{"as_of":"2026-08-23T06:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a62c5611f966ff73e61e3ffc159a09c62278059960491291648908db31506ce","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:01:58.846242Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T10:29:44.377971Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08448","snapshot_observed_at":"2026-08-12T10:48:20.273205Z","title":"Data distillation for text classifica- tion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.00111","last_updated":"2024-11-28T05:37:54Z","snapshot_observed_at":"2026-08-17T14:10:21.088804Z","submitted_at":"2024-11-28T05:37:54Z","title":"Video Set Distillation: Information Diversification and Temporal Densification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T10:48:20.273205Z"},"links":{"cited_paper":"/paper/2104.08448","citing_paper":"/paper/2412.00111"},"observation_digest":"sha256:6ddab6e1b0081bb932a183fd9ca54ab57f4561f32c48306520bdc24918ab93a4","observation_id":"b7371611-d7d3-4d65-bb62-2d1a94da21e3","resolution":{"observed_at":"2026-08-12T10:48:20.273205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08448","snapshot_observed_at":"2026-08-11T22:24:44.122871Z","title":"Data distillation for text classifi- cation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.03512","last_updated":"2024-12-04T17:55:33Z","snapshot_observed_at":"2026-08-17T21:55:54.330193Z","submitted_at":"2024-12-04T17:55:33Z","title":"Distillation of Diffusion Features for Semantic Correspondence","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T22:24:44.122871Z"},"links":{"cited_paper":"/paper/2104.08448","citing_paper":"/paper/2412.03512"},"observation_digest":"sha256:bb9c499c3a88d7e5738d43371c7e73c838fd385f3bcc64e21b7dcfad98c9bdf3","observation_id":"fc4bfb2a-d917-4f8a-9cf2-e1348f9ecd7f","resolution":{"observed_at":"2026-08-11T22:24:44.122871Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08448","snapshot_observed_at":"2026-08-09T10:55:55.010981Z","title":"Data distillation for text classification","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02854","last_updated":"2025-02-06T08:29:46Z","snapshot_observed_at":"2026-08-14T19:26:19.282455Z","submitted_at":"2025-02-05T03:13:25Z","title":"TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T10:55:55.010981Z"},"links":{"cited_paper":"/paper/2104.08448","citing_paper":"/paper/2502.02854"},"observation_digest":"sha256:72265fab05745be412cd91e100ae12e7cc897ef74f0ab79b6f05372fe62c146f","observation_id":"24ec8b36-9dbd-4c27-b9fe-d14ae74f96b2","resolution":{"observed_at":"2026-08-09T10:55:55.010981Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08448","snapshot_observed_at":"2026-08-16T12:01:58.846242Z","title":"and Li, W","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.13825","last_updated":"2025-04-18T17:54:33Z","snapshot_observed_at":"2026-08-16T14:33:02.618374Z","submitted_at":"2025-04-18T17:54:33Z","title":"Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-16T12:01:58.846242Z"},"links":{"cited_paper":"/paper/2104.08448","citing_paper":"/paper/2504.13825"},"observation_digest":"sha256:5637b44740012415724780b9aaec6885e930a195b920dab38ef4b53958ce7f5c","observation_id":"2a2296f0-5af0-4b8a-88ff-6455a4011a97","resolution":{"observed_at":"2026-08-16T12:01:58.846242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08448","snapshot_observed_at":"2026-08-07T13:55:21.222904Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.20807","last_updated":"2025-05-27T07:13:10Z","snapshot_observed_at":"2026-08-19T17:08:54.809417Z","submitted_at":"2025-05-27T07:13:10Z","title":"Simple yet Effective Graph Distillation via Clustering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:55:21.222904Z"},"links":{"cited_paper":"/paper/2104.08448","citing_paper":"/paper/2505.20807"},"observation_digest":"sha256:c80585c0be8bb0a792802e08491c88c565d8e8527ef0c5bf597c2823250c0d65","observation_id":"531d2736-a2d9-4ddc-971c-ef71e28f5cc4","resolution":{"observed_at":"2026-08-07T13:55:21.222904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification","version":1},"cited_work":{"arxiv_id":"2104.08448","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.08448","snapshot_observed_at":"2026-07-04T10:29:44.377971Z","title":"arXiv preprint arXiv:2104.08448 , year=","venue":null,"work_id":"e601bc95-2adc-4e83-b9dc-3cee3202e277","year":null},"citing_paper":{"arxiv_id":"2606.22975","last_updated":"2026-06-22T07:55:55Z","snapshot_observed_at":"2026-08-18T19:50:59.695012Z","submitted_at":"2026-06-22T07:55:55Z","title":"TaLK: Text-attributed Graph Dataset Distillation via Coupling Language Model with Graph-Aware Kernel","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-06-26T08:53:13.162764Z"},"links":{"cited_paper":"/paper/2104.08448","citing_paper":"/paper/2606.22975"},"observation_digest":"sha256:1df5060f97131a6a66aa4a90942f298bea86183a5b5d4bcd91c7ad781de26b7a","observation_id":"d0c5c346-f7cd-4f47-bf9d-9adbbe5ec179","resolution":{"observed_at":"2026-07-04T10:29:44.379549Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08448","snapshot_observed_at":"2026-08-02T12:58:09.769343Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20477","last_updated":"2026-05-27T14:52:24Z","snapshot_observed_at":"2026-08-20T04:54:06.573168Z","submitted_at":"2026-05-27T14:52:24Z","title":"Semi-Supervised Text-Attributed Graph Distillation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T12:58:09.769343Z"},"links":{"cited_paper":"/paper/2104.08448","citing_paper":"/paper/2607.20477"},"observation_digest":"sha256:604371818c0b9514edfc04cc0692b9bb5b74b3d142d494884f87a8c85ffc4f16","observation_id":"3defd738-847a-4853-b5b8-0902aec3e5e1","resolution":{"observed_at":"2026-08-02T12:58:09.769343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2104.08448/citation-record","integrity":"/paper/2104.08448/integrity","json":"/paper/2104.08448/citation-record.json","paper":"/paper/2104.08448"},"outbound":[],"paper":{"arxiv_id":"2104.08448","last_updated":"2021-04-17T04:54:54Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-19T19:03:24.327144Z","submitted_at":"2021-04-17T04:54:54Z","title":"Data Distillation for Text Classification"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2104.08448."}