{"as_of":"2026-08-08T07:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4f6b17d799757184299cbc686b97440eae168dcde0fe69d61c38b3f26ab6451c","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T04:54:50.954005Z","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":"2026-05-19T10:42:15.248266Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2104.08826","last_updated":"2021-11-18T07:56:58Z","snapshot_observed_at":"2026-07-06T11:01:05.577957Z","submitted_at":"2021-04-18T11:39:33Z","title":"GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08826","snapshot_observed_at":"2026-08-08T04:54:50.954005Z","title":"M., Park, D., Kang, J., Lee, S.-W., and Park, W","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.08512","last_updated":"2025-08-14T07:15:48Z","snapshot_observed_at":"2026-08-08T04:46:02.235147Z","submitted_at":"2025-02-12T15:46:34Z","title":"Measuring Diversity in Synthetic Datasets","version":3},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-08T04:54:50.954005Z"},"links":{"cited_paper":"/paper/2104.08826","citing_paper":"/paper/2502.08512"},"observation_digest":"sha256:986fe44bb35e8cd128285ef9dfa3d749304ac063d96254b63486a12f307c6b14","observation_id":"cd503249-e67f-4711-b802-1776c985488d","resolution":{"observed_at":"2026-08-08T04:54:50.954005Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08826","last_updated":"2021-11-18T07:56:58Z","snapshot_observed_at":"2026-07-06T11:01:05.577957Z","submitted_at":"2021-04-18T11:39:33Z","title":"GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08826","snapshot_observed_at":"2026-08-07T11:22:46.312956Z","title":"Gpt3mix: Leveraging large-scale language models for text augmentation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.02689","last_updated":"2025-06-04T02:34:54Z","snapshot_observed_at":"2026-08-07T11:15:51.397764Z","submitted_at":"2025-06-03T09:41:35Z","title":"MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:22:46.312956Z"},"links":{"cited_paper":"/paper/2104.08826","citing_paper":"/paper/2506.02689"},"observation_digest":"sha256:f780f3046ebfc8680c7917c1457e12c609a44d3465a2c49ba36f26ba6d6e6aa0","observation_id":"962356cc-a183-4575-86eb-b59d00747245","resolution":{"observed_at":"2026-08-07T11:22:46.312956Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08826","last_updated":"2021-11-18T07:56:58Z","snapshot_observed_at":"2026-07-06T11:01:05.577957Z","submitted_at":"2021-04-18T11:39:33Z","title":"GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation","version":2},"cited_work":{"arxiv_id":"2104.08826","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2104.08826","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"e5085752-5ff8-4519-bc0e-3de82cf65973","year":2021},"citing_paper":{"arxiv_id":"2506.06226","last_updated":"2026-04-20T11:25:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-06T16:41:17Z","title":"No Data? No Problem: Synthesizing Security Graphs for Better Intrusion Detection","version":3},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-19T10:38:03.311357Z"},"links":{"cited_paper":"/paper/2104.08826","citing_paper":"/paper/2506.06226"},"observation_digest":"sha256:8621379c2d4a0c4724221eff6b11961e2211ebb89bd51740cb7551034dc1749e","observation_id":"462d8bf5-fbae-4752-95d5-7e7e1a64470a","resolution":{"observed_at":"2026-05-19T10:42:15.249612Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08826","last_updated":"2021-11-18T07:56:58Z","snapshot_observed_at":"2026-07-06T11:01:05.577957Z","submitted_at":"2021-04-18T11:39:33Z","title":"GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08826","snapshot_observed_at":"2026-08-06T23:12:19.045722Z","title":"Gpt3mix: Leveraging large-scale language models for text augmentation.arXiv preprint arXiv:2104.08826, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.19262","last_updated":"2025-06-25T03:25:04Z","snapshot_observed_at":"2026-08-08T05:27:16.733839Z","submitted_at":"2025-06-24T02:44:58Z","title":"What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T23:12:19.045722Z"},"links":{"cited_paper":"/paper/2104.08826","citing_paper":"/paper/2506.19262"},"observation_digest":"sha256:b18128ad2f15fb4b06adb22e11c8caac21cbc7c5c41d46a95de7ff65d8bf4b64","observation_id":"19c461a0-09a6-4266-98e1-70345fc5d622","resolution":{"observed_at":"2026-08-06T23:12:19.045722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08826","last_updated":"2021-11-18T07:56:58Z","snapshot_observed_at":"2026-07-06T11:01:05.577957Z","submitted_at":"2021-04-18T11:39:33Z","title":"GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08826","snapshot_observed_at":"2026-08-06T15:55:22.763384Z","title":"arXiv preprint arXiv:2104.08826 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.14590","last_updated":"2025-07-19T12:23:20Z","snapshot_observed_at":"2026-08-06T15:49:51.301954Z","submitted_at":"2025-07-19T12:23:20Z","title":"Backtranslation and paraphrasing in the LLM era? Comparing data augmentation methods for emotion classification","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T15:55:22.763384Z"},"links":{"cited_paper":"/paper/2104.08826","citing_paper":"/paper/2507.14590"},"observation_digest":"sha256:85e53a74b43952b6d8615c94feee818fb4b7c30d871b154f0e3d26ee20ee175f","observation_id":"8f3d0bb5-3d28-4fa7-a3ae-6deefd5d474e","resolution":{"observed_at":"2026-08-06T15:55:22.763384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2104.08826/citation-record","integrity":"/paper/2104.08826/integrity","json":"/paper/2104.08826/citation-record.json","paper":"/paper/2104.08826"},"outbound":[],"paper":{"arxiv_id":"2104.08826","last_updated":"2021-11-18T07:56:58Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T11:01:05.577957Z","submitted_at":"2021-04-18T11:39:33Z","title":"GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2104.08826."}