{"as_of":"2026-08-10T10:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:429926fc6f6abeadf88e2a4656595e422e3c36465e7ab8ba61cab197a91a5fc9","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":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":54,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T04:33:41.230759Z","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":"2026-07-04T20:50:11.498748Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-06T10:59:53.523420Z","title":"Pixelflow: Pixel-space generative models with flow.arXiv preprint arXiv:2504.07963, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.23268","last_updated":"2025-08-04T02:46:11Z","snapshot_observed_at":"2026-08-09T02:04:57.127931Z","submitted_at":"2025-07-31T06:07:20Z","title":"PixNerd: Pixel Neural Field Diffusion","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T10:59:53.523420Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2507.23268"},"observation_digest":"sha256:9b3ec53f9c014538b876e8fd30ae5937f92578c6e76d987a8d8a370efbd9f5db","observation_id":"f7b969ef-c99a-417f-a9f5-f508966d6c65","resolution":{"observed_at":"2026-08-06T10:59:53.523420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2511.13720","last_updated":"2026-01-07T05:36:57Z","snapshot_observed_at":"2026-07-06T22:36:08.495952Z","submitted_at":"2025-11-17T18:59:57Z","title":"Back to Basics: Let Denoising Generative Models Denoise","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-11T22:16:26.996599Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2511.13720"},"observation_digest":"sha256:aa04f6202cdf3acddac071fd1cbd0186577ae096376245e4f6db3e9dfc7c42b0","observation_id":"5270a220-d129-45cd-ab97-67d951c792ef","resolution":{"observed_at":"2026-05-11T22:16:28.411069Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2511.19365","last_updated":"2026-04-08T04:08:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-24T17:59:06Z","title":"DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-17T05:47:24.669763Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2511.19365"},"observation_digest":"sha256:0e9e145bd606ca78350de1d755d6ea2c8dc21c957a660fd336f0d59a04d864bc","observation_id":"26f667ff-d0a4-45bf-8c58-966b79017ddb","resolution":{"observed_at":"2026-05-17T05:49:08.334118Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2511.20645","last_updated":"2026-04-16T17:04:25Z","snapshot_observed_at":"2026-08-07T01:34:34.936041Z","submitted_at":"2025-11-25T18:59:25Z","title":"PixelDiT: Pixel Diffusion Transformers for Image Generation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-17T04:30:07.417197Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2511.20645"},"observation_digest":"sha256:efc5d2254abb1d00f3be275bbdbc2c0b1086678f84d56e81d8f9f57b6b363c76","observation_id":"da6f7c05-5dce-4ed1-9492-1c27e78d162a","resolution":{"observed_at":"2026-05-17T04:31:31.179894Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-03T15:35:13.368010Z","title":"Pixelflow: Pixel-space generative models with flow.arXiv preprint arXiv:2504.07963, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.16615","last_updated":"2026-07-23T12:12:25Z","snapshot_observed_at":"2026-08-07T23:52:07.948019Z","submitted_at":"2025-12-18T14:53:12Z","title":"Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T15:35:13.368010Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2512.16615"},"observation_digest":"sha256:050bb6d1f13707a9a02782c22e9cc251d90f5e392facc46cb17ecf4cc46297c8","observation_id":"5c217c85-25fb-41a1-a626-ff52e4422d43","resolution":{"observed_at":"2026-08-03T15:35:13.368010Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2602.04883","last_updated":"2026-05-18T18:23:50Z","snapshot_observed_at":"2026-08-07T14:56:29.023603Z","submitted_at":"2026-02-04T18:59:49Z","title":"Protein Autoregressive Modeling via Multiscale Structure Generation","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-21T13:21:53.668727Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2602.04883"},"observation_digest":"sha256:7d8a87e3332a6e2a8d3132a59bfae5506ff0a0fafb92e4fc05c96d628bebfea0","observation_id":"5b9fe0ff-d5d4-4eb7-805a-665e990f4e1f","resolution":{"observed_at":"2026-05-21T13:24:11.257303Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-03T01:25:17.920187Z","title":"Pixelflow: Pixel-space generative models with flow.arXiv preprint arXiv:2504.07963,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.10099","last_updated":"2026-07-03T15:19:24Z","snapshot_observed_at":"2026-08-06T13:27:43.962812Z","submitted_at":"2026-02-10T18:58:04Z","title":"Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T01:25:17.920187Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2602.10099"},"observation_digest":"sha256:b06d2a0d1a14cfea0ac96b572423c58d8ebe9832dafc583c119ffb55e81ae234","observation_id":"39c7df84-4c10-46fe-a1a4-c25de5e9be75","resolution":{"observed_at":"2026-08-03T01:25:17.920187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-15T14:00:06.859472Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.06136","last_updated":"2026-06-30T13:32:05Z","snapshot_observed_at":"2026-08-08T21:37:10.403272Z","submitted_at":"2026-03-06T10:45:07Z","title":"Cross-Resolution Distribution Matching for Diffusion Distillation","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-15T14:00:06.859472Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2603.06136"},"observation_digest":"sha256:de09b51735132deb6e9a92921055bbce5d195d380d84610cf7018143343f8983","observation_id":"db3060bf-5110-4b6e-b6d1-8d074ce8bf96","resolution":{"observed_at":"2026-07-15T14:00:06.859472Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2603.21002","last_updated":"2026-05-18T13:08:31Z","snapshot_observed_at":"2026-07-06T22:50:01.539214Z","submitted_at":"2025-11-25T18:54:45Z","title":"SURF: Signature-Retained Fast Video Generation","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-21T18:11:39.642701Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2603.21002"},"observation_digest":"sha256:c0943cf1d17dfe08bbf475e5e3be99809610112d15b812c1a27538a6175ca92e","observation_id":"86f1c0c0-04bb-4e96-abc7-e3e693c9a11e","resolution":{"observed_at":"2026-05-21T18:14:17.499021Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2604.04874","last_updated":"2026-04-06T17:24:18Z","snapshot_observed_at":"2026-07-06T22:53:46.999911Z","submitted_at":"2026-04-06T17:24:18Z","title":"Free-Range Gaussians: Non-Grid-Aligned Generative 3D Gaussian Reconstruction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T19:50:01.623443Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2604.04874"},"observation_digest":"sha256:4705da66cc2e55549cf44123e6a8833cdfeda4b5623418791c3a39b5d792df93","observation_id":"f0159a20-7e6a-4251-a93f-8b28bdb331c9","resolution":{"observed_at":"2026-05-10T22:30:49.262373Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2604.11521","last_updated":"2026-04-13T14:23:31Z","snapshot_observed_at":"2026-07-31T08:57:40.954187Z","submitted_at":"2026-04-13T14:23:31Z","title":"Continuous Adversarial Flow Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T15:25:53.420119Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2604.11521"},"observation_digest":"sha256:89016f7692005fcb61043fe0bb8849d9a517d23e73b515c40c11a493768b971d","observation_id":"2549e106-d73d-49cc-815c-02ac01795088","resolution":{"observed_at":"2026-05-11T10:36:02.103686Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2604.17492","last_updated":"2026-04-19T15:29:15Z","snapshot_observed_at":"2026-07-06T23:04:37.370465Z","submitted_at":"2026-04-19T15:29:15Z","title":"Coevolving Representations in Joint Image-Feature Diffusion","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T06:30:52.371482Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2604.17492"},"observation_digest":"sha256:690326d62b1165b14f4692aa0bfefc915ce3fdbbdd5434e0bd7edf8e04b4f514","observation_id":"ce42a778-12b4-47d3-9fd8-c1883918f41b","resolution":{"observed_at":"2026-05-10T06:31:30.431890Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2604.23264","last_updated":"2026-04-25T12:16:37Z","snapshot_observed_at":"2026-08-06T05:53:51.992744Z","submitted_at":"2026-04-25T12:16:37Z","title":"MotionHiFlow: Text-to-motion via hierarchical flow matching","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T08:28:42.524111Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2604.23264"},"observation_digest":"sha256:41b86cb4e0ffcdb33ad0493574193bf4449a8d1024c03cbbe8397d008a5fad2c","observation_id":"1e6846d6-2171-4449-9417-c16cff0a8cdf","resolution":{"observed_at":"2026-05-11T20:36:10.898980Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2604.24763","last_updated":"2026-05-18T04:20:18Z","snapshot_observed_at":"2026-07-06T23:10:42.926677Z","submitted_at":"2026-04-27T17:59:56Z","title":"Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T04:31:26.325118Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2604.24763"},"observation_digest":"sha256:7baa5a2b52570a7c723437ad3793f44bd32254956a0b8a1524bf5eb7cb27663a","observation_id":"36fc4841-ea36-454f-bef0-14c098b766d7","resolution":{"observed_at":"2026-05-11T21:41:18.874632Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2604.24763","last_updated":"2026-05-18T04:20:18Z","snapshot_observed_at":"2026-07-06T23:10:42.926677Z","submitted_at":"2026-04-27T17:59:56Z","title":"Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-20T23:41:25.275207Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2604.24763"},"observation_digest":"sha256:19e2d73888922e4043f8d21e8f358e16efa92727f1643fdfa463532e02378e10","observation_id":"02e8942e-6abf-4af7-a3b9-2e719e2aa46e","resolution":{"observed_at":"2026-05-20T23:43:51.084701Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.03623","last_updated":"2026-05-05T10:51:40Z","snapshot_observed_at":"2026-07-06T23:16:30.147006Z","submitted_at":"2026-05-05T10:51:40Z","title":"A Few-Step Generative Model on Cumulative Flow Maps","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-05-07T17:05:28.396612Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.03623"},"observation_digest":"sha256:31309d875cf7aec6689fe707ed7c3d86a0924017bf93e17f69a5fb7869ea3838","observation_id":"6d520650-10cd-45ef-98a4-449513ecc8d7","resolution":{"observed_at":"2026-05-11T23:26:13.306252Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.06421","last_updated":"2026-07-28T07:17:48Z","snapshot_observed_at":"2026-08-02T14:48:28.958067Z","submitted_at":"2026-05-07T15:27:46Z","title":"FREPix: Frequency-Heterogeneous Flow Matching for Pixel-Space Image Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T13:24:49.746981Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.06421"},"observation_digest":"sha256:43bd96ee7b9e70612236dc0de5b1d62b9e2ac92a74712dc483116194efcf1d73","observation_id":"ca2fd028-4ceb-401d-8401-2da08e1c8f36","resolution":{"observed_at":"2026-05-11T18:56:06.093827Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-02T14:48:31.918578Z","title":"Pixelflow: Pixel-space generative models with flow.arXiv preprint arXiv:2504.07963, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.06421","last_updated":"2026-07-28T07:17:48Z","snapshot_observed_at":"2026-08-02T14:48:28.958067Z","submitted_at":"2026-05-07T15:27:46Z","title":"FREPix: Frequency-Heterogeneous Flow Matching for Pixel-Space Image Generation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T14:48:31.918578Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.06421"},"observation_digest":"sha256:4b09450eee44d1437599e8d363664aba0b117a19970e95d2800d556ab5e2e381","observation_id":"321b8cfc-5cd7-41b0-8899-a5b5fe510407","resolution":{"observed_at":"2026-08-02T14:48:31.918578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.12500","last_updated":"2026-05-12T17:59:58Z","snapshot_observed_at":"2026-07-06T23:24:13.851504Z","submitted_at":"2026-05-12T17:59:58Z","title":"SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-13T05:12:37.339084Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.12500"},"observation_digest":"sha256:3b9c78ddee498a1f8f6385bba6df23a2807f484ef6ee886421040b29ed13b209","observation_id":"f495c277-ff77-46fc-a33a-c0285f78f7df","resolution":{"observed_at":"2026-05-13T05:17:18.498517Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.12964","last_updated":"2026-05-25T05:34:21Z","snapshot_observed_at":"2026-07-06T23:24:37.915639Z","submitted_at":"2026-05-13T03:58:01Z","title":"Asymmetric Flow Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-14T19:28:21.625879Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.12964"},"observation_digest":"sha256:07806795a45da0c5cbf92032b50e55c42e618649200034bfd0be6f2355ed8a27","observation_id":"53fe5ade-db2f-4c2a-91cd-b2bde1956a17","resolution":{"observed_at":"2026-05-14T19:29:23.924090Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.12964","last_updated":"2026-05-25T05:34:21Z","snapshot_observed_at":"2026-07-06T23:24:37.915639Z","submitted_at":"2026-05-13T03:58:01Z","title":"Asymmetric Flow Models","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T22:07:44.850763Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.12964"},"observation_digest":"sha256:29685dd144286c4480972a6f9f26d5ce1130b680acd68dfbdc297fa5cca413ec","observation_id":"b12948fb-6696-493b-8bcf-6ec396fa12ef","resolution":{"observed_at":"2026-07-01T14:15:47.406557Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.15741","last_updated":"2026-06-03T01:59:39Z","snapshot_observed_at":"2026-07-06T23:27:01.213106Z","submitted_at":"2026-05-15T08:51:55Z","title":"HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-20T19:08:26.689023Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.15741"},"observation_digest":"sha256:717daca550bf4a5139ec710bf96544f8ef19534757c7cfe71499c712e74355a6","observation_id":"33f02cce-5694-444a-83e3-4e42a1cd5c09","resolution":{"observed_at":"2026-05-20T19:08:54.002743Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.15741","last_updated":"2026-06-03T01:59:39Z","snapshot_observed_at":"2026-07-06T23:27:01.213106Z","submitted_at":"2026-05-15T08:51:55Z","title":"HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-30T19:33:53.876614Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.15741"},"observation_digest":"sha256:1d5e1a33491d1d657b6b829d84ca9a903d91518264f99c9e9b2c600c4fa210ee","observation_id":"d455d491-5e86-40fa-99c1-474b3428346d","resolution":{"observed_at":"2026-06-30T19:35:00.962336Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.17759","last_updated":"2026-05-18T02:25:07Z","snapshot_observed_at":"2026-08-01T22:43:12.616139Z","submitted_at":"2026-05-18T02:25:07Z","title":"FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-20T12:43:58.746650Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.17759"},"observation_digest":"sha256:91b3f4efedeed9c73ff35c6d447d1548dadad67ef0e2b1e2bfb40305298c3487","observation_id":"3a091a2e-675e-4e5f-a2b9-d9a7c3684fe4","resolution":{"observed_at":"2026-05-20T12:48:17.677739Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.18267","last_updated":"2026-07-24T06:29:36Z","snapshot_observed_at":"2026-08-02T13:49:17.490757Z","submitted_at":"2026-05-18T12:03:41Z","title":"SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-20T11:59:54.139888Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.18267"},"observation_digest":"sha256:d9cc084b220b5ccd5d57d03da2beee1c253db977d1ee5fb0b8bba7b014e673f3","observation_id":"c531d560-3869-45a7-be4e-b1b8f0ee9081","resolution":{"observed_at":"2026-05-20T12:03:15.352504Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.18267","last_updated":"2026-07-24T06:29:36Z","snapshot_observed_at":"2026-08-02T13:49:17.490757Z","submitted_at":"2026-05-18T12:03:41Z","title":"SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-30T18:39:40.667006Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.18267"},"observation_digest":"sha256:f7094b3cb60adb23c3f9c2b1fda28f9848b73cf16f0cc2466a1a6f4cc8c9c76c","observation_id":"1088a42b-88dd-4121-a8a2-b4b02710f666","resolution":{"observed_at":"2026-06-30T19:15:01.289511Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-02T13:49:19.198371Z","title":"Pixelflow: Pixel-space generative models with flow,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.18267","last_updated":"2026-07-24T06:29:36Z","snapshot_observed_at":"2026-08-02T13:49:17.490757Z","submitted_at":"2026-05-18T12:03:41Z","title":"SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T13:49:19.198371Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.18267"},"observation_digest":"sha256:c991f81146361efebdfa9318a621e55be806d08b1c2cab1328d0cdb9ed392188","observation_id":"5a83be2e-c6ac-4a20-958d-7d3fa9f2485d","resolution":{"observed_at":"2026-08-02T13:49:19.198371Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.18749","last_updated":"2026-05-18T17:59:10Z","snapshot_observed_at":"2026-08-01T11:03:45.027975Z","submitted_at":"2026-05-18T17:59:10Z","title":"WavFlow: Audio Generation in Waveform Space","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-20T07:33:35.243337Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.18749"},"observation_digest":"sha256:96b58c93d0ebb3f73934d2cb458a7208f6e113cbdcdc618067afbf91842b4f62","observation_id":"971fff5d-7441-4db5-b29d-9003b0f09df4","resolution":{"observed_at":"2026-05-20T07:38:09.607423Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.21981","last_updated":"2026-05-21T04:21:43Z","snapshot_observed_at":"2026-07-06T23:32:20.708664Z","submitted_at":"2026-05-21T04:21:43Z","title":"RiT: Vanilla Diffusion Transformers Suffice in Representation Space","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-22T07:50:29.461854Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.21981"},"observation_digest":"sha256:2af0dedead2106c108f8d22d98a34fcf12143322da1dcbcdf622f56d24594228","observation_id":"f7ceb1c0-0e26-4087-ac9e-0bedd30106b9","resolution":{"observed_at":"2026-05-22T07:51:15.906757Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.23531","last_updated":"2026-07-31T12:20:30Z","snapshot_observed_at":"2026-08-05T23:10:43.007996Z","submitted_at":"2026-05-22T11:50:40Z","title":"PixIE: Prompted Pixel-Space Low-Light Image Enhancement","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-25T05:10:40.638498Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.23531"},"observation_digest":"sha256:7a3f91490f1c0fc4b762f3914dd9966bb4ed1859f1e2c9e190ed5de9cd8f0776","observation_id":"00ed65ea-bf60-4218-a9e0-768b54b86b3d","resolution":{"observed_at":"2026-05-25T05:15:22.718039Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2605.31604","last_updated":"2026-07-03T09:50:38Z","snapshot_observed_at":"2026-08-03T15:39:37.184662Z","submitted_at":"2026-05-29T17:59:55Z","title":"Representation Forcing for Bottleneck-Free Unified Multimodal Models","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-28T22:54:10.460872Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.31604"},"observation_digest":"sha256:aa82bdc33ba4e0c8ff94c0919bf4135c9e205f4559d4f9269b7595bd9895e796","observation_id":"3b25fb24-34ca-4423-ac29-70b2a65020eb","resolution":{"observed_at":"2026-07-01T19:16:00.909535Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-12T15:31:57.426559Z","title":"PixelFlow: Pixel-space generative models with flow.arXiv preprint arXiv:2504.07963, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.31604","last_updated":"2026-07-03T09:50:38Z","snapshot_observed_at":"2026-08-03T15:39:37.184662Z","submitted_at":"2026-05-29T17:59:55Z","title":"Representation Forcing for Bottleneck-Free Unified Multimodal Models","version":4},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-12T15:31:57.426559Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2605.31604"},"observation_digest":"sha256:1139048cb3520c9c4d6b56daa1228de640ebbe0a31178446152e91f2e916afc4","observation_id":"5d53b2b8-b652-48ba-9a3d-45cb3819a60d","resolution":{"observed_at":"2026-07-12T15:31:57.426559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.00094","last_updated":"2026-07-01T12:56:35Z","snapshot_observed_at":"2026-07-06T23:40:51.363776Z","submitted_at":"2026-05-25T08:43:14Z","title":"Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-29T22:44:39.440271Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.00094"},"observation_digest":"sha256:aa806e582106b1ca20675df2842984f4733fb741180c7d3e81bf397e4edea5d1","observation_id":"844f4028-8eb0-4933-a845-37dae1691d51","resolution":{"observed_at":"2026-06-29T22:54:01.507377Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.00094","last_updated":"2026-07-01T12:56:35Z","snapshot_observed_at":"2026-07-06T23:40:51.363776Z","submitted_at":"2026-05-25T08:43:14Z","title":"Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-02T23:11:14.733439Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.00094"},"observation_digest":"sha256:052214230ba2359441a62829a819811f9396ca6b8e53183c09efd79d3f2ff354","observation_id":"f0721125-b748-42db-ba71-0aa29686c64d","resolution":{"observed_at":"2026-07-02T23:17:28.991970Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.03455","last_updated":"2026-06-02T10:33:20Z","snapshot_observed_at":"2026-08-05T18:48:21.902772Z","submitted_at":"2026-06-02T10:33:20Z","title":"WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-28T08:18:42.002083Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.03455"},"observation_digest":"sha256:ab66b832cdb6a35f05c9f1dce86bfa48415224be66abe8ecdc9ea7d7e8435a1d","observation_id":"6218d65a-65a5-4d6e-b949-71cc7d3294f7","resolution":{"observed_at":"2026-07-02T05:16:39.840803Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.22527","last_updated":"2026-06-21T14:25:50Z","snapshot_observed_at":"2026-07-29T19:58:03.414249Z","submitted_at":"2026-06-21T14:25:50Z","title":"Trajectory Forcing: Structure-First Generation with Controllable Semantic Trajectories","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-26T10:33:22.625544Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.22527"},"observation_digest":"sha256:35efcc2bdd0123a8b4a068668e94cc7548ff9bf7a64fd7cf509b8ca3cd8fc51e","observation_id":"70659317-7623-4417-a4c9-fd03af2ceed8","resolution":{"observed_at":"2026-07-04T09:09:42.660449Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.26016","last_updated":"2026-07-08T10:57:01Z","snapshot_observed_at":"2026-08-02T07:36:10.167129Z","submitted_at":"2026-06-24T16:37:10Z","title":"MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-25T19:34:02.046104Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.26016"},"observation_digest":"sha256:8c4f5a45f5c239f358e848d5614b7abc722b128a468f7dbc21541fbff76b20b3","observation_id":"67059dbf-de4e-4ed6-90c0-adc6153ab7cc","resolution":{"observed_at":"2026-07-04T20:50:11.502044Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.26016","last_updated":"2026-07-08T10:57:01Z","snapshot_observed_at":"2026-08-02T07:36:10.167129Z","submitted_at":"2026-06-24T16:37:10Z","title":"MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-01T06:27:24.992386Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.26016"},"observation_digest":"sha256:755bda5599420629ceb199f4271d0438f53f184b2ff105a5f9834db381513bf8","observation_id":"c0c80e19-7e48-4409-b267-fe1135444e2c","resolution":{"observed_at":"2026-07-01T09:35:40.208196Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-12T12:07:02.175855Z","title":"arXiv preprint arXiv:2504.07963 (2025) 10","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.26016","last_updated":"2026-07-08T10:57:01Z","snapshot_observed_at":"2026-08-02T07:36:10.167129Z","submitted_at":"2026-06-24T16:37:10Z","title":"MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-12T12:07:02.175855Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.26016"},"observation_digest":"sha256:91312d88b38e4b6ee49bb67083bbd8db0b3c59b9bf676938aca7ff0d9b167e40","observation_id":"83c26c5e-f3d6-4798-aeba-d977bae1368d","resolution":{"observed_at":"2026-07-12T12:07:02.175855Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.27760","last_updated":"2026-06-26T06:39:06Z","snapshot_observed_at":"2026-07-31T06:11:06.764017Z","submitted_at":"2026-06-26T06:39:06Z","title":"PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-29T04:31:57.169935Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.27760"},"observation_digest":"sha256:e65f92c77ba3da3c69d6eb1e9a15ae054b413c404b570f9b58076dac80563041","observation_id":"e5b0c087-cfba-4d25-bf46-dcd9a06a93ab","resolution":{"observed_at":"2026-06-29T20:03:57.201159Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2606.27978","last_updated":"2026-06-26T11:27:39Z","snapshot_observed_at":"2026-08-08T23:47:35.895010Z","submitted_at":"2026-06-26T11:27:39Z","title":"Parallel Rollout Approximation for Pixel-Space Autoregressive Image Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-29T04:58:23.066578Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2606.27978"},"observation_digest":"sha256:755ba5c3a7bc66f3982861b2869432c6cf8c1320a55ab6c9497705eca65f5178","observation_id":"cad54187-286f-419d-93e8-553daec3db32","resolution":{"observed_at":"2026-06-29T19:03:52.176135Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2607.00647","last_updated":"2026-07-01T09:01:13Z","snapshot_observed_at":"2026-07-07T00:06:20.346610Z","submitted_at":"2026-07-01T09:01:13Z","title":"Not All Prediction Targets Keep Training-Free Diffusion Guidance on the Manifold","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-02T14:33:12.091631Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.00647"},"observation_digest":"sha256:3a209c9a193619094587360de480115a08c32af6f4de1d2e23bff3d0fd402292","observation_id":"a1c37480-c095-4b46-b8e4-d9aedcf42d1f","resolution":{"observed_at":"2026-07-02T14:37:03.125398Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":"2504.07963","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-04T20:50:11.498748Z","title":"arXiv preprint arXiv:2504.07963 (2025)","venue":null,"work_id":"1beb1a44-0887-4a87-93c8-5dca148563bd","year":2025},"citing_paper":{"arxiv_id":"2607.01803","last_updated":"2026-07-04T06:58:16Z","snapshot_observed_at":"2026-08-02T02:22:21.215897Z","submitted_at":"2026-07-02T07:18:37Z","title":"PixGS: Pixel-Space Diffusion for Direct 3D Gaussian Splat Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-03T16:13:41.928049Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.01803"},"observation_digest":"sha256:ca6bf23dccc24adb48d02d21051d5f23c8e503b93ec3910a93d14d64a5647cb5","observation_id":"1eaa3aa7-0d41-4673-83fe-3ac8cc16f5f6","resolution":{"observed_at":"2026-07-03T16:18:37.413254Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-07-12T08:36:06.846852Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.01803","last_updated":"2026-07-04T06:58:16Z","snapshot_observed_at":"2026-08-02T02:22:21.215897Z","submitted_at":"2026-07-02T07:18:37Z","title":"PixGS: Pixel-Space Diffusion for Direct 3D Gaussian Splat Generation","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-12T08:36:06.846852Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.01803"},"observation_digest":"sha256:f1dc229d6a63d64ac9af7fbd7559d71701c9bd65efbf7fc1376e16f41b9bd0e8","observation_id":"c8af4c54-6bc1-44db-a7ed-cdb3b38941c1","resolution":{"observed_at":"2026-07-12T08:36:06.846852Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-01T17:35:37.530690Z","title":"Pixelflow: Pixel-space generative models with flow,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17585","last_updated":"2026-07-22T07:24:13Z","snapshot_observed_at":"2026-08-06T07:20:20.809986Z","submitted_at":"2026-07-20T06:04:08Z","title":"Pixel-Space Diffusion Transformers","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-01T17:35:37.530690Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.17585"},"observation_digest":"sha256:f930b2eaccb1e7a652315cd6cb17c24706c5aec2d01e70dd6829e449c5355ad0","observation_id":"91600045-db75-4a32-833b-88bb88492873","resolution":{"observed_at":"2026-08-01T17:35:37.530690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-01T15:16:50.162371Z","title":"Pixelflow: Pixel-space generative models with flow.arXiv preprint arXiv:2504.07963, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18510","last_updated":"2026-07-20T21:08:56Z","snapshot_observed_at":"2026-08-09T02:05:22.323664Z","submitted_at":"2026-07-20T21:08:56Z","title":"DuSPiT: Dual-Branch Sub-Patch Pixel Diffusion Transformer","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T15:16:50.162371Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.18510"},"observation_digest":"sha256:b15d6649538b8474fba076f873af2ca668bc38af43bda567e1c13a457b4db368","observation_id":"4e65f104-f812-4515-9ff6-f076f45f0d7d","resolution":{"observed_at":"2026-08-01T15:16:50.162371Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-01T11:10:14.258534Z","title":"Pixelflow: Pixel-space generative models with flow,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19986","last_updated":"2026-07-22T10:19:43Z","snapshot_observed_at":"2026-08-08T13:29:52.628835Z","submitted_at":"2026-07-22T10:19:43Z","title":"STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-01T11:10:14.258534Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.19986"},"observation_digest":"sha256:aa8420e745aa518136fb06e9b4a0400f859ed81fd260538eec4b1e131ce24343","observation_id":"a55ce2ce-6ebc-4142-8cc2-5980d9b2f2e8","resolution":{"observed_at":"2026-08-01T11:10:14.258534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-01T04:30:08.016742Z","title":"arXiv preprint arXiv:2504.07963 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22531","last_updated":"2026-07-24T17:59:39Z","snapshot_observed_at":"2026-08-07T13:04:18.211748Z","submitted_at":"2026-07-24T17:59:39Z","title":"Twins: Learn to Predict Unified Representations with Focal Loss","version":1},"reference_index":235,"source":"arxiv_source","source_observed_at":"2026-08-01T04:30:08.016742Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.22531"},"observation_digest":"sha256:c26b4cc8e0dff6b9f5e98bf00efd0c1b0544c3e3f43b48c2a8de1e67169af479","observation_id":"709b9f00-4e41-4c09-8b0a-2b0aab8b7dcd","resolution":{"observed_at":"2026-08-01T04:30:08.016742Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-03T00:34:35.378286Z","title":"PixelFlow: Pixel-space generative models with flow","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.28760","last_updated":"2026-07-30T18:26:19Z","snapshot_observed_at":"2026-08-10T00:00:29.055278Z","submitted_at":"2026-07-30T18:26:19Z","title":"WaiT for the Signal: Simple Frequency-Aware Flow-Matching","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T00:34:35.378286Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.28760"},"observation_digest":"sha256:e23400b384569692b18b0cee8bee67db9640d23f88f1621977f7a140ac8ac306","observation_id":"9a91fa73-b45e-4993-85a6-9d314ee63615","resolution":{"observed_at":"2026-08-03T00:34:35.378286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-03T13:23:48.840199Z","title":"arXiv preprint arXiv:2504.07963 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.29122","last_updated":"2026-07-31T07:52:08Z","snapshot_observed_at":"2026-08-08T01:44:11.895032Z","submitted_at":"2026-07-31T07:52:08Z","title":"A Frozen Pixel-Space Diffusion Model Can Guide Itself with Its Own Samples","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-03T13:23:48.840199Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2607.29122"},"observation_digest":"sha256:316936a73e5bc4496cbca2e72dd8559b3a0bf2dd47a8d284238358bb129c3b65","observation_id":"746dbf4f-9a3b-4b7e-b40a-fea396f58002","resolution":{"observed_at":"2026-08-03T13:23:48.840199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-06T00:24:08.392628Z","title":"arXiv preprint arXiv:2504.07963 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.01306","last_updated":"2026-08-02T15:20:55Z","snapshot_observed_at":"2026-08-09T23:24:20.476591Z","submitted_at":"2026-08-02T15:20:55Z","title":"SPAE: Spectrally Guided Autoencoder for Pretrained Visual Latents","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T00:24:08.392628Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2608.01306"},"observation_digest":"sha256:8b55fd6c3a6bea26f5e5b2fa5898e8ee5340f5838b472112f1e03feb4a62eeb9","observation_id":"c4575f3d-7257-43d8-a450-e88e8e5747dd","resolution":{"observed_at":"2026-08-06T00:24:08.392628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-06T22:14:13.052073Z","title":"arXiv preprint arXiv:2504.07963 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04557","last_updated":"2026-08-05T07:51:35Z","snapshot_observed_at":"2026-08-09T14:12:27.633701Z","submitted_at":"2026-08-05T07:51:35Z","title":"VoxStruct3D: Structure-Leading Flow Matching for Voxel-Space 3D MRI Synthesis","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T22:14:13.052073Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2608.04557"},"observation_digest":"sha256:2fcc1956bfa36ffc60c55068993faeaab9cc09266c9e369d32c309207af26829","observation_id":"0440dd51-f5d6-49e3-84cb-35fe107b3c7f","resolution":{"observed_at":"2026-08-06T22:14:13.052073Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-07T23:08:32.719122Z","title":"arXiv preprint arXiv:2504.07963 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05811","last_updated":"2026-08-07T08:39:46Z","snapshot_observed_at":"2026-08-10T10:09:47.066547Z","submitted_at":"2026-08-06T09:44:00Z","title":"Energy-Guided Flow Matching","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T23:08:32.719122Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2608.05811"},"observation_digest":"sha256:130b0f7e375753822e68d786a47f25c3bf89ddfa09862f9f48f012e9aad42cd5","observation_id":"dadeaed1-9458-4ef8-885a-d5d663f8cb2f","resolution":{"observed_at":"2026-08-07T23:08:32.719122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07963","snapshot_observed_at":"2026-08-10T04:33:41.230759Z","title":"arXiv preprint arXiv:2504.07963 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05811","last_updated":"2026-08-07T08:39:46Z","snapshot_observed_at":"2026-08-10T10:09:47.066547Z","submitted_at":"2026-08-06T09:44:00Z","title":"Energy-Guided Flow Matching","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T04:33:41.230759Z"},"links":{"cited_paper":"/paper/2504.07963","citing_paper":"/paper/2608.05811"},"observation_digest":"sha256:7cc9e45900f4bfcfe495d2378d561d7783054569cb240a6e34f051e29e7becc2","observation_id":"b6f4a311-364a-40f3-b5bf-8a3ec7c1193f","resolution":{"observed_at":"2026-08-10T04:33:41.230759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2504.07963/citation-record","integrity":"/paper/2504.07963/integrity","json":"/paper/2504.07963/citation-record.json","paper":"/paper/2504.07963"},"outbound":[],"paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T06:46:29.564428Z","submitted_at":"2025-04-10T17:59:56Z","title":"PixelFlow: Pixel-Space Generative Models with Flow"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 54 inbound Pith citation observations for arXiv:2504.07963."}