e78757781d77ceba59fb3ec5de6dd265a846cb6f29fcfaec87b55359","observation_id":"e55e2dac-d8df-4f53-bc5d-af971cbe6dda","resolution":{"observed_at":"2026-08-15T20:50:32.494751Z","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":"2026-08-15T20:50:32.499411Z","title":"Tiny imagenet visual recognition challenge","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.499411Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:b96d01a5994532fd708c467427d0cf8f91c27f700c9a0aae309ebbf116beb677","observation_id":"c0ea027b-919e-44fc-960c-692714c800bb","resolution":{"observed_at":"2026-08-15T20:50:32.499411Z","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":"2026-08-15T20:50:33.427346Z","title":"A survey on text classification: From traditional to deep learning","venue":null,"work_id":"3497c020-7376-41e1-8810-a322f89b83ed","year":2022},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.503977Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:a1f74928b5103384e703438746f844897d6696ef5d5e95b6c426780e7bdb72b4","observation_id":"e8efec1f-10c5-4d9d-907b-2a18c57abbdb","resolution":{"observed_at":"2026-08-15T20:50:33.432866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.508346Z","title":"Image segmentation using deep learning: A survey","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.508346Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:ebf0e70360008d252b92136f1b81150747cfb504515302a3fecaadb953a9484c","observation_id":"14b24bbf-63d8-420b-9f21-fcd223677268","resolution":{"observed_at":"2026-08-15T20:50:32.508346Z","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":"2026-08-15T20:50:32.513116Z","title":"Deep learning on a data diet: Finding important examples early in training","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.513116Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:8e02f59dc0dc7a0368cf8eaf88732b1e10083a0e88343faff360b37146b54f8c","observation_id":"5c363c79-8e0c-46ce-9d00-28437fc15e39","resolution":{"observed_at":"2026-08-15T20:50:32.513116Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.04621","last_updated":"2017-12-13T06:41:00Z","snapshot_observed_at":"2026-08-17T03:49:15.757431Z","submitted_at":"2017-12-13T06:41:00Z","title":"The Effectiveness of Data Augmentation in Image Classification using Deep Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.04621","snapshot_observed_at":"2026-08-15T20:50:32.517740Z","title":"The effectiveness of data augmentation in image classification using deep learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.517740Z"},"links":{"cited_paper":"/paper/1712.04621","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:44ecde9801d52f32bbf97e5258a5dc628f3974d6f820074f1567aa1d0c2c5cc0","observation_id":"5fdf8e5a-78ce-46dc-a59f-d65acf0aca60","resolution":{"observed_at":"2026-08-15T20:50:32.517740Z","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":"2026-08-15T20:50:32.522614Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.522614Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:98cd30e357a8a4887c16db5ed70f48c6dc4cbf67dacbc995d1b933565330bc70","observation_id":"dbf4e0a7-4eae-464e-b788-d6fac9b36e02","resolution":{"observed_at":"2026-08-15T20:50:32.522614Z","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":"2026-08-15T20:50:33.378850Z","title":"Data efficient learning of molecular slow modes from nonequi- librium metadynamics","venue":null,"work_id":"2e1ed2b9-9c92-4126-96ff-4a763c0128ff","year":2025},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.527178Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:07fa9441c68d90002ecc0bf25a6211087a9a7c64d13314c1c24c138438b46c7a","observation_id":"0f1f3e6e-da3f-402b-9a6d-7de64d7dbd41","resolution":{"observed_at":"2026-08-15T20:50:33.383841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.363228Z","title":"Deep clustering: A comprehensive survey","venue":null,"work_id":"7bb8ef3a-f28e-4c14-8004-c41796380162","year":2024},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.532759Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:d4cc9196b92291de5c017865bbb771e67a2dd95f11613c1976f985effca86271","observation_id":"2539b64a-3769-4a45-971b-32b125960912","resolution":{"observed_at":"2026-08-15T20:50:33.368170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.537497Z","title":"Mobilenetv2: Inverted residuals and linear bottlenecks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.537497Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:9f8a027869ff4a301e5272c27fb99975adf7b6802edf28f47738ff2d9bd975cd","observation_id":"12fbbf47-6f93-4c9f-ad52-44951f6811b0","resolution":{"observed_at":"2026-08-15T20:50:32.537497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.01108","last_updated":"2020-03-01T02:57:50Z","snapshot_observed_at":"2026-08-07T19:07:36.327251Z","submitted_at":"2019-10-02T17:56:28Z","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.01108","snapshot_observed_at":"2026-08-15T20:50:32.542215Z","title":"Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.542215Z"},"links":{"cited_paper":"/paper/1910.01108","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:b4d49aa56d7e80a61a82c0226fa0ad7f2c782adb398b7e18eaafd5061c03cf20","observation_id":"6efae488-b391-4265-ae20-489bfbecd0be","resolution":{"observed_at":"2026-08-15T20:50:32.542215Z","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":"2026-08-15T20:50:33.336124Z","title":"A survey on image data augmentation for deep learning","venue":null,"work_id":"0adb5d4b-0b8c-43ba-9975-71953696753a","year":2019},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.546908Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:e8dbef84ef5ee5d0a864773ac361ca3273bd036284bc4135c0e33f51a875e3f3","observation_id":"7e15430b-1780-4a56-a1b9-d76522afec50","resolution":{"observed_at":"2026-08-15T20:50:33.341466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.319524Z","title":"Beyond neu- ral scaling laws: beating power law scaling via data pruning","venue":null,"work_id":"2d00db21-4e0c-463b-ab7d-529a4c001edc","year":2022},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.551521Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:ed253510630a6861934e87f55248b444604bc52be4df54060db7aa78d61979ac","observation_id":"64d05157-4a98-4041-8202-33488d5c6514","resolution":{"observed_at":"2026-08-15T20:50:33.325054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14669","last_updated":"2024-11-01T09:56:53Z","snapshot_observed_at":"2026-08-16T13:50:09.198209Z","submitted_at":"2024-05-23T15:06:02Z","title":"Efficiency for Free: Ideal Data Are Transportable Representations","version":2},"cited_work":{"arxiv_id":"2405.14669","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.14669","snapshot_observed_at":"2026-08-15T20:50:32.800221Z","title":"Efficiency for Free: Ideal Data Are Transportable Representations","venue":"cs.LG","work_id":"d2425c3d-d691-491c-9f89-90663138a0b8","year":2024},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.555918Z"},"links":{"cited_paper":"/paper/2405.14669","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:e3044d515f730175d722d7f9bed5a173616eacfed936254e35277e29da43e972","observation_id":"9ee67909-a833-4e30-885a-e6d42b86f222","resolution":{"observed_at":"2026-08-15T20:50:32.805558Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.303322Z","title":"On the diversity and realism of distilled dataset: An efficient dataset distillation paradigm","venue":null,"work_id":"4690edcc-9651-4a03-9a41-d9ab31630007","year":2024},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.560837Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:5253a5ebeaf6f8c0f9bf2ad89f17127fdb064e98ec981745f63fccfd57093909","observation_id":"3f911e52-bfb5-463c-b1a3-ce0bda09c8eb","resolution":{"observed_at":"2026-08-15T20:50:33.308342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.565282Z","title":"Efficientnet: Rethinking model scaling for convolutional neural networks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.565282Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:aa0de4e5b252411fb6c4eae462e012a0742ba413d9d9d20a3256e9725d65508a","observation_id":"54fa81f7-1c0a-4ab2-8e66-c04da15c4955","resolution":{"observed_at":"2026-08-15T20:50:32.565282Z","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":"2026-08-15T20:50:33.276251Z","title":"Cafe: Learning to condense dataset by aligning features","venue":null,"work_id":"1bf97038-3dc0-4d1f-9f20-34f942cc953f","year":2022},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.570651Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:d6d845db719e1d08949c3918777edc64f60231bf2a5f4dfb4642c374bbbeeb9f","observation_id":"3da652a7-af25-420a-99f8-ee92cb770706","resolution":{"observed_at":"2026-08-15T20:50:33.281532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.07114","last_updated":"2020-07-13T09:14:27Z","snapshot_observed_at":"2026-08-02T12:06:10.948848Z","submitted_at":"2020-06-12T12:18:52Z","title":"Knowledge Distillation Meets Self-Supervision","version":2},"cited_work":{"arxiv_id":"2006.07114","doi":null,"metadata_source":"pith","pith_arxiv_id":"2006.07114","snapshot_observed_at":"2026-08-15T20:50:32.775393Z","title":"Knowledge Distillation Meets Self-Supervision","venue":"cs.CV","work_id":"698d1870-4b62-4780-975c-d6992f1b228f","year":2020},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.576312Z"},"links":{"cited_paper":"/paper/2006.07114","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:f15ddf96c4de259975df41b19abe1fda9c2507ab089682e7ca08ac70ebf88a79","observation_id":"13c24f4a-3444-42f5-a691-5939cd16671d","resolution":{"observed_at":"2026-08-15T20:50:32.782883Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.260311Z","title":"A gift from knowledge distillation: Fast optimization, network minimization and transfer learning","venue":null,"work_id":"80e65a44-f79c-489f-91b6-6228a2118fd5","year":2017},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.581294Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:7016fa6e7c6a1a793adde76625a9c101685050f33a79eb29890b5ce6f41a7b35","observation_id":"95ef7610-fde2-40eb-8d78-2c3946d41dc3","resolution":{"observed_at":"2026-08-15T20:50:33.265516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13092","last_updated":"2024-02-11T20:34:51Z","snapshot_observed_at":"2026-08-16T15:21:51.186974Z","submitted_at":"2023-06-22T17:59:58Z","title":"Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.13092","snapshot_observed_at":"2026-08-15T20:50:32.585801Z","title":"Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.585801Z"},"links":{"cited_paper":"/paper/2306.13092","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:1bed5bec22600cd42198d49019c4a971d6b23c42dbc5dad2e964a451833da040","observation_id":"025cd46b-a911-4593-abbd-17ae28e4abd7","resolution":{"observed_at":"2026-08-15T20:50:32.585801Z","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":"2026-08-15T20:50:33.244918Z","title":"Cutmix: Regularization strategy to train strong classifiers with localizable features","venue":null,"work_id":"8f8b39f2-fc4d-4189-a30b-94fd1b8d01ed","year":2019},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.590732Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:1cadf2f6b2f34f482cc3c932db13e42336847a5af2f9b27220d2b6d191d0539b","observation_id":"bf89ba15-6088-4511-8bf9-abfef1038b3c","resolution":{"observed_at":"2026-08-15T20:50:33.249842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.595144Z","title":"Barlow twins: Self- supervised learning via redundancy reduction","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.595144Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:321c55e4776565b978a668117d21602167beef1a42c2e67eb44c42f4c2af2443","observation_id":"3b2036f6-36b1-4a1f-948e-9a4b8d2d93a3","resolution":{"observed_at":"2026-08-15T20:50:32.595144Z","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":"2026-08-15T20:50:33.218637Z","title":"Network representation learning: A survey","venue":null,"work_id":"a6e4d69f-40d9-4329-888d-9bd64ea11d6c","year":2018},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.599745Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:380d53ade52d736f36188c5cf2da923da99c4e6c8c5db37e63ca8f36ad054dc0","observation_id":"74943854-ba0b-4b8e-8ee6-b88d57ed5ce0","resolution":{"observed_at":"2026-08-15T20:50:33.223782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.202188Z","title":"Mixup: Beyond empirical risk minimization","venue":null,"work_id":"a8f1ae90-0fd9-4912-ae68-232fe3bcaa60","year":2018},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.604400Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:5a6560661946fb7dcef169e926e4589bb66d065ff06386ef38eaf910e30fd2ba","observation_id":"30aa4347-bcea-4884-b43c-3b90d3f0d446","resolution":{"observed_at":"2026-08-15T20:50:33.207703Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.608983Z","title":"Dataset condensation with distribution matching","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.608983Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:66da920ff8990d72800af7adbbb801256e9bac8a73468457dd1c5bbe9c247ebf","observation_id":"afccdc3a-6a35-444f-8d4a-f8e2a35b87cf","resolution":{"observed_at":"2026-08-15T20:50:32.608983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05929","last_updated":"2021-03-08T13:31:22Z","snapshot_observed_at":"2026-08-09T10:26:02.821053Z","submitted_at":"2020-06-10T16:30:52Z","title":"Dataset Condensation with Gradient Matching","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.05929","snapshot_observed_at":"2026-08-15T20:50:32.614054Z","title":"Dataset condensation with gradient matching","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.614054Z"},"links":{"cited_paper":"/paper/2006.05929","citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:0854ee6b0225062d216f941b70c7d07c25c308dcbc557c351e41b730638ea5f2","observation_id":"37a96e0a-d4ec-498c-8354-78d59661f86a","resolution":{"observed_at":"2026-08-15T20:50:32.614054Z","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":"2026-08-15T20:50:32.618781Z","title":"Decoupled knowledge distillation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.618781Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:6951191f80853f6ead564adfd933283fb53d4ab0979273412d5a43ca4f09653a","observation_id":"b71e3333-0849-4a32-bd5d-ea0f0f49186c","resolution":{"observed_at":"2026-08-15T20:50:32.618781Z","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":"2026-08-15T20:50:33.167076Z","title":"Data-efficient learning with active label cleaning and dynamic curriculum","venue":null,"work_id":"d6a8f42d-527d-4c44-8ead-f432df0c4c37","year":2023},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.623326Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:930db9705996c95168db4ff5b183229bc79ebaf4be55f84616dd5dfab6d65221","observation_id":"9bd09116-6ce5-437b-858b-14b913b715ea","resolution":{"observed_at":"2026-08-15T20:50:33.171994Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.152159Z","title":"Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper","venue":null,"work_id":"69d23212-93ec-4436-b6c5-13dc1d13ae12","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.629128Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:c39eba0439f14974d7f99da356a9f4ed79fc413a2ad24fd0e8f1bd20d29b049a","observation_id":"1a0a1d6a-02ed-4a54-8d7d-56ef9645951f","resolution":{"observed_at":"2026-08-15T20:50:33.157034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.136370Z","title":"Limitations","venue":null,"work_id":"83f98a01-389a-4466-a994-712d415d3c69","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.633962Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:d07bb38e0a3df84cd8e2dd64d1c020b3d073595fefd187ceb9122fdd01814bc7","observation_id":"57418720-6037-4a2a-96a0-ec83753af824","resolution":{"observed_at":"2026-08-15T20:50:33.142245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.120716Z","title":"Guidelines: • The answer NA means that the paper does not include theoretical results","venue":null,"work_id":"ca0894dc-c137-4dd2-b5e3-57864e2f8118","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.638947Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:a54a4958ed986c7b31430aa70a0a316ac5024da830861a93a948519ff70736f7","observation_id":"edeee564-a86b-43fe-8c80-5fcefdbb50a8","resolution":{"observed_at":"2026-08-15T20:50:33.126027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.105375Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"29803b76-cfa8-4c75-b2c8-23a58f112919","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.643607Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:0c6c005e1db22f32307c90676e518dcb34e8e380880d5fe552b172728a23e506","observation_id":"1b5b25be-8b3d-4d5d-9af9-9946bd5ab1c5","resolution":{"observed_at":"2026-08-15T20:50:33.110299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.089123Z","title":"Guidelines: • The answer NA means that paper does not include experiments requiring code","venue":null,"work_id":"607da139-cdc0-4f52-b9f8-9a05a3aa5cfe","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.648573Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:9da072d87171517eea63bfa336916b7ee939b3164bec6a48fa23f23fa2c3bf1b","observation_id":"8b3c6332-81f5-40dd-b7cd-7b80507d1c25","resolution":{"observed_at":"2026-08-15T20:50:33.094880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.073260Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"0d1e91ce-2742-40f7-8ad5-7e50c9152263","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.654738Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:9b963f2670c0afb2dfddac9f7f53339724559794f6043a9ac089045b28f606a8","observation_id":"ecd2a3ef-3b8e-4d4a-8fe1-bb6319fc63e1","resolution":{"observed_at":"2026-08-15T20:50:33.078288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.058018Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"c95cdcbd-f8e6-421f-9120-4b3856a919a6","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.659786Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:ecf494097827cb0d5955071f269f848a1c1b6c55adf4d4ce024a3c6e4f2f21c0","observation_id":"6895b128-f5ea-4de2-bf11-6b2556367532","resolution":{"observed_at":"2026-08-15T20:50:33.062942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.039922Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"1bca36ff-2deb-4a27-aee0-c5bc3e944304","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.664810Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:b433e6430b1cd9669f505a63675abe8b71e521fcdbe3c5fa2ca692b1ad476237","observation_id":"74f39faa-0d49-45a1-90f7-04692672558e","resolution":{"observed_at":"2026-08-15T20:50:33.045517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.023447Z","title":"Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics","venue":null,"work_id":"375e9d17-2924-40b3-96b6-0da167cddbd7","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.669378Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:05b17d79f2727ede1ce5ebbf184587e0411d5ee16154b8978010ecbeca77a6ec","observation_id":"0290223e-c8c7-415f-b81a-9cf541e443d3","resolution":{"observed_at":"2026-08-15T20:50:33.028467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:33.007787Z","title":"Guidelines: • The answer NA means that there is no societal impact of the work performed","venue":null,"work_id":"ba914169-82aa-43e7-aae3-ade9c3801509","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.674107Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:faf2887fe934a4820e74b4e7682506af0ab93eac6630245504ea10d336b96485","observation_id":"52ab232a-9a12-4f8f-8741-98a15b4c5402","resolution":{"observed_at":"2026-08-15T20:50:33.012959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.991543Z","title":"• The answer NA means that the paper poses no such risks","venue":null,"work_id":"b52b6f2b-08d9-444c-a748-11ea9db616f7","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.678759Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:bd2449e558e5b3f606d9ca200c3f18797a16ae66e80e83f67cabdf130addf61d","observation_id":"52b2ba1d-0edd-47ff-b1c2-9d5ee7205de2","resolution":{"observed_at":"2026-08-15T20:50:32.996405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.974699Z","title":"Guidelines: • The answer NA means that the paper does not use existing assets","venue":null,"work_id":"edd8003d-470c-4c5c-bf17-414d16908652","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.683394Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:f1b4bddb000d98a5dd07141741ec147b0e9fe02f7630008e6058ad78612cc3d9","observation_id":"84e8eba8-2533-4b7f-b441-a066093b5242","resolution":{"observed_at":"2026-08-15T20:50:32.980788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.958419Z","title":"Guidelines: • The answer NA means that the paper does not release new assets","venue":null,"work_id":"44872d60-9d4b-4dc2-9e93-10ca6f0087be","year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.688524Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:1d178b074cbe0df32040a9a48e6e36631003b2c12c5f5f67f91f81c16ca6c1d7","observation_id":"bab6aec4-02ba-478b-a1b1-dcc37e4e1803","resolution":{"observed_at":"2026-08-15T20:50:32.963721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T20:50:32.694065Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.694065Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:ae2f3a87581641acdc1cb585b18244c0ff21b62e6f32573e49cc381313306d23","observation_id":"05e40eaf-c514-46ca-b4be-62900055a553","resolution":{"observed_at":"2026-08-15T20:50:32.694065Z","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":"2026-08-15T20:50:32.699690Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.699690Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:a57b0763229d42b160bea2c20ec2ea81eee2e28803035c74866938c35b65fc17","observation_id":"b03837dc-80b5-4e43-bde4-e1b4c3448ba6","resolution":{"observed_at":"2026-08-15T20:50:32.699690Z","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":"2026-08-15T20:50:32.923118Z","title":"Answer: [NA] 29 Justification: LLM is used only for editing","venue":null,"work_id":"83606502-c7e4-460d-9f73-8816a65c3e4e","year":2025},"citing_paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-15T20:50:32.704284Z"},"links":{"citing_paper":"/paper/2506.01987"},"observation_digest":"sha256:141553f938fa03bc6c48063e6151eb7b0e308edf29ead3ca2bab7cbc85066729","observation_id":"1800a3e6-8015-41fe-9863-4c32ee3c2ca1","resolution":{"observed_at":"2026-08-15T20:50:32.928195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.01987","last_updated":"2025-05-17T08:27:19Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T20:43:09.925193Z","submitted_at":"2025-05-17T08:27:19Z","title":"Equally Critical: Samples, Targets, and Their Mappings in Datasets"},"reference_resolution":{"displayed":70,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":2,"verified_fuzzy":34},"total_outbound_references":70},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2506.01987."}