{"as_of":"2026-08-07T18:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e20589ca0da704fc0f5ace4fb82e96cff9a507331134b2b3e32bb46d5feef210","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":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":52,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:14:13.052073Z","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":"2026-08-07T16:06:44.998749Z","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":"2026-08-06T10:59:51.682500Z","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:d02bca6b39b4a27fdac8fa42a9f06e09859bdaa5c534eb0abc5987a28fee3068","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":"2026-08-07T16:06:44.998749Z","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":"sha256:3959a2c35af116cd7fe52581136c831fb6b270e1fd929c3a6ec334fd64a6f9ab","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:17fdd0b8228fbef06ecbd5947b68c4909158e795731a484b62331830a6cdeeed","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:79749df6c51474c2fc337216511a69756c68ff768e405e08b32f03d8ae1b10ce","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"2026-08-07T08:44:50.659416Z","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:eac427113956f1152786143275b92bc93cf8e993be92745fcb8c74ba8acd49df","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":"2026-08-07T16:06:44.998749Z","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":"sha256:1de0879d9bc7a83e26d0eb435d841f58748a2646be985ff3b610c4e42dda1573","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:f11a2e947bb3ab874c9c3545f96a670ab37b4a16e239a9fb3428b6dcf7587c71","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":"2026-08-07T16:06:44.998749Z","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":"2026-07-15T14:00:06.335510Z","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":"sha256:4344cb8502d6508a5f4907abce32e25ec034e010be0ef31f5d66a8fd269783d3","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":"2026-08-07T16:06:44.998749Z","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":"sha256:4792f4d4d317f5f5ecd02d0e77885df979323e9df18655fa2174aea731d91d4b","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:5cfca4d25d0239f883040875aa92182817ed9bd0ed0de8702b39645d0a0bd1c7","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:8644c30766938c34f566329258a1d6d0ed72a3d98a872e32eab6c900a7b3505c","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:ec244982cbbb8cb3dd82a0abcb9cf1a484ed837244f3172bc144f3c7d57c802d","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:a645d38b1e62f6461b0dc65db9dcbbe1f37b3a79370c9d0ffd5f9501f5c276a5","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:9dc927b05cd6470f22d2812f5c415d64d220a5dad2a73471a2f830db6540ba4e","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:73403391172c01530529f57e5267916b300f6b588f511bdef7cac5369dfa6ebc","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:f8d9ba7a679ee2b85ee124fa27df6a99b4ad0304772c11a8c8ec392417bd9ada","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:60018dc339c6caa9e0e7fc84e7503019687313fa88bccbaeb46710ecbceea3ba","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:8a717aff2d14a3f3f3567dff65b4fe9044b5893a0b81ca24bc4c8565c8613307","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":"2026-08-07T16:06:44.998749Z","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":"sha256:69d43f8e387a5d39b8e1c996799573dceddfd84a9ca3282d31ce077af3432982","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:cdd10b7cfff42b566e22a5a86207de79499e0571c384a0a42ef3afda49ba1e17","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:2af0ba3ddb4b1a03d226760723cbf7595eb96ee96d004da5f0c8065640d28588","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:093303cc02c591d324f48b0760d783c1f9e3a6838e1eaa76bd9128698b454c98","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:e603de82c9cdffedb02a9c868cf1c832f8169b3a22336b117c90dd82143ff03a","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:77b1bd79ef43d9dfa2b975e4e217767f91f082c9f26973466b14e5212331bb91","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:7c451ccd6a5c872adb92e7d20df5d69249c421d34fb5b1fa82fb4733f9dadaf8","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:aa76af6fe8c96af5215c0dff7fe2891b31afe4698c81a958289b67d3f81edf7d","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:d90f4b01c51899dc928dc627ec2f0d0e716f302d5c831617ef18fb5bc8606366","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":"2026-08-07T16:06:44.998749Z","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":"sha256:8cd44e6449ab864db573cae4a390605b008a735f59b88e5d5da5cb349edba7e5","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:1de92bfa70e8300b82d33ea4c56e5c46fa79d059ab4b1cd90615c5eef79718d4","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:50890996348c1bf7dceb5e68fb311d25db48d1f39a118c864e2ce25e3f2a8af4","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:3232782ae88b453af91170da641ee0b00272299b6860da71bb2b28c6222758c1","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:0d5eecfb73a23d0979fab5b8dfb1a80c99a4d93367be1c74011e0964fd17c8bb","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":"2026-08-07T16:06:44.998749Z","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":"sha256:93ac2f743b93f90f1530023c77f6554dc4979cd6221223097136b99c7c487cbe","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:299090abcd95faee7dfe316e84fc613ec908345f40e550a15ef8461f8e27ce20","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:c317c9379e52ee188cfbcf3bd59b9ac608b118589c718067280b868a55171705","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:1c9f0c083e5161fea69077749dc8113b45e1272cb53d3fd99918cc65a80d3c44","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:680da622156036cdefecbd2f33aad1a5e8ddd762958bd22b35d054de25049dd7","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:1ccaeea008551bf4b80d2d56b28571efe7f4395f7457548822e3056e97595421","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"sha256:922e026a9853de9a78d4f41396ef1a91e0ca3ccdbf4329cc1f7824a60182a7f9","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":"2026-08-07T16:06:44.998749Z","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":"sha256:7380636fa469bda98666a0da1413f2e25a10008e94a3ed34fdc122f5fc62966b","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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":"2026-08-03T23:56:14.294002Z","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":"sha256:3e48380e238c2f7b1c7c5f88f075361151b313368359b410f303170922dfdf8e","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:dff4bbd1455e822e42ee0485af175c547d29b6026dbd10c7add52b64da4ab1d9","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:e4745b8b90df01de80a82d04a56d8a2f1eae1f27a702fad1edcfc2f2c157f4dc","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07963","last_updated":"2025-04-10T17:59:56Z","snapshot_observed_at":"2026-08-07T16:06:44.998749Z","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:c1d393c0602bd1f8b22521f2660c6beb33bda89db1cacf15409d59b451e89f63","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":"2026-08-07T16:06:44.998749Z","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:cf799daae6b8cd1a9fb4a2b305e3c6050b062dec5a94a374c499f697d471bb59","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":"2026-08-07T16:06:44.998749Z","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":"2026-08-06T08:17:30.075438Z","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":"sha256:7bfa99d669362d592e03e26aae301db56da873616f7b42d679d009e19557d6bb","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":"2026-08-07T16:06:44.998749Z","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":"2026-08-06T19:49:25.842784Z","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:aca9712dcdf97a9899c0343d512e589b9b21680d59d35d25f524364109865aa1","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":"2026-08-07T16:06:44.998749Z","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:aaee9052eac5f64c6fd03ea589c4dd2e0ec222fca4f40fd1af52673a0045278d","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":"2026-08-07T16:06:44.998749Z","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":"2026-08-06T02:19:22.424309Z","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:a83cc4c03e829dd0a99ffec29cf1373131bbfc8733fc07cc56223ce122331bab","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":"2026-08-07T16:06:44.998749Z","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":"2026-08-05T23:12:43.939239Z","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:c462844f1bcd0b46677c3fec13aa30f71a3c1d49280d2ab5878f843e89c7e447","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":"2026-08-07T16:06:44.998749Z","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":"2026-08-06T23:26:14.220474Z","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":"sha256:66a482fc0271029a6615c8f57889a2ae196086ae1a9d483b35b15ec10ebf8840","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":"2026-08-07T16:06:44.998749Z","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":"2026-08-07T17:50:08.032945Z","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:a42e777bd8193cda0c057f0533fae3510a5fa6126260671b2816b87e7d993593","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"}}],"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":"2026-08-07T16:06:44.998749Z","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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 52 inbound Pith citation observations for arXiv:2504.07963."}