{"as_of":"2026-08-23T19:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d4aeb83f7d0deafacf7ac940c2b4d65fdb9a9880c75708c3ff56ed95e2191056","coverage":[{"denominator":70,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":70,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-30T22:10:33.692093Z","state":"measured"},{"denominator":70,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":70,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2605.12377/citation-record","integrity":"/paper/2605.12377/integrity","json":"/paper/2605.12377/citation-record.json","paper":"/paper/2605.12377"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.054938Z","title":"Ntire 2017 challenge on single image super-resolution: Dataset and study","venue":null,"work_id":"d983c94f-a050-4a05-a9d6-5f4684ef303f","year":2017},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:59572f3501e9ca9306ef9ab2c2a7eacd10662017f0d8b7371ef40dd4ed5a5861","observation_id":"3e1a706a-b3ad-4d31-9e60-cbd47cc86d87","resolution":{"observed_at":"2026-07-07T14:53:56.056210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.128760Z","title":"Toward real-world single image super-resolution: A new benchmark and a new model","venue":null,"work_id":"a6da9e54-c707-4fe3-8e22-992ea34bdf5b","year":2019},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:d91686ba4c02342132a56d9434dc5b1fa5ef2733a3daac3488ab0de6073f03ff","observation_id":"20fd1530-4522-49f1-87b0-0bfe3ebc1588","resolution":{"observed_at":"2026-07-07T14:53:56.130034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.125020Z","title":"Adversarial diffu- sion compression for real-world image super-resolution","venue":null,"work_id":"725919f0-7a96-4490-a5ac-de07c4549228","year":2025},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:78f9b18c1428e5fe9ac5d6d27257920ae0b08672ef5c245afc4e6a15a3c50afe","observation_id":"b2f7ffb6-af91-46cf-a168-a8302173eb27","resolution":{"observed_at":"2026-07-07T14:53:56.126276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.041877Z","title":"Taming diffusion prior for image super-resolution with domain shift sdes.NeurIPS","venue":null,"work_id":"3c16aa3b-c535-41f2-8e17-edeaa48bd910","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:ded794fe4abd898731b63ec4d2c2b62091b1e98b3a39ff2da8d20630613b4b33","observation_id":"74a1d907-bfb0-42d2-a367-b0346a5fabf3","resolution":{"observed_at":"2026-07-07T14:53:56.043084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.029994Z","title":"Image quality assessment: Unifying structure and texture similarity.TPAMI","venue":null,"work_id":"ed1caf07-5bdf-471d-8bd1-de5e8bfad8be","year":2020},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:2eb76f4e78a6fe117dbfb7c9baeef9e8fb1b78d946967712aaab99b0d632648c","observation_id":"ca15be22-f4b8-4ed5-932c-cf50d3b76677","resolution":{"observed_at":"2026-07-07T14:53:56.031264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.126888Z","title":"Learning a deep convolutional network for image super-resolution","venue":null,"work_id":"69f37429-e668-4105-b772-3cdce6053284","year":2014},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:7be0124311484389f9f94741f1fa50fb42a909b7468aa3ee8d2fa070663caf60","observation_id":"c3580fa4-4f2e-4c40-9f4e-f0c4819ca30f","resolution":{"observed_at":"2026-07-07T14:53:56.128157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.025735Z","title":"Tsd-sr: One-step diffusion with target score distillation for real-world image super-resolution","venue":null,"work_id":"96ff1172-c903-44a0-88b8-3370b5bf779c","year":2025},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:d8e5189ded9df984a9f3523059a9a505d0bca56e38d561f314340b3ff1e207e1","observation_id":"bc43ae4d-7755-414f-aa97-2560cda93872","resolution":{"observed_at":"2026-07-07T14:53:56.027172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.058742Z","title":"Scaling recti- fied flow transformers for high-resolution image synthesis","venue":null,"work_id":"35c13108-39ef-4c72-9355-d21f073ab437","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:6ece4dc2b2eba9745ac419fe63591e86f253acd8488ba3613721f488faa0f884","observation_id":"464e76e0-bf7d-433d-b1c9-fd2d399cee6c","resolution":{"observed_at":"2026-07-07T14:53:56.060001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.028127Z","title":"Generative adversarial nets.NeurIPS","venue":null,"work_id":"9b5374e4-3132-4b21-a45b-d594f4f1049a","year":2014},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:99388289547771391851d559ee564904394e8e8642481bd5fef2f60da7976f37","observation_id":"3e14e06a-7b9d-4b76-870f-33455391f265","resolution":{"observed_at":"2026-07-07T14:53:56.029393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07476","last_updated":"2024-08-14T11:47:22Z","snapshot_observed_at":"2026-08-16T13:26:31.082648Z","submitted_at":"2024-08-14T11:47:22Z","title":"One Step Diffusion-based Super-Resolution with Time-Aware Distillation","version":1},"cited_work":{"arxiv_id":"2408.07476","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.07476","snapshot_observed_at":"2026-07-01T14:15:46.871028Z","title":"One step diffusion-based super-resolution with time-aware distillation.arXiv preprint arXiv:2408.07476","venue":null,"work_id":"5ce15314-d0fe-47d2-b39b-02f9b80be010","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2408.07476","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:ccd309262b19e1f9bcdf31fc15a0306455f77afae450f4b7966e0a57aa1975ce","observation_id":"cfb0635a-2ec7-41a5-bfb7-48ba478e09a1","resolution":{"observed_at":"2026-07-01T14:15:46.872581Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.049280Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilib- rium.NeruIPS","venue":null,"work_id":"262ecc13-da92-478a-88f1-f17a2cbcfcb8","year":2017},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:caa0f76c66d7e41d911b3bde21f9538823ed74a8479a85f0af9e48d87ab8933f","observation_id":"0eb80de4-35fb-40ab-b93f-df65a8dd2e40","resolution":{"observed_at":"2026-07-07T14:53:56.050570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.023855Z","title":"Denoising diffu- sion probabilistic models.NeruIPS","venue":null,"work_id":"2d2164d5-1f80-4e36-a67f-dc30576e6060","year":2020},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:f2139050bc72cc9ee6ab179eb1b4e694b53eb22e5cc70fd11014af3115c6013d","observation_id":"df6e6206-7403-4617-944f-adcad0a9f699","resolution":{"observed_at":"2026-07-07T14:53:56.025106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.021913Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":"a79a0d15-d1b9-4cdd-97c9-cc71e2c0ca0c","year":2022},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:1238390cea876e0625a6963646def1c45520134187df818db059a419d8a4dbae","observation_id":"c7e919da-c340-4fb0-a23d-df2d27d459bb","resolution":{"observed_at":"2026-07-07T14:53:56.023244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.077277Z","title":"A style-based generator architecture for generative adversarial networks","venue":null,"work_id":"5f6025b1-4754-4622-908a-b3eb36d036a9","year":2019},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:0110e35ca58b6b22690d15c91f91b08f4b098e38362002b2c6dca21cee396b48","observation_id":"76ef7a7d-5783-411f-9c4c-ac4a48d7c777","resolution":{"observed_at":"2026-07-07T14:53:56.078477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.104485Z","title":"Musiq: Multi-scale image quality transformer","venue":null,"work_id":"91765c20-fbbb-4d6b-bd6e-2fd1e2e45e21","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:22814974f68c5f873d0914c7d7db952d798249b36e0c96b736045842d3da05d8","observation_id":"3d941a08-1f18-4a43-8677-d7ecac4c49bd","resolution":{"observed_at":"2026-07-07T14:53:56.105690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.100724Z","title":"Consistency trajectory mod- els: Learning probability flow ode trajectory of diffusion","venue":null,"work_id":"d187c162-7b2c-490f-b5a9-f51ccbfee45c","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:625aaf5e0bf1301201e275c063f16cdc4d496576ac61bd53e8d9411e99fe48a3","observation_id":"9391e808-8b75-4c81-9225-354d9359c004","resolution":{"observed_at":"2026-07-07T14:53:56.101953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.073649Z","title":"Flux.https://github.com/ black-forest-labs/flux","venue":null,"work_id":"d115ba9d-7a9d-4891-b06a-a6fd30ba6fd6","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:509490407031bfafd3e7a6a3bc858b354b21587664e6ff2dbb2e269df24edc7a","observation_id":"9fa66226-3e37-4182-b5d0-4f544eabff99","resolution":{"observed_at":"2026-07-07T14:53:56.074856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.043649Z","title":"Photo- realistic single image super-resolution using a generative ad- versarial network","venue":null,"work_id":"5e678b25-0ce9-4523-add1-09cae0c4d09b","year":2017},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:41f11d11a011cfef69bdc1f8ade345ccbd1aea04f3c612fa48d69efe14d86f9d","observation_id":"8fcebf9d-8a38-49aa-a8f6-285eba1a4ca5","resolution":{"observed_at":"2026-07-07T14:53:56.044904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04224","last_updated":"2025-03-09T16:37:34Z","snapshot_observed_at":"2026-08-19T14:35:14.867251Z","submitted_at":"2024-10-05T16:41:36Z","title":"Unleashing the Power of One-Step Diffusion based Image Super-Resolution via a Large-Scale Diffusion Discriminator","version":3},"cited_work":{"arxiv_id":"2410.04224","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04224","snapshot_observed_at":"2026-07-03T01:07:29.968562Z","title":"Distillation-free one-step diffusion for real-world image super-resolution","venue":null,"work_id":"5dfdae76-f3e4-4a63-93c2-26302cfe7a34","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2410.04224","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:1c0128944e738e4ee11aa9566fbd035d3df554bd280751003d7f30df4ee87ce8","observation_id":"de01487e-39c5-4238-946b-90067d7139a7","resolution":{"observed_at":"2026-07-01T14:15:46.885518Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.075433Z","title":"Lsdir: A large scale dataset for image restoration","venue":null,"work_id":"14e68fab-f992-42e2-914a-171341ffc942","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:447af8531df9e80822fe3e82e3b4783d9e68e8ef41d17682605265c0b788bb17","observation_id":"1c3d8e2f-18d3-4d1a-9a5e-67068e591877","resolution":{"observed_at":"2026-07-07T14:53:56.076682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.113514Z","title":"Swinir: Image restoration us- ing swin transformer","venue":null,"work_id":"4f1fee89-428a-41c9-87a5-a80373ad3cf3","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:e64cbdcc5f774dd631294de62a205bd3383c0333fb4bfe2b231795c33cab1a0a","observation_id":"e33bfe3a-5d47-466a-bf7a-f21a3e0528de","resolution":{"observed_at":"2026-07-07T14:53:56.114735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.090822Z","title":"Diff- bir: Toward blind image restoration with generative diffusion prior","venue":null,"work_id":"c16fb1ae-888c-4f70-8042-b0fc9b132674","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:33156c97bada90d5e655ccb293cd73da45edcce50268bf420e828d64b5c8bd75","observation_id":"ae805965-3451-4615-937c-06a746bde195","resolution":{"observed_at":"2026-07-07T14:53:56.092321Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.134746Z","title":"Flow matching for generative mod- eling","venue":null,"work_id":"37c380b6-a44d-4ac0-95e1-48bdf4d56e83","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:449b3e8f391bb5c01a3f116f4d43ecdc052a5f0556bdaa37fbc73408fa5e4a38","observation_id":"b6a13937-7bda-4ac3-af28-218c84cd8428","resolution":{"observed_at":"2026-07-07T14:53:56.136006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.111709Z","title":"Flow straight and fast: Learning to generate and transfer data with rectified flow","venue":null,"work_id":"8e3655b1-a6a0-4922-b1d2-6054e7a2aa8a","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:f3f4ad2201423a242ffbca27d98aab2c309683b2e5d0b114be53a2f327b7b57d","observation_id":"4c7d1bfd-8ac8-45bb-915a-624fb4d7a4fa","resolution":{"observed_at":"2026-07-07T14:53:56.112925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.086987Z","title":"Instaflow: One step is enough for high-quality diffusion- based text-to-image generation","venue":null,"work_id":"9a110f63-15b9-4af2-8acd-2fd7344fa003","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:2f1f5cad53d2886f505dc8c75c35261409c9a34cf913566a725b216a59994530","observation_id":"a44f5f9e-0d19-43fa-acea-f79b14ef294b","resolution":{"observed_at":"2026-07-07T14:53:56.088399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.02388","last_updated":"2021-01-07T06:12:28Z","snapshot_observed_at":"2026-08-16T11:24:54.113126Z","submitted_at":"2021-01-07T06:12:28Z","title":"Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed","version":1},"cited_work":{"arxiv_id":"2101.02388","doi":null,"metadata_source":"pith","pith_arxiv_id":"2101.02388","snapshot_observed_at":"2026-07-08T09:44:49.469947Z","title":"Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed","venue":"cs.LG","work_id":"5d2ab7c7-eb01-4c10-80f4-2bb52e197828","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2101.02388","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:3285810a1e3997fcf45f5224dc5dece89416721ec2f494868eea93ff9d7185c5","observation_id":"f39f32da-15d7-477e-a6bd-2228b0af31c7","resolution":{"observed_at":"2026-07-01T14:15:46.875645Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04378","last_updated":"2023-10-06T17:11:58Z","snapshot_observed_at":"2026-08-20T13:49:06.053430Z","submitted_at":"2023-10-06T17:11:58Z","title":"Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference","version":1},"cited_work":{"arxiv_id":"2310.04378","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.04378","snapshot_observed_at":"2026-07-08T10:54:49.201621Z","title":"Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference","venue":"cs.CV","work_id":"53b1d836-7feb-402c-97c7-87b9bc51196f","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2310.04378","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:4b1e61ff76aaa9e00552ed7daab36b01c3468718cc4f18b6306bacc22b8b0841","observation_id":"3f6a2845-1eb7-4754-8760-5fdf001268f5","resolution":{"observed_at":"2026-07-01T14:15:46.891677Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.062423Z","title":"completely blind","venue":null,"work_id":"1027a701-ea59-4496-b444-717d65fea5d1","year":2012},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:c243b1957a773cab797d1b953d525895b4909acf6093732ad1d939936913670b","observation_id":"f16237e3-1717-412f-94ac-58f9e370d467","resolution":{"observed_at":"2026-07-07T14:53:56.063514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.064115Z","title":"T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models","venue":null,"work_id":"9213d3cc-920c-4bdc-8a47-385cdd8030e7","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:927e91219c23f37914b5d9178b5b112b476602b7c4d41d1f130c07c3fa597382","observation_id":"02efc788-5df4-4911-84b7-846c675c8a5c","resolution":{"observed_at":"2026-07-07T14:53:56.065388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.031875Z","title":"You only need one step: Fast super-resolution with stable diffusion via scale distillation","venue":null,"work_id":"de17ebbe-bc28-4686-87ee-4170c591e79d","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:d2d84e03f3bbee3e21f0ee43a5d5cd8a1fd859aebc6b5fa911d0facffa7a8437","observation_id":"429debad-add7-436f-919c-0c09e3c1cf34","resolution":{"observed_at":"2026-07-07T14:53:56.033153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.069713Z","title":"Towards realis- tic data generation for real-world super-resolution","venue":null,"work_id":"3ac04717-9464-4e00-bff8-983615b8553d","year":null},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:b0734f63247f24e87517b7b14c580dee73acd8dd0399ea7044ee33349a80a7b5","observation_id":"2112f1ee-29a8-4215-a4e5-9fb624618034","resolution":{"observed_at":"2026-07-07T14:53:56.071179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.089007Z","title":"Learn- ing transferable visual models from natural language super- vision","venue":null,"work_id":"56c21a9a-f100-4ad4-80ae-dd3e047773d0","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:c91ce901139bddb17d148043c960dff5b4c7f28796798442dacb259439577869","observation_id":"fb38fb9c-3682-4cc0-aa87-d0e9a26d687c","resolution":{"observed_at":"2026-07-07T14:53:56.090239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.115341Z","title":"Ultrapixel: Advancing ultra high-resolution image synthesis to new peaks.NeurIPS","venue":null,"work_id":"630c5007-85c2-4ad5-9f38-ec56a83aa7e8","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:c31d3c6c57ce53e095e7f6cf79aab268f9d75e48d6dd11c20a357d90a23d0d35","observation_id":"5ccb1cd4-915b-4e2f-809b-4cbd422c7b76","resolution":{"observed_at":"2026-07-07T14:53:56.116856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.136668Z","title":"High-resolution image syn- thesis with latent diffusion models","venue":null,"work_id":"2303aa8f-e3ad-4a6f-a8c3-e027fb0f8e2b","year":2022},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:c1d614e26590cd17533bae06fcceccafb5952ed530f10b2ed511fbc0411f310b","observation_id":"59f782c8-a53f-41df-ac2b-2e7a184e6003","resolution":{"observed_at":"2026-07-07T14:53:56.137928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.119212Z","title":"Image super- resolution via iterative refinement.TPAMI","venue":null,"work_id":"80c1d2ee-4ef4-4f5b-9421-a6f4d7a7107d","year":2022},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:1757eae05bed67bf5c520195adcf20292b819012e334667cd2dca0a86b26fc7f","observation_id":"73baf30c-481d-4153-88dc-5b7a23b29bd4","resolution":{"observed_at":"2026-07-07T14:53:56.120440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.056832Z","title":"Fast high- resolution image synthesis with latent adversarial diffusion distillation","venue":null,"work_id":"ab1585e7-f49f-442f-9082-493888fb4068","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:ec1038747de3b24157c306347d61d9ee42c0aa628c3f631f08f001b30320ca10","observation_id":"e3a04904-59c8-40fd-b1bc-4dd944d09be7","resolution":{"observed_at":"2026-07-07T14:53:56.058124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.108121Z","title":"Adversarial diffusion distillation","venue":null,"work_id":"a1c863af-a37f-4808-991e-d1ddd41593c7","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:c3769f9c558f52c131d104168adb7a1f1222e3a8eb83b8b0144b7a00e5d1c084","observation_id":"cd573648-9f1b-4d68-a952-6021cdb29d8d","resolution":{"observed_at":"2026-07-07T14:53:56.109245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.122862Z","title":"Boosting latent diffusion with flow match- ing","venue":null,"work_id":"d5d8fda6-b14f-4262-9463-0f854e1d2017","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:be1f076fac7ab816837dcbc34b7b11c2d547a85a2406b17a16e80cd24f0129c6","observation_id":"ff28b137-b683-4afb-b4e3-3b69ea75c993","resolution":{"observed_at":"2026-07-07T14:53:56.124380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.121057Z","title":"Denois- ing diffusion implicit models","venue":null,"work_id":"4544cc90-24a7-4c14-8024-81ebe7f01732","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:edb728b2d5201c69b7f0d7062a50961963df5c3ae7d93733ff8f2630d6f93bc2","observation_id":"dd7a67e2-276a-4e34-805f-d0096c7cb5c9","resolution":{"observed_at":"2026-07-07T14:53:56.122264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.071778Z","title":"Score-based generative modeling through stochastic differential equa- tions","venue":null,"work_id":"37516910-e733-4c2a-9a42-3ec36a168638","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:268ca0cf1b4170d5facd08760414373f42c13274f6aefe3b27fb7aac80b6ff53","observation_id":"e9eebe2d-0bdd-49d6-8967-4c5e2eee664e","resolution":{"observed_at":"2026-07-07T14:53:56.073079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.117464Z","title":"Consistency models","venue":null,"work_id":"757042c1-b83b-4bcd-9b3e-8ee4d453351d","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:d60b697256f4d5a775f7b550e6de43227879403ab4720eb386cb74e92a8d2700","observation_id":"1b212326-4efe-4e50-abeb-2174bdec341a","resolution":{"observed_at":"2026-07-07T14:53:56.118578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.109843Z","title":"Coser: Bridging image and language for cognitive super-resolution","venue":null,"work_id":"403fb1ab-9a1c-46dd-ba0b-f3f5132cbfed","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:514ee53c1d47f4a12d8b9632a4012acf14057be8359cb9490873dc9c5ca32a3a","observation_id":"f7585993-55b1-4d96-b80a-6c035913d026","resolution":{"observed_at":"2026-07-07T14:53:56.111088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.097026Z","title":"Phased consistency models.NeurIPS","venue":null,"work_id":"de9a32f0-1d17-442f-8cbb-cb7b2bd92319","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:c658769267732ac5a5d3ed8a03c234c4edb81c456f6a2060507286e3b8ec5783","observation_id":"9ffb64a2-65c6-4056-a8ed-09d07eaf3ccb","resolution":{"observed_at":"2026-07-07T14:53:56.098215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.102682Z","title":"Ex- ploring clip for assessing the look and feel of images","venue":null,"work_id":"405f2bb5-328b-41ab-b864-2c51ac4f2b83","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:8caa09db7fc1276c1f2aeb2d8107caf35f8d44e3a583df81ea46dd9222859354","observation_id":"34a8a166-c0e6-4901-b247-4c62517cd5d3","resolution":{"observed_at":"2026-07-07T14:53:56.103887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.098842Z","title":"Exploiting diffusion prior for real-world image super-resolution.IJCV","venue":null,"work_id":"80baf320-2cff-4ad7-83c1-b4e0428acd8d","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:38782c0de545d858027b558ea9cd6eeaa5d30471e18dbdd72813876d8778f789","observation_id":"d683fe87-fe9f-4e3a-93d2-4d2af541ab97","resolution":{"observed_at":"2026-07-07T14:53:56.100112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12191","last_updated":"2024-10-03T15:54:49Z","snapshot_observed_at":"2026-08-06T05:35:29.109022Z","submitted_at":"2024-09-18T17:59:32Z","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","version":2},"cited_work":{"arxiv_id":"2409.12191","doi":"10.48550/arxiv.2409.12191","metadata_source":"pith","pith_arxiv_id":"2409.12191","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","venue":"cs.CV","work_id":"8abcfe4f-e0fb-44b7-9123-448fac95f90a","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2409.12191","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:d09747b97a7deca3df5c8021413b50acb981b793f7c7d68c929e8e2dd4d2eb6b","observation_id":"05595fd2-a446-418c-a8d3-ff31613c8e8a","resolution":{"observed_at":"2026-07-01T14:15:46.882200Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-15T14:08:11.914281+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-15T14:08:11.914281+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.095082Z","title":"Real-esrgan: Training real-world blind super-resolution with pure synthetic data","venue":null,"work_id":"f464c862-b150-421a-be02-4bda25e453b5","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:0c74943ad40357123a7bfaee013802dd57edf0051bfbdd7cacbd4dca8e1072a1","observation_id":"db404336-0049-4f80-9d22-6a137b826b15","resolution":{"observed_at":"2026-07-07T14:53:56.096422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.035668Z","title":"Sinsr: diffusion-based image super- resolution in a single step","venue":null,"work_id":"d71d9ecc-e154-40b6-aaa7-c5e9ef87204f","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:74d2385745e40397952c30d4dbf81c4961bdbf795be761a322fb262b0c014a87","observation_id":"6021ca47-869c-4adc-a0fa-d7c28c66c971","resolution":{"observed_at":"2026-07-07T14:53:56.036954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.065976Z","title":"Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.NeurIPS","venue":null,"work_id":"37b18d5a-8adc-4643-a856-eefbc3a28ead","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:5ad7db854cd3971f7ff5960f75fe6a817ecbe416eeea7306ec106d5ecdbc804e","observation_id":"4bf98e1e-8f1c-4eef-b04c-209b212a6ca1","resolution":{"observed_at":"2026-07-07T14:53:56.067261Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.067856Z","title":"Component divide-and-conquer for real-world image super-resolution","venue":null,"work_id":"c1efb9c0-7b45-447c-809d-153013752b7c","year":2020},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:1ce81808b86242a82e1a3b8941949c4f557e4afbcac654a8f229481edbc89898","observation_id":"6c403d50-32f1-471a-9652-9c6fc0796971","resolution":{"observed_at":"2026-07-07T14:53:56.069073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.132522Z","title":"One-step effective diffusion network for real-world image super-resolution.NeurIPS","venue":null,"work_id":"7c3fc342-2ad3-47c2-8152-c40da95ac330","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:7a091f5f9020a11dce27d5a1bb3ff0d66ea752507880ddef1d08cf2026fa5af7","observation_id":"bb51552f-64c1-439c-ac72-b0a46daea71b","resolution":{"observed_at":"2026-07-07T14:53:56.134132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.080969Z","title":"Seesr: Towards semantics-aware real-world image super-resolution","venue":null,"work_id":"6096e705-7f1b-4e1e-bc85-0a245842cee1","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:0790843805758bcdaf1d6eb11a8153d822b65bfe45c4d7c374b63ac0ea7d1f11","observation_id":"a047b2b5-dea0-45d3-8a35-2f07a8e0521c","resolution":{"observed_at":"2026-07-07T14:53:56.082198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.130663Z","title":"Tack- ling the generative learning trilemma with denoising diffu- sion gans","venue":null,"work_id":"9f2c232f-d852-4ed5-a4a2-d91d586100b1","year":2022},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:7edc9021e4b68dee4ef3dcdfcf4f457a980fac8339de27f08ab180b3abfe8633","observation_id":"c0a7268b-4adb-4c44-8a16-26f8555bebab","resolution":{"observed_at":"2026-07-07T14:53:56.131937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.01717","last_updated":"2024-12-27T04:03:29Z","snapshot_observed_at":"2026-08-19T22:20:03.273322Z","submitted_at":"2024-04-02T08:07:38Z","title":"AddSR: Accelerating Diffusion-based Blind Super-Resolution with Adversarial Diffusion Distillation","version":4},"cited_work":{"arxiv_id":"2404.01717","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.01717","snapshot_observed_at":"2026-07-03T16:38:39.631915Z","title":"Addsr: Accelerating diffusion- based blind super-resolution with adversarial diffusion dis- tillation","venue":null,"work_id":"5afd3c4a-352a-4f67-815b-beb0ca946b0b","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2404.01717","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:515d69765c76e097c54d2adc3cf58bb7bf73bc7c339a1dd93b095538c78cd23e","observation_id":"281b2202-e3e8-4d29-8528-49d0147645f8","resolution":{"observed_at":"2026-07-01T14:15:46.878983Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.051175Z","title":"Perflow: Piecewise rectified flow as universal plug-and-play accelerator.NeurIPS","venue":null,"work_id":"1fbff066-0fc8-49d2-9faf-68986f8bfe11","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:980d24e18a2e55cb87a852336695f3bccd6d88d022711e2f34f2bd769e4f1eeb","observation_id":"2a17ba89-8851-42cf-940c-4ac8ed5f3fa8","resolution":{"observed_at":"2026-07-07T14:53:56.052469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02398","last_updated":"2024-07-02T16:15:37Z","snapshot_observed_at":"2026-08-17T16:42:56.554179Z","submitted_at":"2024-07-02T16:15:37Z","title":"Consistency Flow Matching: Defining Straight Flows with Velocity Consistency","version":1},"cited_work":{"arxiv_id":"2407.02398","doi":"10.48550/arxiv.2407.02398","metadata_source":"pith","pith_arxiv_id":"2407.02398","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Consistency flow matching: Defining straight flows with velocity consistency","venue":"cs.CV","work_id":"88f9c5fa-dd27-420b-b012-3849fb16c89f","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2407.02398","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:b5e0497fbea794363520d6bc077bf3c7b24666a7cccba9ca34a6f668b39e1198","observation_id":"9a673959-d42a-4284-bb2a-920cb8a1438c","resolution":{"observed_at":"2026-07-01T14:15:46.888749Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.053068Z","title":"Maniqa: Multi-dimension attention network for no-reference image quality assessment","venue":null,"work_id":"36a52c2c-5233-4251-8b4d-aab855f2602a","year":2022},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:480946d433278277b995e7c82874e975d6e838c45e406cbb01d381aed8404652","observation_id":"7ec48922-a0bf-48c0-824a-f3a229573c1e","resolution":{"observed_at":"2026-07-07T14:53:56.054339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.037617Z","title":"Pixel-aware stable diffusion for realistic im- age super-resolution and personalized stylization","venue":null,"work_id":"f0f3cadc-c077-479b-8dce-67066b729bea","year":null},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:b875e7e15c4ee8f540c911911d452374023b79dbd451ae77b505811082e96ef2","observation_id":"dd6b5f67-79e2-48af-838d-00b93f33a526","resolution":{"observed_at":"2026-07-07T14:53:56.039183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.047450Z","title":"Improved distribution matching distillation for fast image synthesis","venue":null,"work_id":"12592482-c969-45c7-87e1-3e256f15b5a8","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:9273a4a73017fc9e75555778f15e280ae32c985bb96f71d00b756fa516e01353","observation_id":"81d54441-646c-41ca-8b35-f335b758d5e7","resolution":{"observed_at":"2026-07-07T14:53:56.048673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.106292Z","title":"One-step diffusion with distribution matching distillation","venue":null,"work_id":"95405231-9a06-47db-b73a-28309884ac90","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:2fc5d8c12891431055bfc0a47d27a22fe35813eb355a09f3aa028c15e44a268e","observation_id":"20af6ef4-affb-4cbd-bf7d-72087a6fdfa2","resolution":{"observed_at":"2026-07-07T14:53:56.107522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.045472Z","title":"Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild","venue":null,"work_id":"cd1e2bc4-5458-4e83-ab11-5226a9e09ded","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:8f03d67e538bff430b1565c4bf57e3d4a9a50b59fc31d8289d5f5ff0c7b71486","observation_id":"ab3515d4-ed8a-40bb-9567-c75bc9003ec1","resolution":{"observed_at":"2026-07-07T14:53:56.046840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.079055Z","title":"Resshift: Efficient diffusion model for image super- resolution by residual shifting.NeurIPS","venue":null,"work_id":"e142e6c2-806f-4e3e-ba85-5e2935b613bc","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:d3140bf6a0060d23be53590d62aaad66678dd47dfb431b381f076c402226c888","observation_id":"586ce14c-ac77-4af8-b148-504f308f4273","resolution":{"observed_at":"2026-07-07T14:53:56.080337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.033783Z","title":"Arbitrary-steps image super-resolution via diffusion inver- sion","venue":null,"work_id":"630a3b03-a0be-43d5-980f-2c796257d161","year":2025},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:cc74ad6716d478750cdb8ec1c8c34941aa09ddb6338161a3773813cdf598e1eb","observation_id":"43d1abcf-ac44-4a20-86ac-ab48a9a66e1d","resolution":{"observed_at":"2026-07-07T14:53:56.035055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.17058","last_updated":"2024-09-25T16:15:21Z","snapshot_observed_at":"2026-08-16T13:15:26.444811Z","submitted_at":"2024-09-25T16:15:21Z","title":"Degradation-Guided One-Step Image Super-Resolution with Diffusion Priors","version":1},"cited_work":{"arxiv_id":"2409.17058","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.17058","snapshot_observed_at":"2026-07-01T14:15:46.893088Z","title":"Degradation- guided one-step image super-resolution with diffusion priors","venue":null,"work_id":"838e77d6-49cd-4653-aab4-a2732b86902b","year":2024},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"cited_paper":"/paper/2409.17058","citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:b2ce7eff8d82a90554a1bd3de9661c8000a747183c2f546b44d1a8624035b97c","observation_id":"865d351b-e450-44ba-9264-8172501bd8f5","resolution":{"observed_at":"2026-07-01T14:15:46.894606Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.060601Z","title":"Designing a practical degradation model for deep blind image super-resolution","venue":null,"work_id":"e933e5c8-3fea-49df-8c12-ebcdff556b5b","year":2021},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:e59df40a410bb6b58e3d4cce4187579c9a49bf142c729731ca077d966899b27d","observation_id":"56123cc8-3259-4212-b28e-b4418206b507","resolution":{"observed_at":"2026-07-07T14:53:56.061840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.082909Z","title":"Adding conditional control to text-to-image diffusion models","venue":null,"work_id":"4d637b33-fc1b-44c1-a1d6-3095e01868f5","year":2023},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:781a6f5b8ce8691c834c68177941851781d1afdeca02954de8e6bd2ccfc0733c","observation_id":"7b766145-7def-4960-a3c7-7fe20c9d19f5","resolution":{"observed_at":"2026-07-07T14:53:56.084148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.039808Z","title":"The unreasonable effectiveness of deep features as a perceptual metric","venue":null,"work_id":"92e2f4e2-6154-4d3b-b8e9-c735e18d67a4","year":2018},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:b3c933ee7eb4e3fd5b4d5c50100bf947258a1a0959640a6d29a30e3d39ca3436","observation_id":"8de95fa9-68f0-4b58-8c62-01a75e5a03d8","resolution":{"observed_at":"2026-07-07T14:53:56.041100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.092914Z","title":"The fine-tuned SR flow model is then used to initialize both the SR modelθand the teacher modelϕ","venue":null,"work_id":"8f262cff-da51-4cf4-a8b2-9b99aedfb66a","year":null},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:3e3708651b4f2a8598e81964a298b02401204906144ebf26df3517facb978f68","observation_id":"71c5576b-b502-44d0-bdda-a1afe4a65d41","resolution":{"observed_at":"2026-07-07T14:53:56.094472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2400.6936","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-01T14:15:46.895978Z","title":"Evaluation on DIV2K-Val We also evaluate our method on the DIV2K-Val dataset [1, 45]","venue":null,"work_id":"ce5f7004-36a8-48d3-b4ac-b854949b4563","year":1968},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:94721050cfecdd3a49ec0f90758acb8d15b41606daddf5c8a245af8896b708d8","observation_id":"7461dcee-41e8-4631-86ad-dc7691a45c9c","resolution":{"observed_at":"2026-07-01T14:15:46.897788Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-07T14:53:56.084757Z","title":"We provide valuable insights into the effective use of flow-based techniques and consistency learning to achieve competitive SR results in a single-step setting","venue":null,"work_id":"82594d32-aef5-4ac8-9478-2562a54e8beb","year":null},"citing_paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-06-30T22:10:33.692093Z"},"links":{"citing_paper":"/paper/2605.12377"},"observation_digest":"sha256:e6fc9a77f8528bb6cf2f4d776bb4fecca7c2f01619894bc5633e73c1d84df8e0","observation_id":"9bd485e0-700a-410a-bf89-fa90d82bf832","resolution":{"observed_at":"2026-07-07T14:53:56.086369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.12377","last_updated":"2026-06-01T10:58:56Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T11:57:34.377097Z","submitted_at":"2026-05-12T16:42:38Z","title":"Fast Image Super-Resolution via Consistency Rectified Flow"},"reference_resolution":{"displayed":70,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":8,"verified_fuzzy":61},"total_outbound_references":70},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2605.12377."}