{"as_of":"2026-08-06T17:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f0a545b2dc44dfc321931892db8da8e7816b1e013a360772ad843ce4f01f8ab9","coverage":[{"denominator":67,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":67,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T17:51:54.183590Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T13:40:25.697869Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T18:51:07.796875Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"cited_work":{"arxiv_id":"2512.08125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2512.08125","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Available: https://arxiv.org/abs/2512.08125","venue":null,"work_id":"c50d4a1e-2cf0-4460-b2e0-426cfa889acf","year":null},"citing_paper":{"arxiv_id":"2604.22005","last_updated":"2026-04-23T18:49:06Z","snapshot_observed_at":"2026-07-06T23:08:28.444591Z","submitted_at":"2026-04-23T18:49:06Z","title":"Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T13:40:25.697869Z"},"links":{"cited_paper":"/paper/2512.08125","citing_paper":"/paper/2604.22005"},"observation_digest":"sha256:194de02265f0517f9d649c36172a7bae8c1e449be378697bc57c3dbf61e5e3eb","observation_id":"ecc36725-fbd3-40b7-8181-aae2347e4e40","resolution":{"observed_at":"2026-05-26T03:04:08.376947Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2512.08125/citation-record","integrity":"/paper/2512.08125/integrity","json":"/paper/2512.08125/citation-record.json","paper":"/paper/2512.08125"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08797","last_updated":"2025-10-09T00:43:44Z","snapshot_observed_at":"2026-07-06T15:03:52.079498Z","submitted_at":"2023-03-15T17:43:42Z","title":"Stochastic Interpolants: A Unifying Framework for Flows and Diffusions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08797","snapshot_observed_at":"2026-08-03T17:51:50.603012Z","title":"Stochastic interpolants: A unifying framework for flows and diffusions.arXiv preprint arXiv:2303.08797,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:50.603012Z"},"links":{"cited_paper":"/paper/2303.08797","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:c2a561c3dda2a537ebd396f4b5f8fcf3258839c8e61664808de5230d1a22694d","observation_id":"0a46af35-47b0-4e2f-adfb-cbc9043cb37b","resolution":{"observed_at":"2026-08-03T17:51:50.603012Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:50.678178Z","title":"Blended diffusion for text-driven editing of natural images","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:50.678178Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:ceadefbdc652d928e023072292eae66dcc298929c29c31da4e22dd66cc48623e","observation_id":"23b81ef7-7cd5-4302-b374-87d5e4845b45","resolution":{"observed_at":"2026-08-03T17:51:50.678178Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:50.822409Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:50.822409Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:b2309994f3d92d42f7474003426852177dd483c4e14af268397ba62b4a788cdd","observation_id":"ffe590fa-57f7-41bc-897c-2be88249e3c5","resolution":{"observed_at":"2026-08-03T17:51:50.822409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14017","last_updated":"2024-07-21T11:19:38Z","snapshot_observed_at":"2026-08-04T10:26:46.539800Z","submitted_at":"2024-02-21T18:56:03Z","title":"D-Flow: Differentiating through Flows for Controlled Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14017","snapshot_observed_at":"2026-08-03T17:51:50.963485Z","title":"D-flow: Differentiating through flows for controlled generation.arXiv preprint arXiv:2402.14017, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:50.963485Z"},"links":{"cited_paper":"/paper/2402.14017","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:3eb28d52cd8874704702f35d26a4346e45cb567152fe1e9c34196177ab88d6c8","observation_id":"2b960543-0043-45ca-860a-762ab7a5a88e","resolution":{"observed_at":"2026-08-03T17:51:50.963485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:51.116774Z","title":"Masactrl: Tuning-free mu- tual self-attention control for consistent image synthesis and editing","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:51.116774Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:c0da1f7881e292e819542d407030382ef48ecb74136ce618d42e7bd3a0a113ec","observation_id":"afe25d64-f288-47bd-8744-a894b3296d09","resolution":{"observed_at":"2026-08-03T17:51:51.116774Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:51.239842Z","title":"Pix2video: Video editing using image diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:51.239842Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:916ca4ca93bb8bc9bb52aac52721a36a5837af67ba8c4b9fd71badc21160af88","observation_id":"34eec0de-1f3f-411c-af0c-dd051a633506","resolution":{"observed_at":"2026-08-03T17:51:51.239842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:51.364776Z","title":"Ilvr: Conditioning method for denoising diffusion probabilistic models.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 14347–14356, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:51.364776Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:1e999e387b26be55022472d7df22187638c91aae9bad2189cc13483f1047e4ef","observation_id":"cbcc0415-1fab-4d69-9fa0-b692c2246c5c","resolution":{"observed_at":"2026-08-03T17:51:51.364776Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:51.537919Z","title":"Stargan v2: Diverse image synthesis for multiple domains","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:51.537919Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:e128ca521dbb6710ade8c2dd6542d7c7a0cb2fd46f7e25d9f7d71373d7696b2f","observation_id":"b99bffbc-f8a3-4567-b53d-d0dfa90b787a","resolution":{"observed_at":"2026-08-03T17:51:51.537919Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14687","last_updated":"2024-05-20T04:23:45Z","snapshot_observed_at":"2026-08-03T03:59:22.374270Z","submitted_at":"2022-09-29T11:12:27Z","title":"Diffusion Posterior Sampling for General Noisy Inverse Problems","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14687","snapshot_observed_at":"2026-08-03T17:51:51.779297Z","title":"Diffusion posterior sam- pling for general noisy inverse problems.arXiv preprint arXiv:2209.14687, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:51.779297Z"},"links":{"cited_paper":"/paper/2209.14687","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:8281bcf0c996930a59d509020824bd59d75a2c633bb527ceb5af8a5c302527bb","observation_id":"830fa764-70f0-4f7c-b6e1-ff6e8f3d97b3","resolution":{"observed_at":"2026-08-03T17:51:51.779297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:51.921922Z","title":"Fluxs- pace: Disentangled semantic editing in rectified flow mod- els","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:51.921922Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:b76d2b920101580e9aeb81bbb4f7097112e7ed1b6325d6a53c256a7d8b564dab","observation_id":"be14b42b-6623-4f97-9e3a-e70ee825d2c8","resolution":{"observed_at":"2026-08-03T17:51:51.921922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.07517","last_updated":"2024-12-10T13:56:26Z","snapshot_observed_at":"2026-07-06T20:04:39.240950Z","submitted_at":"2024-12-10T13:56:26Z","title":"FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.07517","snapshot_observed_at":"2026-08-03T17:51:52.086212Z","title":"Fireflow: Fast inversion of rec- tified flow for image semantic editing.arXiv preprint arXiv:2412.07517, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.086212Z"},"links":{"cited_paper":"/paper/2412.07517","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:2aee050feacbee30d8a699da89e3a29bfda8860b4d5e49452e86c8a435af3266","observation_id":"49653e43-0684-4b08-8599-247fcfcb3b49","resolution":{"observed_at":"2026-08-03T17:51:52.086212Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.149477Z","title":"Diffusion models beat gans on image synthesis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.149477Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:58c27c6561633a7b65b7e1518219492e26452bd324b49fd1fadf8f7121297266","observation_id":"cefe2ba3-faeb-4250-bff2-05afee3cc70d","resolution":{"observed_at":"2026-08-03T17:51:52.149477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.196417Z","title":"guided-diffusion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.196417Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:3e36947adf610414c74e02fa20e127ac80d9f5f32bbf6353ae04529d427f7088","observation_id":"da6dd92c-8cee-4382-8f36-802c011b3613","resolution":{"observed_at":"2026-08-03T17:51:52.196417Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.251490Z","title":"Scaling recti- fied flow transformers for high-resolution image synthesis","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.251490Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:4e01f6824c6504c09302cce8a034403da50554ba5b17534ce3a3b44c16140b7b","observation_id":"0890af7b-06cc-486e-a2ef-c0c203fa01e7","resolution":{"observed_at":"2026-08-03T17:51:52.251490Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10373","last_updated":"2023-11-20T10:54:09Z","snapshot_observed_at":"2026-08-06T08:12:35.134201Z","submitted_at":"2023-07-19T18:00:03Z","title":"TokenFlow: Consistent Diffusion Features for Consistent Video Editing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10373","snapshot_observed_at":"2026-08-03T17:51:52.304554Z","title":"Tokenflow: Consistent diffusion features for consistent video editing.arXiv preprint arXiv:2307.10373, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.304554Z"},"links":{"cited_paper":"/paper/2307.10373","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:f3881a1c28092f32d38faf46ff05c5ae32d315479a1fa40e5bdd25c2c8ac07bf","observation_id":"e0ffe6c9-8ca9-403b-826f-686a050ba15b","resolution":{"observed_at":"2026-08-03T17:51:52.304554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.358815Z","title":"Gonzalez and Richard E","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.358815Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:370153ef3eb716faf27c95ae1f134ae9dd2b7a73ee5ad6de03a3265124534f26","observation_id":"64241eb5-1cdd-43ba-a6cc-8e7ecd53d3c8","resolution":{"observed_at":"2026-08-03T17:51:52.358815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.412772Z","title":"Nagy, and Dianne P","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.412772Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:c0635f10dcf51fec31715dbafd6d88722afe9467dc1224e6f7501afdadf61403","observation_id":"d6930838-ac92-471b-93fa-f4f448aa0a95","resolution":{"observed_at":"2026-08-03T17:51:52.412772Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.472023Z","title":"Prompt-to-prompt im- age editing with cross attention control.The Eleventh In- ternational Conference on Learning Representations (ICLR),","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.472023Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:3edcfaa964259e65537b57929c651ba376034a19b0a1f4d9ac7b4023b9d0f3dc","observation_id":"e1b78479-e64a-4682-b7a7-b8953cd14fd8","resolution":{"observed_at":"2026-08-03T17:51:52.472023Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.518862Z","title":"Style aligned image generation via shared atten- tion","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.518862Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:a5a29d618c6bd4e78d7d95f1cc8682d9917cb316d53838e1bce6c2e3647460e6","observation_id":"e96f015e-1a7d-4d5d-9eeb-962d9c07901c","resolution":{"observed_at":"2026-08-03T17:51:52.518862Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.573199Z","title":"Classifier-free diffusion guidance, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.573199Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:7d20a4919f9d483eb401553fa6aeb03d37eca4c095ae456f339f1037f9484db6","observation_id":"622d8be0-6eff-4e15-8e06-ad202fb08a68","resolution":{"observed_at":"2026-08-03T17:51:52.573199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.626089Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.626089Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:dc956a1d32ff308f4d15cef4e56be6095be758ce4e4689be335989b91110a93c","observation_id":"e04803f0-e90a-4f1e-9da1-a61f6611f9cf","resolution":{"observed_at":"2026-08-03T17:51:52.626089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.13109","last_updated":"2026-05-20T05:16:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-17T17:24:23Z","title":"UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.13109","snapshot_observed_at":"2026-08-03T17:51:52.681339Z","title":"Uniedit-flow: Unleashing inversion and editing in the era of flow models.arXiv preprint arXiv:2504.13109,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.681339Z"},"links":{"cited_paper":"/paper/2504.13109","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:7ddc0133431569c5ff20aefbd85d5de5a597c74d62bce6874f1c4f1cf607e6a0","observation_id":"4b8ef620-65f1-49b2-b758-379cd64758e3","resolution":{"observed_at":"2026-08-03T17:51:52.681339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10196","last_updated":"2018-02-26T15:33:34Z","snapshot_observed_at":"2026-07-06T06:06:26.276752Z","submitted_at":"2017-10-27T15:28:35Z","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10196","snapshot_observed_at":"2026-08-03T17:51:52.686802Z","title":"Progressive growing of gans for improved quality, stability, and variation.arXiv preprint arXiv:1710.10196, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.686802Z"},"links":{"cited_paper":"/paper/1710.10196","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:5c8b86b29832fcefe071c47621195e3a8baddfa4f0da378675ab713ebd7b7730","observation_id":"b8a6764f-9193-4e88-9afe-68c2cb9f8061","resolution":{"observed_at":"2026-08-03T17:51:52.686802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.707682Z","title":"Snips: Solving noisy inverse problems stochastically.Advances in Neural Information Processing Systems, 34:21757–21769,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.707682Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:831ac0b17477ff843a3490290378033ffb7c5b0b991b0981009efe5b7b124c2a","observation_id":"c64523a8-0ff7-4419-a934-e53369bd27da","resolution":{"observed_at":"2026-08-03T17:51:52.707682Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:52.867490Z","title":"Denoising diffusion restoration models.Advances in Neural Information Processing Systems, 35:23593–23606,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.867490Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:a8da7b336001df2c6f189edde0ad47c94ec0121a2a1271528350239910c209cd","observation_id":"c84f12ce-603c-4975-8911-c91d146c6a84","resolution":{"observed_at":"2026-08-03T17:51:52.867490Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.23145","last_updated":"2025-07-27T15:39:01Z","snapshot_observed_at":"2026-07-06T21:32:43.441417Z","submitted_at":"2025-05-29T06:33:16Z","title":"FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.23145","snapshot_observed_at":"2026-08-03T17:51:52.978201Z","title":"Flowalign: Trajectory-regularized, inversion-free flow- based image editing.arXiv preprint arXiv:2505.23145,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:52.978201Z"},"links":{"cited_paper":"/paper/2505.23145","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:6880a650d2c9fb8d349f65c1d6214437e8ff7bb67e24244dc02952913302239a","observation_id":"e099fe64-e5e4-4419-aeae-96d21286998f","resolution":{"observed_at":"2026-08-03T17:51:52.978201Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.067181Z","title":"Reflex: Text-guided editing of real images in rectified flow via mid-step feature extraction and attention 11 adaptation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.067181Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:5207b12a96ca8821bf492a8c3bb732b1dac28e77a968902b699d6eb26d8ffef2","observation_id":"1b7d6960-3f89-4549-9ccd-8fd602b8b67f","resolution":{"observed_at":"2026-08-03T17:51:53.067181Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.165418Z","title":"Kingma and Max Welling","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.165418Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:aec4561f3f574835986f43885fbf2b3d408422bf299e514445dc23015862c375","observation_id":"21a095b1-61b2-44c3-a012-4fd319c9ceb7","resolution":{"observed_at":"2026-08-03T17:51:53.165418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.256074Z","title":"Dual prompting image restoration with diffusion transformers","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.256074Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:ad5f395ed35356f462edaf1c65ad22077b52187b7d7af3bc791db8c26d6491a0","observation_id":"18dde52c-f4c9-4052-9386-1a9af98112b2","resolution":{"observed_at":"2026-08-03T17:51:53.256074Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.258966Z","title":"Flowedit: Inversion- free text-based editing using pre-trained flow models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.258966Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:b05531e8f3760acbd8561f53e253572035422c49cc40675750dcae92e9b5932e","observation_id":"0220f046-1534-46f3-a67a-94ec53d24768","resolution":{"observed_at":"2026-08-03T17:51:53.258966Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.335895Z","title":"FLUX.https://github.com/ black-forest-labs/flux, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.335895Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:409120dd9985109589d4fb33f64999832a9618685d469fa34f12a077043738f3","observation_id":"f880805f-9970-4e61-8fea-90ecdcd7eb41","resolution":{"observed_at":"2026-08-03T17:51:53.335895Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02747","last_updated":"2023-02-08T15:46:05Z","snapshot_observed_at":"2026-08-02T18:24:58.914589Z","submitted_at":"2022-10-06T08:32:20Z","title":"Flow Matching for Generative Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.02747","snapshot_observed_at":"2026-08-03T17:51:53.440806Z","title":"Flow matching for generative mod- eling.arXiv preprint arXiv:2210.02747, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.440806Z"},"links":{"cited_paper":"/paper/2210.02747","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:e09fcb406018f2af61f3a2febcc1e6eeb5ff08d41a28beb555d6b63cfe174467","observation_id":"656fba88-f205-4554-b924-b4142821c16f","resolution":{"observed_at":"2026-08-03T17:51:53.440806Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.552263Z","title":"Video-p2p: Video editing with cross-attention control","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.552263Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:b8df0b17a8dd63970b89b1ecbeb7083dcd7b78fd52d2565fe795feeaf147c314","observation_id":"63aa18c2-4bf5-4488-af89-1915fd5fed06","resolution":{"observed_at":"2026-08-03T17:51:53.552263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.03003","last_updated":"2022-09-07T08:59:55Z","snapshot_observed_at":"2026-07-06T13:49:40.974495Z","submitted_at":"2022-09-07T08:59:55Z","title":"Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.03003","snapshot_observed_at":"2026-08-03T17:51:53.592645Z","title":"Flow straight and fast: Learning to generate and transfer data with rectified flow.arXiv preprint arXiv:2209.03003, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.592645Z"},"links":{"cited_paper":"/paper/2209.03003","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:26578d531d9c81c33cef26cc70b709ef7a9f85798973f0001d0de197d5e661ec","observation_id":"7a6d2fed-5178-4257-aea1-d7b89f04c3b6","resolution":{"observed_at":"2026-08-03T17:51:53.592645Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.712247Z","title":"Deep learning face attributes in the wild","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.712247Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:26d41e16dd0ab01248710daa69e02a7de6a65e655ff92df464f8357252e0dc74","observation_id":"865b65ac-36fb-4884-9d4c-9c01759ac8ea","resolution":{"observed_at":"2026-08-03T17:51:53.712247Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02423","last_updated":"2025-09-09T07:43:19Z","snapshot_observed_at":"2026-08-03T18:54:30.811068Z","submitted_at":"2024-10-03T12:13:56Z","title":"PnP-Flow: Plug-and-Play Image Restoration with Flow Matching","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02423","snapshot_observed_at":"2026-08-03T17:51:53.816120Z","title":"Pnp-flow: Plug-and-play image restoration with flow matching.arXiv preprint arXiv:2410.02423, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.816120Z"},"links":{"cited_paper":"/paper/2410.02423","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:20ec8f45f5857014f377742b5f7cb428f9334b2cbecfd56377c5333542646789","observation_id":"5efbe621-e86e-4fbe-adb4-e43a42b6c8b9","resolution":{"observed_at":"2026-08-03T17:51:53.816120Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.856825Z","title":"SDEdit: Guided image synthesis and editing with stochastic differential equa- tions","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.856825Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:19b38f140d7329089ead418ebd67d6d588275fa7eeade6d82b2cd2ca9fdca7ba","observation_id":"0908ddab-69fb-49f8-9f4f-b61188540d54","resolution":{"observed_at":"2026-08-03T17:51:53.856825Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:53.923697Z","title":"T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:53.923697Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:b7064e6669a01c6e78cd656eee0bea28161047a63f0b513f698fbb750f621c6d","observation_id":"e0370a48-3b87-4cb0-af9a-0dc49850db41","resolution":{"observed_at":"2026-08-03T17:51:53.923697Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.009319Z","title":"Improved denoising diffusion probabilistic models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.009319Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:0969f149b3921bc4e58b1a3e1bf2d39224c72904c97cca79b9084bdfe5667ede","observation_id":"b31bddbe-adc3-43f2-8baa-e3b611044f14","resolution":{"observed_at":"2026-08-03T17:51:54.009319Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.037193Z","title":"Understanding the latent space of diffusion models through the lens of riemannian geometry","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.037193Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:052022e33443bd30f7f98d895b793897cc1c66921b49befb6a5c27a45f508963","observation_id":"77924f1f-3c2e-42ee-9cca-6946f01121ad","resolution":{"observed_at":"2026-08-03T17:51:54.037193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.083935Z","title":"Muckley, Ricky T","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.083935Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:5026a7e8bb745c75cec3498342f44a60077b87fa1302cf188855cbd35c457830","observation_id":"3f28887b-1331-4dba-ba45-4bb7c145511b","resolution":{"observed_at":"2026-08-03T17:51:54.083935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.092472Z","title":"Fatezero: Fus- ing attentions for zero-shot text-based video editing","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.092472Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:848138aca787a016f6ee316c240d87260a0ce3ab2a3f7696722a4ea9abe161b4","observation_id":"6f5d7c20-628b-4cff-a060-5bd7411c384c","resolution":{"observed_at":"2026-08-03T17:51:54.092472Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.116353Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.116353Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:c1727f743c3558cb9988a65ad3c5038ee43e444bf832f72e37d86207215dfee7","observation_id":"86a3f603-3223-4d2b-ba31-b420040d9fb2","resolution":{"observed_at":"2026-08-03T17:51:54.116353Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.122528Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.122528Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:fc612c47fb614a4b8d9af2778e15a1cad5325c25c375ac8c22ffcc1224096e6c","observation_id":"c0fc000d-f339-4874-a015-87c2a98112d1","resolution":{"observed_at":"2026-08-03T17:51:54.122528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.125296Z","title":"Semantic im- age inversion and editing using rectified stochastic differen- tial equations","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.125296Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:4583ea1e94a055d0eac0025cef7a3b60bbf7a19d57091e883d64af83f820a252","observation_id":"451825e1-74c2-4ad9-a6a5-bc8b44129fd5","resolution":{"observed_at":"2026-08-03T17:51:54.125296Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.127812Z","title":"Image super- resolution via iterative refinement.IEEE transactions on pattern analysis and machine intelligence, 45(4):4713–4726,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.127812Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:424646e99d2182ac26d3a73f6793ffde2cfc79f4dba5c5188db85ea7ad695b68","observation_id":"497dbcc6-61ab-4a00-97b5-e9df54c0323d","resolution":{"observed_at":"2026-08-03T17:51:54.127812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.130676Z","title":"Progressive prompt de- tailing for improved alignment in text-to-image generative models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.130676Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:41697da7a53e1bb4bfd1a9a534603a97bf0f1e045f35e17be2daefd2c51908b1","observation_id":"ac608de0-7d86-409f-a0d0-9593f0c2b203","resolution":{"observed_at":"2026-08-03T17:51:54.130676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.133090Z","title":"Fast high- resolution image synthesis with latent adversarial diffusion distillation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.133090Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:b5b602ceb47db2089d80f6c2f51d19bdacb000d1ee5b9273aa0993b57310b48d","observation_id":"6357fa3d-4f3c-4859-86b9-2e4119b77bb5","resolution":{"observed_at":"2026-08-03T17:51:54.133090Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.135555Z","title":"Diff2flow: Training flow matching models via dif- fusion model alignment","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.135555Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:592c45e8fb480dd2e01e546fca93cc34371a2118ab9cad8ab34dbe7967ca61a3","observation_id":"3ae5c445-9061-4aac-be2c-40d5435fba82","resolution":{"observed_at":"2026-08-03T17:51:54.135555Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.137967Z","title":"Parallel sampling of diffusion models.Ad- vances in Neural Information Processing Systems, 36:4263– 4276, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.137967Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:a04b1b411d339fd99938f7fe1827c76d8c9c680126970f473ad5bb01ed42dad1","observation_id":"b3fc4ed8-f7dc-4ede-bced-c022d0cbdb5a","resolution":{"observed_at":"2026-08-03T17:51:54.137967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.140540Z","title":"Solving inverse problems with latent diffusion models via hard data consistency.The Eleventh International Conference on Learning Representa- tions (ICLR), 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.140540Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:4c37d2396ada4094ea08f0a869db0dcb848969e1302c87e4bf32667459572756","observation_id":"06a89faf-30a6-44b7-8dfb-88289cf41cd4","resolution":{"observed_at":"2026-08-03T17:51:54.140540Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-07-06T10:01:50.133383Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-03T17:51:54.143289Z","title":"Denois- ing diffusion implicit models.arXiv:2010.02502, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.143289Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:d2ef2a6c0e03b3c33ac8d791eb4ff001ffa405e08ba5d9c49c28bf234b85504f","observation_id":"9d5ebdae-48b1-4e5e-963d-296e9287fe0d","resolution":{"observed_at":"2026-08-03T17:51:54.143289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.13456","last_updated":"2021-02-10T18:17:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-11-26T19:39:10Z","title":"Score-Based Generative Modeling through Stochastic Differential Equations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.13456","snapshot_observed_at":"2026-08-03T17:51:54.146092Z","title":"Score-based 12 generative modeling through stochastic differential equa- tions.arXiv preprint arXiv:2011.13456, 2020","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.146092Z"},"links":{"cited_paper":"/paper/2011.13456","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:2a854fb21e41f9dc9d36a89d56cca4e05fe485ae3b1b1f5c3020f3b16eda99b5","observation_id":"b3f56ed4-7ca6-4605-b967-f98b7e15f451","resolution":{"observed_at":"2026-08-03T17:51:54.146092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.148766Z","title":"Stable Diffusion 3.https://stability","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.148766Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:dc20d50960c43d91e753691281f888d357c036631d709188ba9790b893bc2b22","observation_id":"834968c5-a252-45db-9c89-001acfe147bc","resolution":{"observed_at":"2026-08-03T17:51:54.148766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.153917Z","title":"Plug-and-play diffusion features for text-driven image-to-image translation","venue":null,"work_id":null,"year":1921},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.153917Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:b60f99fee9c9343c3c7ef05a6fc691c512cd13efa623cbc3accface0187bff19","observation_id":"43e5383b-3bd6-455a-8105-d95c89afed77","resolution":{"observed_at":"2026-08-03T17:51:54.153917Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.156428Z","title":"Plug-and-play priors for model based re- construction","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.156428Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:7c8cbe6412d2742885da4bedebc5f299630be35ad4da6f02bbecccd631940964","observation_id":"c04feecf-f82e-4331-91ec-871a68f0e84e","resolution":{"observed_at":"2026-08-03T17:51:54.156428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.158761Z","title":"Edict: Exact diffusion inversion via coupled transformations","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.158761Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:7120233abeb978d4b36e926ee2aaf6caf8e84e86caeb4f2613b8c790b0a0bb50","observation_id":"26eb756a-19bd-47ec-9810-668a7cd5735a","resolution":{"observed_at":"2026-08-03T17:51:54.158761Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.161052Z","title":"Reconciling stochas- tic and deterministic strategies for zero-shot image restora- tion using diffusion model in dual","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.161052Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:74cb697969b64a2a23120d2abaf84d5b5e1afafee01090d0441d63e037dba760","observation_id":"4a9ae2f9-6a7a-4b51-ad14-5fb31e291b51","resolution":{"observed_at":"2026-08-03T17:51:54.161052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04746","last_updated":"2025-06-13T02:29:47Z","snapshot_observed_at":"2026-08-06T07:12:03.031931Z","submitted_at":"2024-11-07T14:29:02Z","title":"Taming Rectified Flow for Inversion and Editing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04746","snapshot_observed_at":"2026-08-03T17:51:54.163837Z","title":"Tam- ing rectified flow for inversion and editing.arXiv preprint arXiv:2411.04746, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.163837Z"},"links":{"cited_paper":"/paper/2411.04746","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:bda7528e83622cefe3bf3bcac0d2d1c2131b6a793597c13f501e2f484710d4ea","observation_id":"20695e71-0039-488d-9282-cdf8c1f5c86a","resolution":{"observed_at":"2026-08-03T17:51:54.163837Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.166509Z","title":"Point2pix- zero: Point-driven refined diffusion for multi-object image editing.Pattern Recognition, page 112041, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.166509Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:1d483cd5c15ef1aaa31d5c5805b26b740f3183e137365ca2d651e101cd19609e","observation_id":"b36346fb-5f49-415e-aabf-3d19cbf3d164","resolution":{"observed_at":"2026-08-03T17:51:54.166509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.168786Z","title":"Zero-shot image restoration using denoising diffusion null-space model.The Eleventh International Conference on Learning Representa- tions (ICLR), 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.168786Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:9187b7b12ec68a3e44770b075d5fcfe17f1d9270f0780dc3016fae1d8e747524","observation_id":"2835152b-ad15-43cd-abe7-4dc0cba5a68d","resolution":{"observed_at":"2026-08-03T17:51:54.168786Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.171125Z","title":"Paint by example: Exemplar-based image editing with diffusion mod- els","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.171125Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:9f6c04eb6b7da08935714caa00bf280505ac5755a9b150f9cd8f36a06a2ee53a","observation_id":"45ffb712-288d-47b3-811b-c4f393b5f0e5","resolution":{"observed_at":"2026-08-03T17:51:54.171125Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.03293","last_updated":"2025-02-20T13:17:01Z","snapshot_observed_at":"2026-08-06T10:03:37.409988Z","submitted_at":"2024-06-05T14:02:31Z","title":"Text-to-Image Rectified Flow as Plug-and-Play Priors","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03293","snapshot_observed_at":"2026-08-03T17:51:54.173437Z","title":"Text-to-image rectified flow as plug-and-play priors.arXiv preprint arXiv:2406.03293, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.173437Z"},"links":{"cited_paper":"/paper/2406.03293","citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:02aea46b04c38bbc407ba4f415bf79f4174a0af4c7d2c8d72fe807c8a021abe0","observation_id":"9fe47656-9684-4830-950c-fd86dd7535ca","resolution":{"observed_at":"2026-08-03T17:51:54.173437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.176021Z","title":"The unreasonable effectiveness of deep features as a perceptual metric","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.176021Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:ec549a1ef6b790b6df4d42556110992dcb117e6fb46a36ea7ef4cb01f4345ec1","observation_id":"6ea66d36-3f22-4059-8994-6768d21b1a5e","resolution":{"observed_at":"2026-08-03T17:51:54.176021Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.178597Z","title":"Real- world image variation by aligning diffusion inversion chain","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.178597Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:4a9746dcd826cd661592d8d70329a84d736e9958d606e65496cdbb56aad2bb3f","observation_id":"ccac9e56-ecce-4692-8158-df4059236c2b","resolution":{"observed_at":"2026-08-03T17:51:54.178597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.180918Z","title":"Flow priors for lin- ear inverse problems via iterative corrupted trajectory match- ing.Advances in Neural Information Processing Systems, 37:57389–57417, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.180918Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:bbbe6fae7e7ed66eee1d942951334869dcb8347b8d174ab39aa77e86ef31dc50","observation_id":"b00f908d-749f-4f36-99d8-75833435bf32","resolution":{"observed_at":"2026-08-03T17:51:54.180918Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T17:51:54.183590Z","title":"Denoising dif- fusion models for plug-and-play image restoration","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-03T17:51:54.183590Z"},"links":{"citing_paper":"/paper/2512.08125"},"observation_digest":"sha256:f64975801682d6306c81555b883ab6e3eed292353b52a7e0ba88ce0a843bd0a3","observation_id":"d507cc5c-4c82-4504-bee3-59dcd6d086e2","resolution":{"observed_at":"2026-08-03T17:51:54.183590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2512.08125","last_updated":"2026-05-24T22:00:59Z","latest_version":2,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-06T12:53:36.389512Z","submitted_at":"2025-12-09T00:09:21Z","title":"FlowSteer: Conditioning Flow Field for Consistent Image Restoration"},"reference_resolution":{"displayed":67,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":67,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":67},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 1 inbound Pith citation observation for arXiv:2512.08125."}