{"as_of":"2026-08-19T11:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2b10a01eda5058bb8e59310a5fe437adb14f25e1e8c63e2b73962d1d009761f1","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T18:51:47.472317Z","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":"2026-05-10T16:55:57.755875Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":"2203.00386","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","venue":null,"work_id":"e8e47566-ee56-4fd0-8e66-34c6b471db7a","year":2022},"citing_paper":{"arxiv_id":"2204.06125","last_updated":"2022-04-13T01:10:33Z","snapshot_observed_at":"2026-08-15T12:50:58.405488Z","submitted_at":"2022-04-13T01:10:33Z","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-10T16:55:57.612364Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2204.06125"},"observation_digest":"sha256:b7ca5d18f345a2f3a261c370f33e4f3186a60956af455470459a3d9a91c0bad9","observation_id":"1f4e4dd4-4b6a-492f-9cee-e4a6c034e945","resolution":{"observed_at":"2026-05-10T16:55:57.758432Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-12T18:02:15.171099Z","title":"Clip-gen: Language-free training of a text-to-image genera- tor with clip","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12044","last_updated":"2025-04-14T16:02:15Z","snapshot_observed_at":"2026-08-17T12:18:23.191452Z","submitted_at":"2024-11-18T20:31:38Z","title":"ITACLIP: Boosting Training-Free Semantic Segmentation with Image, Text, and Architectural Enhancements","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-12T18:02:15.171099Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2411.12044"},"observation_digest":"sha256:d41e3976f9e7021f2281c90ff19be0a7f40d2bd6f99818b0b144904e904c86ff","observation_id":"feb0ec46-cbde-4eec-955d-825dc8e0ba31","resolution":{"observed_at":"2026-08-12T18:02:15.171099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-12T17:44:06.184255Z","title":"Clip-gen: Language- free training of a text-to-image generator with clip,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12319","last_updated":"2024-11-20T03:31:17Z","snapshot_observed_at":"2026-08-18T11:02:23.210144Z","submitted_at":"2024-11-19T08:23:52Z","title":"CLIP Unreasonable Potential in Single-Shot Face Recognition","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T17:44:06.184255Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2411.12319"},"observation_digest":"sha256:a4cf22705a0d3815e1223b936037da714167bb0d686b145df8f4945bb2af748d","observation_id":"c312f0ed-0886-4efd-bc38-b84dafb08972","resolution":{"observed_at":"2026-08-12T17:44:06.184255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-11T20:29:54.320641Z","title":"arXiv preprint arXiv:2203.00386 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.05694","last_updated":"2024-12-07T16:43:02Z","snapshot_observed_at":"2026-08-18T14:49:39.665050Z","submitted_at":"2024-12-07T16:43:02Z","title":"Combining Genre Classification and Harmonic-Percussive Features with Diffusion Models for Music-Video Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T20:29:54.320641Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2412.05694"},"observation_digest":"sha256:69c9fa7a550b9999c8c18214bac78d28af1961f3c4c6eea0db2ee10e0cef55c8","observation_id":"7c4614a6-cdc5-4e16-86ca-d30e5eb20a41","resolution":{"observed_at":"2026-08-11T20:29:54.320641Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-11T20:29:03.376858Z","title":"Clip-gen: Language-free training of a text-to-image genera- tor with clip","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.05780","last_updated":"2024-12-23T11:42:18Z","snapshot_observed_at":"2026-08-15T15:21:57.185549Z","submitted_at":"2024-12-08T02:23:40Z","title":"BudgetFusion: Perceptually-Guided Adaptive Diffusion Models","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T20:29:03.376858Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2412.05780"},"observation_digest":"sha256:a15095aa3d0ce564c4009415d86af3aeb3055896f012b80a129ad1f964a7fa53","observation_id":"2c4eff88-30ba-44b7-a738-1980efce8508","resolution":{"observed_at":"2026-08-11T20:29:03.376858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-11T18:11:54.551267Z","title":"Clip-gen: Language- free training of a text-to-image generator with clip,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.08158","last_updated":"2024-12-11T07:29:04Z","snapshot_observed_at":"2026-08-13T23:49:23.874766Z","submitted_at":"2024-12-11T07:29:04Z","title":"How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-11T18:11:54.551267Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2412.08158"},"observation_digest":"sha256:580a6f956e604f328f0f179815b0ac172778806512c1dbecef7793cc86eaee58","observation_id":"7b895ac4-d2b2-4224-9f9e-fff8f3f4666c","resolution":{"observed_at":"2026-08-11T18:11:54.551267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-07T12:58:10.360905Z","title":"Clip-gen: Language-free training of a text-to-image generator with clip.arXiv preprint arXiv:2203.00386, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23161","last_updated":"2025-06-04T10:30:14Z","snapshot_observed_at":"2026-08-14T21:25:22.613578Z","submitted_at":"2025-05-29T06:55:26Z","title":"Implicit Inversion turns CLIP into a Decoder","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T12:58:10.360905Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2505.23161"},"observation_digest":"sha256:5ba391b566711c1b1df47abf447d19dca964af1babdab68eb1adc6c63d205fc9","observation_id":"fc31449a-d54d-4159-8edc-c13736f48fc1","resolution":{"observed_at":"2026-08-07T12:58:10.360905Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-15T18:51:47.472317Z","title":"Clip-gen: Language- free training of a text-to-image generator with clip,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.18544","last_updated":"2025-06-23T11:54:15Z","snapshot_observed_at":"2026-08-19T03:07:51.140706Z","submitted_at":"2025-06-23T11:54:15Z","title":"Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T18:51:47.472317Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2506.18544"},"observation_digest":"sha256:d8e5d2e5f5333058314f369a03a667d9222c2ab1d4e47fcf676346d28ad85787","observation_id":"3bba8fd5-c2a1-4655-a9c9-e30ce919f66d","resolution":{"observed_at":"2026-08-15T18:51:47.472317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-06T20:59:02.389027Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.01438","last_updated":"2025-07-02T07:47:28Z","snapshot_observed_at":"2026-08-18T02:46:10.927697Z","submitted_at":"2025-07-02T07:47:28Z","title":"EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-06T20:59:02.389027Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2507.01438"},"observation_digest":"sha256:7f93ece1b4a2d6c3dcfc8c20923629a74e8f1e5c634d726dafa6ef73a69b7605","observation_id":"58ee5fe9-b9a1-47fb-842b-0053e92d9dce","resolution":{"observed_at":"2026-08-06T20:59:02.389027Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00386","snapshot_observed_at":"2026-08-04T17:39:24.326550Z","title":"Clip-gen: Language- free training of a text-to-image generator with clip,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.10765","last_updated":"2025-09-13T00:37:20Z","snapshot_observed_at":"2026-08-10T12:45:00.699713Z","submitted_at":"2025-09-13T00:37:20Z","title":"Language-based Color ISP Tuning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T17:39:24.326550Z"},"links":{"cited_paper":"/paper/2203.00386","citing_paper":"/paper/2509.10765"},"observation_digest":"sha256:2946905e23d483a1200099e808cc55e2790df32c8a46e0e0ee3cd652869d05b5","observation_id":"050fddba-2847-49b4-ae68-99af450117c7","resolution":{"observed_at":"2026-08-04T17:39:24.326550Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2203.00386/citation-record","integrity":"/paper/2203.00386/integrity","json":"/paper/2203.00386/citation-record.json","paper":"/paper/2203.00386"},"outbound":[],"paper":{"arxiv_id":"2203.00386","last_updated":"2022-03-01T12:11:32Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T17:17:50.020394Z","submitted_at":"2022-03-01T12:11:32Z","title":"CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2203.00386."}