{"as_of":"2026-08-13T13:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:126e7b17570a7b61321b17a24b2d53ed4536d6a348b689359fb794ac7a574aac","coverage":[{"denominator":87,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":87,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-25T04:30:04.849603Z","state":"measured"},{"denominator":87,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":87,"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/2605.23482/citation-record","integrity":"/paper/2605.23482/integrity","json":"/paper/2605.23482/citation-record.json","paper":"/paper/2605.23482"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":"2303.08774","doi":"10.1002/tea.20265","metadata_source":"pith","pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GPT-4 Technical Report","venue":"cs.CL","work_id":"b928e041-6991-4c08-8c81-0359e4097c7b","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:c339d51decf656da6360f59459261e3582a71e03ebec62f30331e5ffb5dbc581","observation_id":"bb1b1edf-771d-4e10-9d64-8b882b47eaea","resolution":{"observed_at":"2026-05-25T04:30:19.681939Z","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":"2026-06-05T21:23:00.469572Z","title":"Contextual diversity for active learning","venue":null,"work_id":"d393888b-f331-44ac-a92d-4a1d6924e22b","year":null},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:2e991ef390c9e0a24b35b7730bb44afff51f31784cbf9d4ed4fe2be51385376f","observation_id":"24855f7c-0f2d-4621-bb44-c13c2c129d84","resolution":{"observed_at":"2026-05-25T04:30:20.771076Z","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":"2026-06-05T21:23:00.469572Z","title":"Flamingo: a visual language model for few-shot learning.Advances in neural information processing systems, 35:23716–23736","venue":null,"work_id":"fda65d69-c33a-43a8-b2b6-7d817a1c10f5","year":null},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:4fef33cc3051fb0bee79d7904c3abab16e5f21bf07b2087976abed5ec5e00fa0","observation_id":"fdec9356-13e7-4a3a-9b1b-d447c68fdc80","resolution":{"observed_at":"2026-05-25T04:30:20.868943Z","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":"2309.16609","last_updated":"2023-09-28T17:07:49Z","snapshot_observed_at":"2026-08-09T21:25:20.369782Z","submitted_at":"2023-09-28T17:07:49Z","title":"Qwen Technical Report","version":1},"cited_work":{"arxiv_id":"2309.16609","doi":"10.48550/arxiv.2309.16609","metadata_source":"pith","pith_arxiv_id":"2309.16609","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen Technical Report","venue":"cs.CL","work_id":"bb1fd52f-6b2f-437c-9516-37bdf6eb9be8","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2309.16609","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:b59caa99883c009175ef67c9e20ebdc7c0dd29dffbc2f79f13561d0240749a33","observation_id":"6f09058d-3141-403b-b3bc-6ae49b86627b","resolution":{"observed_at":"2026-05-25T04:30:19.731300Z","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":"2026-07-15T23:50:15.620681+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-15T23:50:15.620681+00:00","source":"openalex_status_cache"},{"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":"2026-06-05T21:23:00.469572Z","title":"Dataset distillation as data compression: A rate-utility perspective","venue":null,"work_id":"86c41218-dd77-4bf5-a7af-2d8b72c6b167","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:90987a0972a5fb77dfa12db0aecc6131e2c839a30011ddb3a78440e982977692","observation_id":"e83b96d1-eadb-45a9-9695-910289142e52","resolution":{"observed_at":"2026-05-25T04:30:20.994187Z","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":"2026-06-05T21:23:00.469572Z","title":"High-performance large-scale image recognition without normalization","venue":null,"work_id":"b5e52590-2854-4238-b350-bae0e3156709","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:0c5baad06da480797de71c626eae56826f9bc89f12f2e7619d74849711c2bd4c","observation_id":"3827a8bd-7bb6-4d2e-b4fe-86bd0c27673d","resolution":{"observed_at":"2026-05-25T04:30:20.774694Z","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":"2026-06-05T21:23:00.469572Z","title":"Coyo-700m: Image-text pair dataset","venue":null,"work_id":"e9ce3d7e-6a1a-44c2-a476-267009c3ca23","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:d235ecb9b025fbea3a166bee796d62e8844278108fa93818ce1d9e906dff3640","observation_id":"28e7b280-f346-42a2-bc39-558c5872ea34","resolution":{"observed_at":"2026-05-25T04:30:20.907792Z","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":"2026-06-05T21:23:00.469572Z","title":"Dataset distillation by matching training trajectories","venue":null,"work_id":"19916c51-cf3d-4740-9be5-3d0bd6dd408c","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:5fe966255cdd7176123fa94f769f040c6ce17a4a60e41acf6a5f6597e4b511dc","observation_id":"a756559d-032d-4e95-bc5b-e611ef00e466","resolution":{"observed_at":"2026-05-25T04:30:20.984179Z","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":"2026-06-05T21:23:00.469572Z","title":"Generalizing dataset distillation via deep generative prior","venue":null,"work_id":"2ee18b75-40b4-48cc-bde1-05cae93e06b4","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:e398c5612735070b81b2609af30880ec18adc6ec8d1a60a3a787d03c6ce79420","observation_id":"170551af-4719-4ac1-8f16-805828428e36","resolution":{"observed_at":"2026-05-25T04:30:21.053997Z","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":"1906.11829","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1906.11829","snapshot_observed_at":"2026-07-03T19:28:52.634253Z","title":"Selection via proxy: Efficient data se- lection for deep learning.arXiv preprint arXiv:1906.11829","venue":null,"work_id":"12daad0e-7402-46c0-bc01-a0fd7dfbadf7","year":1906},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/1906.11829","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:eaa64906bd883408f9c3815b53d5b0e2eff03cbe22cec23df9c91af1e4ab10b9","observation_id":"9073564d-fcae-437a-a2a4-0b587573a13c","resolution":{"observed_at":"2026-05-25T04:30:19.700525Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Dc- bench: Dataset condensation benchmark.Advances in Neural Information Processing Systems, 35:810–822","venue":null,"work_id":"905b175c-4c15-45a5-ad4b-9f8633b33949","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:82a0a4aa172b14a4499af63b615b1a306dba2961a56ccc9f630b163c339574a1","observation_id":"5d5151f7-c8d9-49d3-a9ae-26f6ea97b360","resolution":{"observed_at":"2026-05-25T04:30:20.829465Z","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":"2026-06-05T21:23:00.469572Z","title":"Scaling up dataset distillation to imagenet-1k with constant memory","venue":null,"work_id":"fc862bf9-49e4-4a17-8a8b-66d6c62c9ec2","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:42b659a1e8d94152fff567030bf07a66e45bd824bbead39f4ae2d9658d2b2ec2","observation_id":"61819af8-b812-4183-86f9-e80cc0d92af3","resolution":{"observed_at":"2026-05-25T04:30:20.894290Z","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":"2026-06-05T21:23:00.469572Z","title":"Optical: Leveraging optimal transport for con- tribution allocation in dataset distillation","venue":null,"work_id":"145ad544-b9c7-4d52-a25e-5494a509c76b","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:560145134ba1c459e0531f94eb3141dee2217440ccd29647b5b2b1242ad97cd6","observation_id":"15b4ce2c-e1fc-4f17-84ea-3b9cfb9e781d","resolution":{"observed_at":"2026-05-25T04:30:20.850485Z","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":"2026-06-05T21:23:00.469572Z","title":"Ex- ploiting inter-sample and inter-feature relations in dataset distillation","venue":null,"work_id":"4c593f8f-14fa-4768-b0dd-1fa33b6e5248","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:5fe59f8d9e005bf25329233beb46aff4871ffe558d0a923c68fb33ef4e4b1128","observation_id":"b164a5b1-1ea2-411d-925b-0df9d27e957b","resolution":{"observed_at":"2026-05-25T04:30:20.810369Z","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":"2026-06-05T21:23:00.469572Z","title":"Remember the past: Dis- tilling datasets into addressable memories for neural networks","venue":null,"work_id":"17592352-3420-4acd-835e-2703f7ebad9c","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:eb4813804d9859f1e0ebd93111cc6f968e5bb5e15f8e06e410c72d1a389eb646","observation_id":"e9ccbba6-591c-47cb-b69b-039dba0f19d3","resolution":{"observed_at":"2026-05-25T04:30:20.839154Z","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":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-07-30T09:12:38.100527Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":"1810.04805","doi":"10.1111/jofi.12885","metadata_source":"pith","pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","venue":"cs.CL","work_id":"ed240a10-5b19-406c-baa5-30803f465785","year":2018},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:6ebe4ebc38bc5e60bcb798b2d4db793381371d8b342a64ebec711dec8957d1fb","observation_id":"ebb26c08-d39a-4037-9d04-f0619b93f7f8","resolution":{"observed_at":"2026-05-25T04:30:19.663370Z","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":"2026-06-05T21:23:00.469572Z","title":"Minimizing the accumulated trajectory error to improve dataset distillation","venue":null,"work_id":"a3c793ec-d102-4cbd-b6c5-7a889c416873","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:9e2ba45ace4b880651e7c2adfd8b9eec31635d23b8cfce5b007514aebbc4b618","observation_id":"6f256287-1151-4322-93e2-63a89f6ff4ee","resolution":{"observed_at":"2026-05-25T04:30:20.764466Z","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":"1802.09841","last_updated":"2018-02-27T12:02:33Z","snapshot_observed_at":"2026-07-06T06:25:35.999872Z","submitted_at":"2018-02-27T12:02:33Z","title":"Adversarial Active Learning for Deep Networks: a Margin Based Approach","version":1},"cited_work":{"arxiv_id":"1802.09841","doi":null,"metadata_source":"pith","pith_arxiv_id":"1802.09841","snapshot_observed_at":"2026-07-08T21:35:37.621008Z","title":"Adversarial Active Learning for Deep Networks: a Margin Based Approach","venue":"cs.LG","work_id":"2549e0f4-543f-4276-82dd-cfaa56df38b3","year":2018},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/1802.09841","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:ea3b674d514cc9bf19fab4566ffc8fe4dddd8c9a6b6d465a7d6523f23a7567ea","observation_id":"9f46be29-507b-425f-8def-73e04600d29e","resolution":{"observed_at":"2026-05-25T04:30:19.726897Z","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":"2026-06-05T21:23:00.469572Z","title":"Springer Science & Business Media","venue":null,"work_id":"9f076855-36fe-480b-8ed3-52a2ddc37afc","year":2009},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:ab43a7ba1d8f116d57811b8980f0806c63fac359db63b8cf1c56e7f508b52b2f","observation_id":"b2f060f8-4bbb-4c27-918f-cd2a17dc02a5","resolution":{"observed_at":"2026-05-25T04:30:20.767591Z","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":"2026-06-05T21:23:00.469572Z","title":"Deepcore: A comprehensive library for coreset selection in deep learning","venue":null,"work_id":"826b5f6d-ba65-4cd7-850c-271229c28f3b","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:70f5e03257099c960b5b0d3809a58b89e54945a21561f7bb6ba607626846d080","observation_id":"6fe1e8f3-e306-4afd-8ebb-8cd4efcd3c7e","resolution":{"observed_at":"2026-05-25T04:30:20.844251Z","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":"2026-06-05T21:23:00.469572Z","title":"Algorithm as 136: A k-means clustering algorithm.Journal of the royal statistical society","venue":null,"work_id":"aff8154d-5a26-4fc8-8c57-9f38704fbd07","year":1979},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:8de4d79ba6858b41e52ab77edd39f87bf9cc9eb7b59eccec9ceb04ae7f883b20","observation_id":"9ae3d7be-dbc6-4f31-93fb-f205e838a456","resolution":{"observed_at":"2026-05-25T04:30:21.057256Z","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":"2310.14019","last_updated":"2023-10-21T14:05:58Z","snapshot_observed_at":"2026-08-13T05:44:06.569019Z","submitted_at":"2023-10-21T14:05:58Z","title":"You Only Condense Once: Two Rules for Pruning Condensed Datasets","version":1},"cited_work":{"arxiv_id":"2310.14019","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.14019","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"You only condense once: Two rules for pruning condensed datasets","venue":null,"work_id":"282ca02b-024b-4620-88f0-0d905313465b","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2310.14019","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:c9155830993829535b603d4e2812a882d06a07cb765befd1a96723c53e102aa2","observation_id":"a860435e-ad0f-4add-ae6c-6c96c2453322","resolution":{"observed_at":"2026-05-25T04:30:19.744140Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Fram- ing image description as a ranking task: Data, models and evaluation metrics.Journal of Artificial Intelligence Research, 47:853–899","venue":null,"work_id":"a82ae8ca-61f1-4d56-baa7-3d572d2e67a6","year":2013},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:5e2342ec98799f6cf709e435a763817cc00349689e0c7b0a5faaa9063ba0acb1","observation_id":"113f4165-8e98-41f1-a6f0-c3112d63d677","resolution":{"observed_at":"2026-05-25T04:30:21.044214Z","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":"2026-06-05T21:23:00.469572Z","title":"Submodular combinatorial information measures with applications in machine learning","venue":null,"work_id":"7b269429-4b63-4216-a11e-0f812b2397af","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:0b4455ce97d412950d484182857b8f1b99db8ec612f6c58bdf4e66675622f415","observation_id":"7cce0f53-c09e-4bfa-b978-6c2c4357635f","resolution":{"observed_at":"2026-05-25T04:30:21.047650Z","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":"2026-06-05T21:23:00.469572Z","title":"Model stock: All we need is just a few fine-tuned models","venue":null,"work_id":"cd2fce33-7e5f-4112-a292-43080fb6bce1","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:e9e95bb9a4a09c5ccac58f8cce56a8afa1ac9408e5cd7858f2641682c4c585e1","observation_id":"3fe974ca-302f-43ba-af81-a7018e430e05","resolution":{"observed_at":"2026-05-25T04:30:21.037095Z","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":"2026-06-05T21:23:00.469572Z","title":"Grad-match: Gra- dient matching based data subset selection for efficient deep model training","venue":null,"work_id":"038e8d46-f8c6-4538-a866-8b41e5413421","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:18e9f687d068220b53b86de00c8ef8347fac200ae86721fa0d5d5709a87dca37","observation_id":"3a1b678a-488d-4f85-a2b4-d55c63f4f47a","resolution":{"observed_at":"2026-05-25T04:30:21.032765Z","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":"2026-06-05T21:23:00.469572Z","title":"Glister: Generalization based data subset selection for efficient and robust learning","venue":null,"work_id":"6cbf2859-2242-42fa-a019-02217cf8c1f0","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:9416b2c49475f9c56c21b7110dcec630ea9d2aed7a8834e04cfb15e4a43d9b4d","observation_id":"511a206a-1e52-41d8-87f5-c0954cfad579","resolution":{"observed_at":"2026-05-25T04:30:21.040610Z","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":"2210.06205","last_updated":"2022-10-12T13:45:36Z","snapshot_observed_at":"2026-08-10T08:06:06.981484Z","submitted_at":"2022-10-12T13:45:36Z","title":"On Divergence Measures for Bayesian Pseudocoresets","version":1},"cited_work":{"arxiv_id":"2210.06205","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.06205","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"On divergence measures for bayesian pseudocoresets","venue":null,"work_id":"92eb9dc4-4175-43f6-b4b6-cad8eed16b67","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2210.06205","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:1d93856dda4af413372e1eb15aab8fd42bf5e1eb79fbb1fe2a649663e470367f","observation_id":"da8fd825-c2bf-463a-9a85-a2c1a73ae696","resolution":{"observed_at":"2026-05-25T04:30:19.706031Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Dataset condensation via efficient synthetic-data pa- rameterization","venue":null,"work_id":"21e1d8b0-64e8-4176-9832-9861cceca01d","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:d9cce4a8a75343c8ddbde7f85cca7addc835b057bb1b9282350e490c731f17fb","observation_id":"794c5a05-5f82-46f4-99f8-57156dc7972d","resolution":{"observed_at":"2026-05-25T04:30:21.060778Z","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":"2026-06-05T21:23:00.469572Z","title":"Computing geodesic paths on manifolds.Proceedings of the national academy of Sciences, 95(15):8431–8435","venue":null,"work_id":"ca5caa5b-a8da-4f2f-bf10-50d2c646ab1c","year":1998},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:3bb159d0eabf3423808c504c21a796c6acf172d3ffd9ad4962f0ae469500e815","observation_id":"e15c2f99-98eb-4214-a254-4ba731112f00","resolution":{"observed_at":"2026-05-25T04:30:21.015146Z","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":"2208.10494","last_updated":"2022-08-21T18:14:08Z","snapshot_observed_at":"2026-08-10T13:42:40.320402Z","submitted_at":"2022-08-21T18:14:08Z","title":"Dataset Condensation with Latent Space Knowledge Factorization and Sharing","version":1},"cited_work":{"arxiv_id":"2208.10494","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2208.10494","snapshot_observed_at":"2026-06-30T07:24:21.236605Z","title":"Dataset condensation with latent space knowledge factorization and sharing","venue":null,"work_id":"cab7769e-bf26-4006-a40c-22de6e13e4f9","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2208.10494","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:2803dd035d38e1e9d6d86ef89f221870d0eca6bf03610f75409288e197dab8f6","observation_id":"d0647da1-9871-4a70-8315-e4ad609f24ba","resolution":{"observed_at":"2026-05-25T04:30:19.668110Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"A comprehensive survey of dataset distillation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(1):17–32","venue":null,"work_id":"8d00d337-7e8e-4e28-a12f-57915996d01f","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:abe0d35733e0c179c9abbcb92cc93b408dac64504542a649474df54aaa173f22","observation_id":"d1990a5a-451a-478f-ba5c-cfa7345d7a4f","resolution":{"observed_at":"2026-05-25T04:30:21.018852Z","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":"2026-06-05T21:23:00.469572Z","title":"Diversity-enhanced distribution alignment for dataset distillation","venue":null,"work_id":"bd9f3794-fa54-4e76-9675-ca55f8ddf3f8","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:44756991ffb94b93472fd17ec33e516e8e25c45afb6512aca566c5b0744d3703","observation_id":"c01b737a-22b6-43e1-8e32-f379753c6032","resolution":{"observed_at":"2026-05-25T04:30:21.022523Z","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":"2026-06-05T21:23:00.469572Z","title":"Blip: Bootstrapping language-image pre-training for unified vision- language understanding and generation","venue":null,"work_id":"548b4cb7-70d0-47fc-8895-c449bfa80e29","year":null},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:60785b2a2954955c8b6bae2f06fcbd51d6a47140e53a8e084a17cd995ad51252","observation_id":"b41c62f6-8844-45ac-87fb-f8517954d392","resolution":{"observed_at":"2026-05-25T04:30:21.004652Z","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":"2026-06-05T21:23:00.469572Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":"304b2804-916d-4329-8579-0a286285a7b0","year":2014},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:7ec119bed4af30f64e0d756b34a1d55a2a4f35e1123e605acd75f5cfe006dbe0","observation_id":"60d75159-771e-4f7c-abcb-8a1d667a8378","resolution":{"observed_at":"2026-05-25T04:30:21.001074Z","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":"2026-06-05T21:23:00.469572Z","title":"Dataset distillation by automatic training trajectories","venue":null,"work_id":"2c4e6163-242d-4e43-b289-75cc87e819ee","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:ebe63a90cc174b925d54a35346a73b6f63e8955cdc54e3cd07094417d76102ba","observation_id":"23f8dab7-99d3-4452-a393-0c87b8e9b059","resolution":{"observed_at":"2026-05-25T04:30:21.008149Z","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":"2026-06-05T21:23:00.469572Z","title":"Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916","venue":null,"work_id":"80df3d4a-379c-485b-991a-704ad587d79c","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:e9a6230314401a5eb184129c19e626181e23b8b2b1851b600b037b2f3abe3fcf","observation_id":"b577a09f-53c6-45ab-befc-8ca49eb94157","resolution":{"observed_at":"2026-05-25T04:30:20.997983Z","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":"2026-06-05T21:23:00.469572Z","title":"Dataset distillation via the wasserstein metric","venue":null,"work_id":"801ad2b0-fe5a-43cc-9e0d-7cbe050e5b32","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:330eadaf551dd610c575627b53755a796f029866622a3320b315a3689bfb7089","observation_id":"c2cdef6e-ddbf-4479-a2e2-9393c9bb1369","resolution":{"observed_at":"2026-05-25T04:30:21.011654Z","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":"2502.05673","last_updated":"2025-07-03T14:56:22Z","snapshot_observed_at":"2026-08-09T10:27:08.020566Z","submitted_at":"2025-02-08T19:37:33Z","title":"The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions","version":3},"cited_work":{"arxiv_id":"2502.05673","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05673","snapshot_observed_at":"2026-07-03T19:28:52.641313Z","title":"The evolution of dataset distillation: Toward scalable and generalizable solutions","venue":null,"work_id":"860a67ef-7964-4c53-9334-906378d361a6","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2502.05673","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:25ea818b47edfc53b5cbf2e446ff6a3baf87593b5e1d5c183976a32eda4ee39d","observation_id":"556ca236-42b8-48aa-ba02-072fcf48a893","resolution":{"observed_at":"2026-05-25T04:30:19.693768Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Dataset distillation via factorization","venue":null,"work_id":"c8eb5915-ba88-4634-87f9-8af49b0c922b","year":null},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:facf27ceccfb1b9a995a2003b69d7617bf13e96258d6baf7b5b86a27cf63783c","observation_id":"4100d2f0-b066-4645-a8c4-88b627793e13","resolution":{"observed_at":"2026-05-25T04:30:20.991101Z","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":"2026-06-05T21:23:00.469572Z","title":"Slimmable dataset condensation","venue":null,"work_id":"73321984-8816-4559-9d92-a56194f83029","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:e6271eb103ae1cda399f9af9ee995f7f055e7124e01e2b5af752773efe45c456","observation_id":"4c383005-6579-436e-bc87-438aa58a6d67","resolution":{"observed_at":"2026-05-25T04:30:21.028963Z","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":"2302.14416","last_updated":"2023-08-30T14:22:32Z","snapshot_observed_at":"2026-08-13T12:35:30.588067Z","submitted_at":"2023-02-28T08:48:45Z","title":"DREAM: Efficient Dataset Distillation by Representative Matching","version":3},"cited_work":{"arxiv_id":"2302.14416","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.14416","snapshot_observed_at":"2026-07-02T14:07:02.379420Z","title":"Dream: Efficient dataset distillation by repre- sentative matching","venue":null,"work_id":"bd044839-4de6-489f-b703-75c0dfcc49af","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2302.14416","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:bf30670cd8a34981abb349819c90313b637b16c4ed9947fc48253f31d3ad4232","observation_id":"ff1764bd-9631-42b4-ba56-729f38c0b9fe","resolution":{"observed_at":"2026-05-25T04:30:19.774543Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Efficient dataset distillation using random feature approxima- tion","venue":null,"work_id":"c33df66a-ae7b-4729-aa2b-85b5059a04d2","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:ed4080a208428d1cf250276180228c6af4448a69f304526df180d077e98f0d74","observation_id":"6a9d4483-b1e2-4a3c-bef9-7803f71a5167","resolution":{"observed_at":"2026-05-25T04:30:20.974008Z","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":"2302.06755","last_updated":"2023-11-09T22:26:32Z","snapshot_observed_at":"2026-08-13T12:45:04.576016Z","submitted_at":"2023-02-13T23:53:16Z","title":"Dataset Distillation with Convexified Implicit Gradients","version":2},"cited_work":{"arxiv_id":"2302.06755","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.06755","snapshot_observed_at":"2026-06-30T07:24:21.199040Z","title":"Dataset distillation with convexified implicit gradients","venue":null,"work_id":"222ccbf4-f3e2-4ada-a605-f066426eb036","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2302.06755","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:88354e3a5dbf3fc7c1e73a92dfadf53b4637ce2c74258d58c0f79dd65be98bdc","observation_id":"8f4690eb-c4f3-47c5-9ad8-782e37556e1c","resolution":{"observed_at":"2026-05-25T04:30:19.799890Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Bayesian pseudocoresets","venue":null,"work_id":"36428680-b966-4517-af85-c0c2cc727623","year":null},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:d0078a9ce2ee97fb23c6f0206094664a55f216d8fcced9be8bdeaf7b15bbe2dc","observation_id":"62df5cb0-a5b1-4d65-916a-2a6e8d357cc2","resolution":{"observed_at":"2026-05-25T04:30:20.977144Z","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":"2109.03764","last_updated":"2021-09-08T16:40:18Z","snapshot_observed_at":"2026-08-06T03:32:43.504624Z","submitted_at":"2021-09-08T16:40:18Z","title":"Active Learning by Acquiring Contrastive Examples","version":1},"cited_work":{"arxiv_id":"2109.03764","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.03764","snapshot_observed_at":"2026-07-02T23:07:27.200901Z","title":"Active learning by acquiring contrastive examples","venue":null,"work_id":"7f801aa2-f94a-455c-980a-ae5f7dce9a6b","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2109.03764","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:f034c64c5cf2988b02d6dc1230c7c36e5929a3ae8b463371193cbb8ad53a4c2e","observation_id":"445fd892-b6f9-4804-ac80-abacc6a3a102","resolution":{"observed_at":"2026-05-25T04:30:19.753829Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Geomm: On geodesic perspective for multi-modal learning","venue":null,"work_id":"9c0d30be-0307-4d3b-a88b-53093f6e7fc1","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:daafa2a0c3bb12ef2db3a08592d813218482f02f300873a8fcb5d220441915fa","observation_id":"5c856a9c-7383-43a8-8e2e-5946b7c8c1d0","resolution":{"observed_at":"2026-05-25T04:30:20.971083Z","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":"2026-06-05T21:23:00.469572Z","title":"Coresets for data-efficient training of machine learning mod- els","venue":null,"work_id":"41ae1bf7-1e71-4441-a70b-5e0f5d23d576","year":2020},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:6467be4bdd10475eb1bf2ca65637cf79022b8f4379e01ce56fb356fa6f31da1b","observation_id":"c828aefe-2832-4512-8378-5aa9bcd5717a","resolution":{"observed_at":"2026-05-25T04:30:20.922222Z","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":"2011.00050","last_updated":"2021-03-22T19:15:46Z","snapshot_observed_at":"2026-08-07T21:29:51.916383Z","submitted_at":"2020-10-30T18:54:04Z","title":"Dataset Meta-Learning from Kernel Ridge-Regression","version":3},"cited_work":{"arxiv_id":"2011.00050","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2011.00050","snapshot_observed_at":"2026-07-04T03:29:29.824869Z","title":"Dataset meta-learning from kernel ridge-regression","venue":null,"work_id":"aa97142a-d368-40f3-ba32-562f9fa6f6f5","year":2011},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2011.00050","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:3f5f121af4e688f679275d3b2b467e6ea8efd5b9dc85423e9428950a5649eef5","observation_id":"94bdaa0f-5526-4db8-ab85-1f14e433eb38","resolution":{"observed_at":"2026-05-25T04:30:19.672507Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Dataset distillation with infinitely wide convolutional networks","venue":null,"work_id":"9e8b12a3-2275-4988-a6e8-62ef2a528324","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:ed7d5e443cc82c3e06272a4d23ed79aedf674da8e72bf40a4753dc3ba28dffe8","observation_id":"7eae90dd-4736-44a5-b921-602de78d0dfc","resolution":{"observed_at":"2026-05-25T04:30:20.967501Z","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":"2026-06-05T21:23:00.469572Z","title":"Deep learning on a data diet: Finding important examples early in training.Advances in neural information processing systems, 34:20596–20607","venue":null,"work_id":"cfb652e8-cf43-495b-9f54-6a5ee52cd3e7","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:1ba4cb4cba3cc629168414d819e6955961a75aca4dd55e10a9505db958e6008c","observation_id":"95d5cf52-def2-4a7e-9fae-158cc9926c4b","resolution":{"observed_at":"2026-05-25T04:30:20.980860Z","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":"2026-07-10T20:17:33.931222Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"05644b85-8aaa-4cb3-8f21-4ce50a3822a5","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:98e19e13d0615ee9b77eef75f77ee3ecb1276ba05ef6d3b7f10ebe893b019444","observation_id":"6270df56-18ab-4468-a5a5-debfbd0ea6c7","resolution":{"observed_at":"2026-05-25T04:30:20.987999Z","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":"2026-06-05T21:23:00.469572Z","title":"Datadam: Efficient dataset distillation with attention matching","venue":null,"work_id":"8f41604c-12a8-40d2-8b23-ca052e8cf3fb","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:fb512b0497c7e3b6917a4434afaf44ddecba435042a76e9eea8b79cc1dcac823","observation_id":"890e57b0-2745-42ae-bf6d-d4546744c1db","resolution":{"observed_at":"2026-05-25T04:30:20.902793Z","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":"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":"1910.01108","doi":"10.48550/arxiv.1910.01108","metadata_source":"pith","pith_arxiv_id":"1910.01108","snapshot_observed_at":"2026-07-11T02:57:46.620845Z","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","venue":"cs.CL","work_id":"756f9764-ecd6-4672-8043-b37c698c7ad2","year":2019},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/1910.01108","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:4e9a1e21954c18b5bc8309df1f953666c58054ea26e608a022d657e97cc739af","observation_id":"938621c1-2098-4aa8-bdd1-455c0b8684db","resolution":{"observed_at":"2026-05-25T04:30:19.769021Z","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":"2026-06-05T21:23:00.469572Z","title":"Laion-5b: An open large-scale dataset for training next gen- eration image-text models.Advances in Neural Information Processing Systems, 35:25278–25294","venue":null,"work_id":"b4058e8e-d262-4b88-b323-601a136d0afe","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:eb776ede8e5a8c1e4e3538b443289c35aa7c168b484acc1899f2ab375742aead","observation_id":"13953d0a-d2ae-482e-b866-d99c85c4a699","resolution":{"observed_at":"2026-05-25T04:30:20.918214Z","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":"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":"1708.00489","doi":"10.48550/arxiv.1708.00489","metadata_source":"pith","pith_arxiv_id":"1708.00489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Active Learning for Convolutional Neural Networks: A Core-Set Approach","venue":"stat.ML","work_id":"64b057c0-f8b3-4d7a-9f16-e2880f8b501c","year":2017},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/1708.00489","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:5277dd00a9f9258ac7339ff9310c57526ffca2cf9b1b9d4be4dc981aeb1f1fc5","observation_id":"31905bed-f3a4-4f3d-a85b-e32ddba19397","resolution":{"observed_at":"2026-05-25T04:30:19.790856Z","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":"2026-06-05T21:23:00.469572Z","title":"Fre- quency domain-based dataset distillation.Advances in Neural Information Processing Systems, 36:70033–70044","venue":null,"work_id":"c28e15df-24f1-4102-bef2-3f6a957739d8","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:0b2a929eba16077e74e34f5ec4bbd70f07c7f9e7a144bd47d79774125fd78f61","observation_id":"e27b41b4-f516-4e5c-879e-5ec9ae6b2a81","resolution":{"observed_at":"2026-05-25T04:30:20.912296Z","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":"2026-06-05T21:23:00.469572Z","title":"Fyi: Flip your images for dataset distillation","venue":null,"work_id":"e8dbddaf-cd37-4346-a728-b60aa024f96b","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:e0747cfa2f62e45e6497e5a709914ebf105e1ad9199f60ca8e09843bbc62be70","observation_id":"8bd91ff3-9ada-4a3e-a95e-bda408f165c3","resolution":{"observed_at":"2026-05-25T04:30:21.050913Z","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":"2026-06-05T21:23:00.469572Z","title":"D^4m: Dataset distillation via disentangled diffusion model","venue":null,"work_id":"b3dcb116-086e-4ca0-8437-8205b2fadf30","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:688926e13f83a4656a5d4f498cd292d3681e9124e6ebf294dfa0f01652a65053","observation_id":"2e7c9b44-9053-4b2e-a44d-3cff8d70a80b","resolution":{"observed_at":"2026-05-25T04:30:20.833458Z","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":"2403.05530","last_updated":"2024-12-16T17:39:39Z","snapshot_observed_at":"2026-07-06T17:41:42.995949Z","submitted_at":"2024-03-08T18:54:20Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","version":5},"cited_work":{"arxiv_id":"2403.05530","doi":"10.48550/arxiv.2403.05530","metadata_source":"pith","pith_arxiv_id":"2403.05530","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","venue":"cs.CL","work_id":"80e3e977-f1bb-4c83-8d0c-1ab0a0c5c3f1","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2403.05530","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:fdefe2c416d767ac12f3d270acd3dd7334ca42b12b27247f6a91fc5553d12e58","observation_id":"b54fe154-1e67-4e55-8ec5-adf6b5fddca2","resolution":{"observed_at":"2026-05-25T04:30:19.739405Z","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":"2026-08-02T03:08:14.426583+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-02T03:08:14.426583+00:00","source":"openalex_status_cache"},{"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":"2026-06-05T21:23:00.469572Z","title":"Yfcc100m: The new data in multimedia research","venue":null,"work_id":"2029f07d-ecd3-4c29-b652-6d1daf4ef27d","year":2016},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:7e6ee975c63bb29862468caea8e37fa928044700c64e05a048127a626de83f2c","observation_id":"5397fbdb-8700-4d3d-8a6e-b347e6d9dcd4","resolution":{"observed_at":"2026-05-25T04:30:20.824915Z","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":"2303.11278","last_updated":"2024-05-08T19:04:46Z","snapshot_observed_at":"2026-08-13T12:20:34.109006Z","submitted_at":"2023-03-20T17:13:50Z","title":"Bayesian Pseudo-Coresets via Contrastive Divergence","version":2},"cited_work":{"arxiv_id":"2303.11278","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.11278","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Con- structing bayesian pseudo-coresets using contrastive diver- gence","venue":null,"work_id":"4eebb5c6-b411-4e2e-a4bf-98d64d7bc902","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2303.11278","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:84536a62f7f39d981d2df6f8181ada37b842e5e579b69f27e174467993e5466a","observation_id":"89accf18-2cb4-45ed-88e0-a9aee3249d67","resolution":{"observed_at":"2026-05-25T04:30:19.785787Z","resolver_source":"arxiv_id","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":{"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":"1812.05159","doi":"10.48550/arxiv.1812.05159","metadata_source":"pith","pith_arxiv_id":"1812.05159","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"An empirical study of example forgetting during deep neural network learning.arXiv preprint arXiv:1812.05159","venue":"cs.LG","work_id":"7d8ffe39-cf5a-4cb9-8835-8fc3f0984de1","year":2018},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/1812.05159","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:e3bcf4e9c70db4336f4abf8918906625c62407a4c11f0360db5ff0e82c8953b5","observation_id":"eefbc150-7e87-44eb-902a-56a245a9e444","resolution":{"observed_at":"2026-05-25T04:30:19.712917Z","resolver_source":"arxiv_id","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":"2026-07-11T02:19:28.595758+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T02:19:28.595758+00:00","source":"openalex_status_cache"},{"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":"2026-06-05T21:23:00.469572Z","title":"Cao2: Rectifying inconsistencies in diffusion-based dataset distillation","venue":null,"work_id":"d7f1045d-fd27-437a-bae8-26ef43a33ca8","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:9ab919743818b8ca86de8b7957b06a6376fd373038c693770d5ebaa984489cc4","observation_id":"4f41be25-51a7-4fcf-b99f-0a45a7b5da0b","resolution":{"observed_at":"2026-05-25T04:30:20.899139Z","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":"2026-06-05T21:23:00.469572Z","title":"Cafe: Learning to condense dataset by aligning features","venue":null,"work_id":"1ef57da4-5760-4026-a729-0a9507070829","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:0be94f134cf8891025f11f2d0eb5229241d9559c0ce075028a67af1aae32a9f4","observation_id":"5f9e55bc-0445-4e45-9857-0120f06f5e52","resolution":{"observed_at":"2026-05-25T04:30:20.806195Z","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":"1811.10959","last_updated":"2020-02-24T23:25:50Z","snapshot_observed_at":"2026-07-06T07:17:20.813296Z","submitted_at":"2018-11-27T13:17:45Z","title":"Dataset Distillation","version":3},"cited_work":{"arxiv_id":"1811.10959","doi":"10.48550/arxiv.1811.10959","metadata_source":"pith","pith_arxiv_id":"1811.10959","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Dataset Distillation","venue":"cs.LG","work_id":"e5036812-7ef1-4616-8677-c754d141d74f","year":2018},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/1811.10959","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:1c632641fbfd37619b0df56b2da4d43e4bb5070b8e3014023e3d78d245721351","observation_id":"b29b9174-524e-43dd-bc17-c32bb6546301","resolution":{"observed_at":"2026-05-25T04:30:19.758454Z","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":"2026-06-05T21:23:00.469572Z","title":"Herding dynamical weights to learn","venue":null,"work_id":"8ad0e8a3-8731-449e-b3f3-b4240b7d554a","year":2009},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:3fb5694873041de47b22aa42fe241be8b378c18099860d864e8347367c571cb7","observation_id":"71390526-98b4-49e9-95eb-335733897256","resolution":{"observed_at":"2026-05-25T04:30:20.820612Z","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":"2026-06-05T21:23:00.469572Z","title":"Vision-language dataset distillation","venue":null,"work_id":"0b6afec8-18c3-4f41-93cb-453974a31400","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:558c4f95fc9381106d474f9137d51d352ab140307fd1ff972ea35a56d2825df5","observation_id":"f0267136-f512-430b-8349-6c06467758ec","resolution":{"observed_at":"2026-05-25T04:30:20.801115Z","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":"2026-06-05T21:23:00.469572Z","title":"Low-rank similarity mining for multimodal dataset distilla- tion","venue":null,"work_id":"d59f6e91-82d4-45ae-961f-09ac568f915d","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:ff0a771d80f56d5c0e4b73fda1146d0fca87e3b05667ffe7530858aec9c68485","observation_id":"bd599628-1482-477d-b881-11027010f43f","resolution":{"observed_at":"2026-05-25T04:30:20.888993Z","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":"2026-06-05T21:23:00.469572Z","title":"Dataset distillation via cur- riculum data synthesis in large data era.Transactions on Machine Learning Research","venue":null,"work_id":"c800ca8b-dcf7-4bb5-99b1-0bb157b82e6a","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:7e077b192fd663c6a58eec9391d0cb4a7b1196118269199d1642a9de717d88b1","observation_id":"043e2b91-4b53-4652-a3e7-299c63e7e06d","resolution":{"observed_at":"2026-05-25T04:30:20.878109Z","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":"2306.13092","last_updated":"2024-02-11T20:34:51Z","snapshot_observed_at":"2026-08-13T11:11:04.879014Z","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":"2306.13092","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.13092","snapshot_observed_at":"2026-07-02T14:07:02.384303Z","title":"Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective","venue":null,"work_id":"aadded40-b338-47aa-a37b-7772e283bbe7","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2306.13092","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:07a545c3b2a4b101a798b59bfeaa1867f1312530eed85e69ede9635fccd17da8","observation_id":"d604cecb-090f-44e0-97e1-da48e3d5455f","resolution":{"observed_at":"2026-05-25T04:30:19.718376Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"04a0795b-7101-4f38-b7c2-c511ba361e1b","year":2014},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:84d9d1268dfc0c42b2b72cb99eb0ffec198ea3ff134d89a0f274f3335607413c","observation_id":"111f11fc-a5de-4f69-844b-dbccc76f4939","resolution":{"observed_at":"2026-05-25T04:30:20.797278Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dataset distilla- tion: A comprehensive review.IEEE transactions on pattern analysis and machine intelligence, 46(1):150–170","venue":null,"work_id":"fb8d9794-3dcb-4179-a61e-0cdbc7ee240e","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:2a7a0d4bf8cdc4d85ea96d5e6b96cead1e1dcccec93254d279d9da50cf1ddee1","observation_id":"6ef57874-b563-4d46-b0f9-d548c8227da2","resolution":{"observed_at":"2026-05-25T04:30:20.793995Z","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":"2026-06-05T21:23:00.469572Z","title":"Sigmoid loss for language image pre-training","venue":null,"work_id":"4ad05e9c-bec5-42a6-88a5-74daf1c9d7a7","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:0c5453392e9b7718a6c18d08c657b1bff543d446b039867e1b8706bd7a83ab77","observation_id":"a49359f0-811b-4fa8-810f-d61b30642f62","resolution":{"observed_at":"2026-05-25T04:30:20.815727Z","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":"2406.01063","last_updated":"2024-06-03T07:22:17Z","snapshot_observed_at":"2026-08-12T23:51:51.868071Z","submitted_at":"2024-06-03T07:22:17Z","title":"DANCE: Dual-View Distribution Alignment for Dataset Condensation","version":1},"cited_work":{"arxiv_id":"2406.01063","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.01063","snapshot_observed_at":"2026-07-04T03:29:29.763769Z","title":"Dance: Dual-view distri- bution alignment for dataset condensation","venue":null,"work_id":"698dd450-a5b7-4f33-804d-fbfb884b4be2","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2406.01063","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:012f9597743d87f87f9dc4f5eda4e1937849c87cc526e28260784e34c3a696e1","observation_id":"185e0e0e-cfa5-451a-9695-0d063f560890","resolution":{"observed_at":"2026-05-25T04:30:19.687628Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"M3d: Dataset condensation by minimizing maximum mean discrepancy","venue":null,"work_id":"c930adb5-00f2-4df2-8527-0ec95af8638b","year":2024},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:a844ef4f78dd2ab3904d089b2bc8bba22f1c6f260f95090884955559c48421b2","observation_id":"bfb7262f-4a5a-4920-a88c-2df36595d1a9","resolution":{"observed_at":"2026-05-25T04:30:20.873527Z","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":"2026-06-05T21:23:00.469572Z","title":"Accelerating dataset distillation via model augmentation","venue":null,"work_id":"ec5db80c-b3e6-4f74-8f8a-ae2476ed7bae","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:c791385ba6460dd036957daa780b943ccd5e0ba7074b69435032b96b8bf39026","observation_id":"b2cb886f-ebba-439a-8f86-c79b12daaa14","resolution":{"observed_at":"2026-05-25T04:30:20.863254Z","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":"2026-06-05T21:23:00.469572Z","title":"Dataset condensation with differ- entiable siamese augmentation","venue":null,"work_id":"452278ab-fe5d-45ed-98d4-e43a0b84b906","year":2021},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:f1f726ee97b890f1fe7205bb02b8ecf01cf3dd79f80d2a57f26ee45100efedf1","observation_id":"cd8b3ce3-6757-4877-8de9-9120269d17b7","resolution":{"observed_at":"2026-05-25T04:30:20.858815Z","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":"2204.07513","last_updated":"2022-12-21T03:01:34Z","snapshot_observed_at":"2026-07-06T13:00:46.828547Z","submitted_at":"2022-04-15T15:16:01Z","title":"Synthesizing Informative Training Samples with GAN","version":2},"cited_work":{"arxiv_id":"2204.07513","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2204.07513","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Synthesizing informative training samples with gan","venue":null,"work_id":"ae06f9f8-cf31-495e-a241-2ec2e0c96b13","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2204.07513","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:cf8c46b16484b832f3291b04ef417e01f8f0e2ad581192e43d3f3349ba93580d","observation_id":"a810b6d0-3cea-4b50-a9a4-dc7314514ddc","resolution":{"observed_at":"2026-05-25T04:30:19.677214Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Dataset condensation with distri- bution matching","venue":null,"work_id":"ac2e367b-8dd9-4fc6-859e-fd687d2869ee","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:80c8110a781947ae45bc015937e92872da3175eb5304919e6f85ed4ce009963c","observation_id":"a26b42b3-e791-4728-ae28-c8aa15b3876b","resolution":{"observed_at":"2026-05-25T04:30:20.782394Z","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":"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":"2006.05929","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.05929","snapshot_observed_at":"2026-07-04T03:29:29.787182Z","title":"Dataset condensation with gradient matching","venue":null,"work_id":"d8fcd60b-5c36-46b6-9812-2613367634e7","year":2006},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2006.05929","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:f9559d122eccd4ce53fd75a24940f9baf3da3a33c5ae71eb136bfa7d90bfd132","observation_id":"91f82cc9-7483-43fc-946a-bd188f0643c0","resolution":{"observed_at":"2026-05-25T04:30:19.780306Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Im- proved distribution matching for dataset condensation","venue":null,"work_id":"79785d14-bf2c-47cf-b7bd-b09ee6da0546","year":2023},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:b2f644cdd75eeca96e007ffd78fe36d2bd18a43535fa9f445d8a5cdcc49b3959","observation_id":"47748afe-db22-41ef-9273-c164b69c7fa2","resolution":{"observed_at":"2026-05-25T04:30:20.787603Z","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":"2509.15472","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T07:24:21.203066Z","title":"Efficient multimodal dataset distillation via generative models","venue":null,"work_id":"8f28381a-2a23-4a37-8295-a17bae20c4f1","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:df7183acd0d1c9f60ea820a8f7c4ae1d51b59ed0185bb3cdf48796e89bc4f313","observation_id":"f44b3032-351e-4fd8-bdf6-a983962b9867","resolution":{"observed_at":"2026-05-25T04:30:19.658123Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"Towards stable and storage- efficient dataset distillation: Matching convexified trajectory","venue":null,"work_id":"55ecaaff-e1da-4a63-a72f-35fad231aaec","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:d6c0fe6325862421f3863efa25328035e7f6422deea0eb556a7c18e0b989dbd5","observation_id":"73532abd-050b-4d85-94f4-9e771de7efda","resolution":{"observed_at":"2026-05-25T04:30:20.882646Z","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":"2206.00719","last_updated":"2022-10-24T05:49:56Z","snapshot_observed_at":"2026-08-13T06:37:56.589331Z","submitted_at":"2022-06-01T19:02:06Z","title":"Dataset Distillation using Neural Feature Regression","version":2},"cited_work":{"arxiv_id":"2206.00719","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2206.00719","snapshot_observed_at":"2026-06-30T07:24:21.226709Z","title":"Dataset distillation using neural feature regression","venue":null,"work_id":"afbe5aa3-860b-43f0-84f4-17948ac2037f","year":2022},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"cited_paper":"/paper/2206.00719","citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:576c1b2c8d3669e37c7f044bd85c95cb9896326991d8f7fa4b4051e9204e85a0","observation_id":"69dfc22c-e0f3-4067-bca7-55db51678670","resolution":{"observed_at":"2026-05-25T04:30:19.763435Z","resolver_source":"arxiv_id","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":"2026-06-05T21:23:00.469572Z","title":"modality gap","venue":null,"work_id":"540f6ca4-25fa-4a13-a5e2-89de9a123331","year":2025},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:3decdb0bd3a2c65b6fbc97bafb209d6d8830bfb4f6b071a481d2abfa652bf914","observation_id":"299df765-0679-44a8-a7cd-b805a44f2bdf","resolution":{"observed_at":"2026-05-25T04:30:20.778067Z","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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"5acb8e04-5d94-4368-ae25-bdb4573bf71b","year":null},"citing_paper":{"arxiv_id":"2605.23482","last_updated":"2026-05-22T10:41:58Z","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-05-25T04:30:04.849603Z"},"links":{"citing_paper":"/paper/2605.23482"},"observation_digest":"sha256:0d4f8d7530758db455767dcdc586ed380fb3705219d8153970e591cb17d636a4","observation_id":"f7823319-a57b-4eec-b86a-b274a96de661","resolution":{"observed_at":"2026-05-25T04:30:21.025755Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"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":"2605.23482","last_updated":"2026-05-22T10:41:58Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T20:25:13.564510Z","submitted_at":"2026-05-22T10:41:58Z","title":"Multimodal Distribution Matching for Vision-Language Dataset Distillation"},"reference_resolution":{"displayed":87,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":25,"verified_fuzzy":60},"total_outbound_references":87},"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 87 of 87 outbound references and 0 inbound Pith citation observations for arXiv:2605.23482."}