{"as_of":"2026-08-24T03:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:77a3df9f68d579c5ad95e8c54887acb7a95ea6caade388e73e689654aa3a33dc","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":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":29,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T22:36:22.992440Z","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":"2026-07-01T09:45:40.415009Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-12T19:18:15.990889Z","title":"Is synthetic data from generative models ready for image recognition?,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.10863","last_updated":"2024-11-16T19:01:50Z","snapshot_observed_at":"2026-08-20T06:56:59.867576Z","submitted_at":"2024-11-16T19:01:50Z","title":"Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T19:18:15.990889Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2411.10863"},"observation_digest":"sha256:c94e57853df60da3ec69e259a2e6e0b5010d6656614109765c53c5c0b22b9cf3","observation_id":"d6bf533c-c497-4f96-b3e3-ed8ccc311bda","resolution":{"observed_at":"2026-08-12T19:18:15.990889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-12T10:49:00.522078Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.18926","last_updated":"2024-11-28T05:25:33Z","snapshot_observed_at":"2026-08-17T07:26:38.960839Z","submitted_at":"2024-11-28T05:25:33Z","title":"Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough?","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T10:49:00.522078Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2411.18926"},"observation_digest":"sha256:84fa7dfee5fe669193e7060b0689d5d9224fb26cc59c120a82957c3dd9c63c84","observation_id":"6b42cfc1-8891-4a8e-b26d-d56663279635","resolution":{"observed_at":"2026-08-12T10:49:00.522078Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-11T19:57:41.037858Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.06248","last_updated":"2024-12-09T06:47:29Z","snapshot_observed_at":"2026-08-16T11:07:15.346366Z","submitted_at":"2024-12-09T06:47:29Z","title":"Rendering-Refined Stable Diffusion for Privacy Compliant Synthetic Data","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T19:57:41.037858Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2412.06248"},"observation_digest":"sha256:eeaf2e56aec7a7eef69b94fbe2fe1270b437751cefa717a1a1cfec75386684cc","observation_id":"167ca046-86cd-40d5-b63f-46896d7ddf23","resolution":{"observed_at":"2026-08-11T19:57:41.037858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-11T15:17:38.681766Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.11183","last_updated":"2025-08-22T08:05:31Z","snapshot_observed_at":"2026-08-17T19:40:22.222870Z","submitted_at":"2024-12-15T13:26:51Z","title":"OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T15:17:38.681766Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2412.11183"},"observation_digest":"sha256:d26b0ec5d9f493579fd0e7c937c503fed79c97f4b2a42b51ac03f45b445a74bb","observation_id":"2da199c9-c244-41e3-a70c-97c72ab12a8b","resolution":{"observed_at":"2026-08-11T15:17:38.681766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-11T11:32:38.988962Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.15358","last_updated":"2024-12-19T19:42:22Z","snapshot_observed_at":"2026-08-12T07:57:42.391472Z","submitted_at":"2024-12-19T19:42:22Z","title":"Dataset Augmentation by Mixing Visual Concepts","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T11:32:38.988962Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2412.15358"},"observation_digest":"sha256:b5b3c7a20c660f85a05e44cef6467fae15ee1f185867ae13114cfbc27d17cdca","observation_id":"fb51f3d9-a5ec-4569-b5a1-12f098664c81","resolution":{"observed_at":"2026-08-11T11:32:38.988962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-11T10:34:42.911407Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.16499","last_updated":"2024-12-21T06:10:32Z","snapshot_observed_at":"2026-08-20T18:14:47.808684Z","submitted_at":"2024-12-21T06:10:32Z","title":"Autonomous Crack Detection using Deep Learning on Synthetic Thermogram Datasets","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T10:34:42.911407Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2412.16499"},"observation_digest":"sha256:4a9b35f5882d291465d2b73c8d27388b77aa211f76e2e19ccde9a116439bc52b","observation_id":"91776a6a-e230-48a4-9f27-d838befc6bab","resolution":{"observed_at":"2026-08-11T10:34:42.911407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-11T05:47:18.871965Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.17219","last_updated":"2024-12-25T11:57:49Z","snapshot_observed_at":"2026-08-20T06:49:32.634788Z","submitted_at":"2024-12-23T02:18:54Z","title":"Discriminative Image Generation with Diffusion Models for Zero-Shot Learning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T05:47:18.871965Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2412.17219"},"observation_digest":"sha256:d4a120bc4c75af3ab886458fd667e08a622e2c8edbb6d397be174694fa066949","observation_id":"8eb57996-6dd5-4afa-9c53-86d97271b1a9","resolution":{"observed_at":"2026-08-11T05:47:18.871965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":"2210.07574","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-07-01T09:45:40.415009Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":"369476a1-565f-48dd-a629-3d2d93090c04","year":2022},"citing_paper":{"arxiv_id":"2503.22171","last_updated":"2026-04-17T04:53:40Z","snapshot_observed_at":"2026-08-15T00:04:06.434063Z","submitted_at":"2025-03-28T06:18:15Z","title":"An Empirical Study of Validating Synthetic Data for Text-Based Person Retrieval","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-22T22:59:36.542774Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2503.22171"},"observation_digest":"sha256:2ae31559f5ace7f355d255a439611020bb0b61de6a5cf9a2c53210f1ce5a7b44","observation_id":"0c589d14-8a62-474b-8b3f-54bdd15c57b9","resolution":{"observed_at":"2026-05-22T23:02:13.648759Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-15T22:36:22.992440Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.06948","last_updated":"2025-05-11T11:29:48Z","snapshot_observed_at":"2026-08-20T06:51:47.894008Z","submitted_at":"2025-05-11T11:29:48Z","title":"Unsupervised Learning for Class Distribution Mismatch","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-15T22:36:22.992440Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2505.06948"},"observation_digest":"sha256:208a66650c4f4a847ea611e4c69f27c1370e87f7ca9310d563532b5cc6f41487","observation_id":"43f2225f-9d78-4822-8e0d-489090480a42","resolution":{"observed_at":"2026-08-15T22:36:22.992440Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-15T21:10:42.107261Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.10551","last_updated":"2025-05-15T17:57:38Z","snapshot_observed_at":"2026-08-19T04:33:27.254516Z","submitted_at":"2025-05-15T17:57:38Z","title":"Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T21:10:42.107261Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2505.10551"},"observation_digest":"sha256:cfc7e42795e127112e23433031d0e39058949a9fa60c2e4493e9b189f050bec7","observation_id":"30c65c69-1c03-4064-8359-904db1834762","resolution":{"observed_at":"2026-08-15T21:10:42.107261Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-15T20:45:56.548166Z","title":"Is synthetic data from generative models ready for image recognition?,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.12108","last_updated":"2025-08-07T10:33:17Z","snapshot_observed_at":"2026-08-18T14:12:54.459810Z","submitted_at":"2025-05-17T18:27:15Z","title":"EarthSynth: Generating Informative Earth Observation with Diffusion Models","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T20:45:56.548166Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2505.12108"},"observation_digest":"sha256:04cd01c7978694b6ef0ca392e6f231086beb180fd61934c592bc517ff68c6dc6","observation_id":"01a133c2-618d-45e6-b2dd-eac8978168ef","resolution":{"observed_at":"2026-08-15T20:45:56.548166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-07T14:44:43.815200Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.17783","last_updated":"2025-08-26T15:45:08Z","snapshot_observed_at":"2026-08-22T12:04:43.984432Z","submitted_at":"2025-05-23T11:56:06Z","title":"Generative Data Augmentation for Object Point Cloud Segmentation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:44:43.815200Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2505.17783"},"observation_digest":"sha256:8d5e6d6eb27195df8f51e68a8fe9323fe5e73dfd1d85d1b7b8a6483820b48a75","observation_id":"67b64720-6b74-4e83-ae1f-fbab2eda55dd","resolution":{"observed_at":"2026-08-07T14:44:43.815200Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-06T23:12:16.931612Z","title":"Is synthetic data from generative models ready for image recognition?arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.19360","last_updated":"2025-06-26T01:32:12Z","snapshot_observed_at":"2026-08-20T14:28:42.959428Z","submitted_at":"2025-06-24T06:41:34Z","title":"SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T23:12:16.931612Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2506.19360"},"observation_digest":"sha256:aa38d4ec2e56c14562a71e25f96900a5076fbfb137620f6bd5af10dee208dacc","observation_id":"f12becd5-2a12-452d-b2f9-b7b5de9ce869","resolution":{"observed_at":"2026-08-06T23:12:16.931612Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-06T21:56:15.570823Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23038","last_updated":"2025-06-28T23:44:18Z","snapshot_observed_at":"2026-08-17T18:00:58.348652Z","submitted_at":"2025-06-28T23:44:18Z","title":"Inpainting is All You Need: A Diffusion-based Augmentation Method for Semi-supervised Medical Image Segmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T21:56:15.570823Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2506.23038"},"observation_digest":"sha256:0fe940beffc9c2e58a0ca4910a0b4cbd14dfa5f55aab9ba4f8050fa565645da5","observation_id":"20a68a1d-e3a2-4eb3-a58f-49d96ec5a5d5","resolution":{"observed_at":"2026-08-06T21:56:15.570823Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-06T20:04:01.714423Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.04051","last_updated":"2025-07-05T14:20:49Z","snapshot_observed_at":"2026-08-18T20:32:44.869707Z","submitted_at":"2025-07-05T14:20:49Z","title":"Generate, Refine, and Encode: Leveraging Synthesized Novel Samples for On-the-Fly Fine-Grained Category Discovery","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:04:01.714423Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2507.04051"},"observation_digest":"sha256:0fdac0fb2f245ea3d7ad87c777128bbdffcf6e991ba50fbb9ed0e29a3e4451d1","observation_id":"b5251441-0a8b-4390-8f88-04f93ba1fe46","resolution":{"observed_at":"2026-08-06T20:04:01.714423Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-06T15:18:06.780393Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.16254","last_updated":"2025-07-22T06:07:07Z","snapshot_observed_at":"2026-08-18T15:05:46.754623Z","submitted_at":"2025-07-22T06:07:07Z","title":"Edge-case Synthesis for Fisheye Object Detection: A Data-centric Perspective","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:06.780393Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2507.16254"},"observation_digest":"sha256:7ead2ef2c1916ec6c357c82b42ed6579c7b0033e0bd7602f5cfaabc978e42f5f","observation_id":"b573f621-05f3-47c2-ace2-655eb5a8c9d2","resolution":{"observed_at":"2026-08-06T15:18:06.780393Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-06T12:18:17.644406Z","title":"Is synthetic data from generative models ready for image recognition? arXiv preprint arXiv:2210.07574, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.21947","last_updated":"2025-07-29T16:00:20Z","snapshot_observed_at":"2026-08-12T10:40:36.846836Z","submitted_at":"2025-07-29T16:00:20Z","title":"Enhancing Generalization in Data-free Quantization via Mixup-class Prompting","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T12:18:17.644406Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2507.21947"},"observation_digest":"sha256:579154ca0542178a2aef654122e0d3a43a72b497c3af4bd20a788b801a1b80c6","observation_id":"bc4a2ee5-c593-4188-a4b6-cdca5ded8ab0","resolution":{"observed_at":"2026-08-06T12:18:17.644406Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-05T22:02:24.041143Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.07714","last_updated":"2025-08-11T07:41:09Z","snapshot_observed_at":"2026-08-14T09:12:42.455076Z","submitted_at":"2025-08-11T07:41:09Z","title":"DoorDet: Semi-Automated Multi-Class Door Detection Dataset via Object Detection and Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T22:02:24.041143Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2508.07714"},"observation_digest":"sha256:cfbfbd7a102280413b12a3e9751b7fd1ecebc68327943972e84c09164157e54b","observation_id":"b0efc5cc-9b65-4bbd-8064-e55be8f5400e","resolution":{"observed_at":"2026-08-05T22:02:24.041143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-05T11:53:05.422168Z","title":"Is synthetic data from generative models ready for image recognition?,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02161","last_updated":"2025-09-02T10:12:53Z","snapshot_observed_at":"2026-08-18T18:01:22.681674Z","submitted_at":"2025-09-02T10:12:53Z","title":"Enhancing Zero-Shot Pedestrian Attribute Recognition with Synthetic Data Generation: A Comparative Study with Image-To-Image Diffusion Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T11:53:05.422168Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2509.02161"},"observation_digest":"sha256:35a3b82b97cea33976d8546753b5c6c92316094ae124704ba35f9e11d3554f16","observation_id":"2cd1c357-0bce-4d37-9d5b-5c1fad07ec33","resolution":{"observed_at":"2026-08-05T11:53:05.422168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-05T10:17:01.818069Z","title":"Is synthetic data from generative models ready for image recognition?,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.04298","last_updated":"2025-09-04T15:13:29Z","snapshot_observed_at":"2026-08-14T09:41:41.899897Z","submitted_at":"2025-09-04T15:13:29Z","title":"Noisy Label Refinement with Semantically Reliable Synthetic Images","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T10:17:01.818069Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2509.04298"},"observation_digest":"sha256:b6e424890ec6ca3aaf7eccd1be7a3af2a039b91ff1e45040d648838a40ed48fd","observation_id":"4e5eea64-60b3-417f-91e7-11f4f39f776b","resolution":{"observed_at":"2026-08-05T10:17:01.818069Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":"2210.07574","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-07-01T09:45:40.415009Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":"369476a1-565f-48dd-a629-3d2d93090c04","year":2022},"citing_paper":{"arxiv_id":"2510.14543","last_updated":"2026-04-12T09:52:58Z","snapshot_observed_at":"2026-08-14T12:15:09.461533Z","submitted_at":"2025-10-16T10:32:48Z","title":"Exploring Cross-Modal Flows for Few-Shot Learning","version":4},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-18T06:16:12.608513Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2510.14543"},"observation_digest":"sha256:e9c9a622ee1f7161bf9014d4597a138249da944fc1fb7aed5a6b3be9e15be5c7","observation_id":"0d30919a-469e-4a3e-9163-c976570d76b7","resolution":{"observed_at":"2026-05-18T06:20:58.945504Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-04T08:07:37.618570Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.22973","last_updated":"2026-05-23T10:32:32Z","snapshot_observed_at":"2026-08-11T06:26:50.480167Z","submitted_at":"2025-10-27T03:52:45Z","title":"Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T08:07:37.618570Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2510.22973"},"observation_digest":"sha256:126fa1e168c4238a6e0dd4b318b30b8a92396bbebb0edd0973859f34c181e6b4","observation_id":"5e5fefb6-9f4e-49e7-a280-8db299e7e632","resolution":{"observed_at":"2026-08-04T08:07:37.618570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-03T05:06:44.477234Z","title":"Is synthetic data from generative models ready for image recognition?arXiv preprint arXiv:2210.07574,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.03300","last_updated":"2026-06-15T19:28:32Z","snapshot_observed_at":"2026-08-16T18:19:41.283950Z","submitted_at":"2026-02-03T09:26:32Z","title":"R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T05:06:44.477234Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2602.03300"},"observation_digest":"sha256:808e03575f7843799e467959d6fffe8e4a7a23f8c36a2e8b233a9436250da973","observation_id":"aa159330-4121-4a8a-8e79-959a5537da5b","resolution":{"observed_at":"2026-08-03T05:06:44.477234Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":"2210.07574","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-07-01T09:45:40.415009Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":"369476a1-565f-48dd-a629-3d2d93090c04","year":2022},"citing_paper":{"arxiv_id":"2604.12335","last_updated":"2026-04-14T06:17:35Z","snapshot_observed_at":"2026-08-11T09:39:12.749021Z","submitted_at":"2026-04-14T06:17:35Z","title":"All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T15:26:55.369840Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2604.12335"},"observation_digest":"sha256:7e36607cf17f8ff04fd44e09b7a79d3040353864bc5969c4f2adec1ad1e0e5f3","observation_id":"e7feb0d5-3409-482a-808b-e8e85549bf40","resolution":{"observed_at":"2026-05-11T10:31:03.831703Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":"2210.07574","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-07-01T09:45:40.415009Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":"369476a1-565f-48dd-a629-3d2d93090c04","year":2022},"citing_paper":{"arxiv_id":"2605.16384","last_updated":"2026-05-11T10:51:02Z","snapshot_observed_at":"2026-08-16T02:45:29.338546Z","submitted_at":"2026-05-11T10:51:02Z","title":"Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-05-20T22:41:44.510546Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2605.16384"},"observation_digest":"sha256:e070620b1692781f617e056fb77764997e6acfaf9cfdbba45069f34998b6c4ed","observation_id":"0ff88d79-2643-4dd0-83c7-e703cb9e722b","resolution":{"observed_at":"2026-05-20T22:43:50.948798Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":"2210.07574","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-07-01T09:45:40.415009Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":"369476a1-565f-48dd-a629-3d2d93090c04","year":2022},"citing_paper":{"arxiv_id":"2605.19289","last_updated":"2026-05-19T03:07:04Z","snapshot_observed_at":"2026-08-16T08:45:42.110720Z","submitted_at":"2026-05-19T03:07:04Z","title":"What Makes Synthetic Data Effective in Image Segmentation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-20T07:08:16.047730Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2605.19289"},"observation_digest":"sha256:bca0b7bc6d199e0b70836adae5ead7fb3f4686151a205a37809533ca1caa520f","observation_id":"8af1a31f-3564-4a74-98a1-a0e3174442c2","resolution":{"observed_at":"2026-05-20T07:13:06.678571Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":"2210.07574","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-07-01T09:45:40.415009Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":"369476a1-565f-48dd-a629-3d2d93090c04","year":2022},"citing_paper":{"arxiv_id":"2605.26353","last_updated":"2026-05-25T21:58:15Z","snapshot_observed_at":"2026-08-16T14:13:05.363241Z","submitted_at":"2026-05-25T21:58:15Z","title":"Personalized Generative Models for Contextual Debiasing","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-29T22:11:24.376145Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2605.26353"},"observation_digest":"sha256:4c46e398e720fe5a5d3564af04b43f36b76f07cca4590892718354890ec2d1db","observation_id":"11c6bb25-f64f-4dfd-b6cb-ad4cc834769d","resolution":{"observed_at":"2026-06-29T22:13:59.771709Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":"2210.07574","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-07-01T09:45:40.415009Z","title":"Is synthetic data from generative models ready for image recognition?","venue":null,"work_id":"369476a1-565f-48dd-a629-3d2d93090c04","year":2022},"citing_paper":{"arxiv_id":"2606.31204","last_updated":"2026-06-30T06:33:55Z","snapshot_observed_at":"2026-08-15T18:44:44.029397Z","submitted_at":"2026-06-30T06:33:55Z","title":"AC3S: Adaptive Conditioning for 3D-Aware Synthetic Data Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-01T06:12:59.736399Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2606.31204"},"observation_digest":"sha256:34f738891409a2aa5cd2be63512dd3cc5de32908abf8a4e3cb8852718f807bdb","observation_id":"5bfc6e4b-2ed7-4ebc-8438-4e5367190f0b","resolution":{"observed_at":"2026-07-01T09:45:40.416507Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07574","snapshot_observed_at":"2026-08-07T00:54:50.888768Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.04394","last_updated":"2026-08-05T02:56:32Z","snapshot_observed_at":"2026-08-14T18:05:59.304768Z","submitted_at":"2026-08-05T02:56:32Z","title":"Free-Lunch Augmentation by Revisiting Diffusion-Based Data Generation for Cross-Domain Few-Shot Object Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T00:54:50.888768Z"},"links":{"cited_paper":"/paper/2210.07574","citing_paper":"/paper/2608.04394"},"observation_digest":"sha256:7eed3e64084611f029dc2186031e643d4a533429096a6d58f0e857ad9daaf066","observation_id":"eab662ee-0bb0-4ad6-a007-255629963a0f","resolution":{"observed_at":"2026-08-07T00:54:50.888768Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2210.07574/citation-record","integrity":"/paper/2210.07574/integrity","json":"/paper/2210.07574/citation-record.json","paper":"/paper/2210.07574"},"outbound":[],"paper":{"arxiv_id":"2210.07574","last_updated":"2023-02-15T06:26:38Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-20T06:56:32.381613Z","submitted_at":"2022-10-14T06:54:24Z","title":"Is synthetic data from generative models ready for image recognition?"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2210.07574."}