{"as_of":"2026-08-10T13:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9d46fa5b566f6087e829524485269d23dc2c7ad63b4d566e24fa2db7c3190304","coverage":[{"denominator":34,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":34,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:40:22.468532Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2507.02391/citation-record","integrity":"/paper/2507.02391/integrity","json":"/paper/2507.02391/citation-record.json","paper":"/paper/2507.02391"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:27.974215Z","title":"Score-based generative modeling through stocha stic differen- tial equations,","venue":null,"work_id":"7e672866-85aa-4d18-b5a2-910f35353d6d","year":2021},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:19.663975Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:5e238f6aae171267b826b6f0301daed99d91a726e9da2f7a22352bd918711fb2","observation_id":"278dad41-f6f4-4d3b-8035-06d7e401f06e","resolution":{"observed_at":"2026-08-06T20:40:28.019152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:27.862739Z","title":"Di ffusion models in vision: A survey,","venue":null,"work_id":"e456f92d-a83a-4a57-8f5e-749535c2b936","year":2023},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:19.715167Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:affe4247915a97a7608c701a5f281e81a7c0a8654e92a3934e9f8c587759bd9d","observation_id":"80a6b4cf-47f5-4197-82ea-ba37d9e43946","resolution":{"observed_at":"2026-08-06T20:40:27.902978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.00083","last_updated":"2024-09-30T17:34:01Z","snapshot_observed_at":"2026-07-06T19:24:48.032228Z","submitted_at":"2024-09-30T17:34:01Z","title":"A Survey on Diffusion Models for Inverse Problems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.00083","snapshot_observed_at":"2026-08-06T20:40:19.787123Z","title":"A survey on diffusion models for inverse problems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:19.787123Z"},"links":{"cited_paper":"/paper/2410.00083","citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:774a9a4d0511884135ba918872b336a2fd67861d7ed683dc11c43cacf976f078","observation_id":"6add9775-6d21-4e7e-95a5-fe6450a36e87","resolution":{"observed_at":"2026-08-06T20:40:19.787123Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:27.725617Z","title":"Speech enhancement and dereverberation with diffusion-b ased genera- tive models,","venue":null,"work_id":"828bfd93-81ff-4600-b00d-eef7a75a9f0c","year":2023},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:19.876765Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:b8a82c2da9a16d39961c574a5c1ba2f8435951f773c3b46df1c7d3956f6c2923","observation_id":"d9859bf5-7c75-482f-8d90-5523775d3419","resolution":{"observed_at":"2026-08-06T20:40:27.807467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:27.566055Z","title":"StoRM: A diffusion-based stochastic regeneration model for speech enhancement and dereverberation,","venue":null,"work_id":"756d33dc-2b60-491d-9b7e-30c16f66596f","year":2023},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:19.966570Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:73b9183de3e6e9eb032319f88a0dbaf05ca4b04e42e814b4f8f1dc58d6e36168","observation_id":"b7d5f922-0fe0-4499-8dd1-4348414601e7","resolution":{"observed_at":"2026-08-06T20:40:27.639863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:27.440446Z","title":"Diffusion-based speech enhancement in matched and mis- matched conditions using a Heun-based sampler,","venue":null,"work_id":"12c64fd2-5c58-4dfa-b04e-253ff3cc033a","year":2024},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.025636Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:a918cc3e97eef63f48b7bc4b5e02b576d13132c82712004c26e1d1b528d4b386","observation_id":"5962565a-0588-4c58-9376-24efef167cc1","resolution":{"observed_at":"2026-08-06T20:40:27.495675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.03065","last_updated":"2022-09-16T10:27:27Z","snapshot_observed_at":"2026-08-09T14:32:30.515268Z","submitted_at":"2022-06-07T07:32:32Z","title":"Universal Speech Enhancement with Score-based Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.03065","snapshot_observed_at":"2026-08-06T20:40:20.093693Z","title":"Univer- sal speech enhancement with score-based diffusion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.093693Z"},"links":{"cited_paper":"/paper/2206.03065","citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:4d73610872890b60212b0634ec50fcfc42b6838ceaefacac3358ad22ac0cd159","observation_id":"dcb38973-f993-41fd-aa7d-b2c4d998a713","resolution":{"observed_at":"2026-08-06T20:40:20.093693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:27.315852Z","title":"Conditional diffusion probabilistic model for speech enh ancement,","venue":null,"work_id":"0e5e7a94-043b-432b-a319-3edb437f64b3","year":2022},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.183537Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:4cf2e9f833cf92f886c523f341b7b5570da512704ebdc1769af99a7225b4736b","observation_id":"1b3619ec-8597-48aa-b591-cb5703636cbf","resolution":{"observed_at":"2026-08-06T20:40:27.375052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:27.131413Z","title":"Cold dif fusion for speech enhancement,","venue":null,"work_id":"00148b8e-7057-43cc-ad3a-7bc927dda82d","year":2023},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.268143Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:51b80a78a2639efd774ec87c2d821b8f8b074709e16715ebceef43718fc583b4","observation_id":"59dcc19e-63c9-4b02-b621-9c66cf066d78","resolution":{"observed_at":"2026-08-06T20:40:27.201109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:26.963954Z","title":"Supervised speech separation base d on deep learning: An overview,","venue":null,"work_id":"d1d31a4a-d9c4-4699-8d47-c9d6b8cfddeb","year":2018},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.356257Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:2a39e7009831e82e971d83a309a74aaf4545d975ee03119d0f0f5874ff1b342d","observation_id":"8cd49ff8-4060-42f2-b195-3f77390824d1","resolution":{"observed_at":"2026-08-06T20:40:27.028384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:26.780435Z","title":"A regression appr oach to speech enhancement based on deep neural networks,","venue":null,"work_id":"372f1cad-ac95-4d54-8620-4f4e60d7c6db","year":2014},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.444162Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:e31666d3ec5ea25687c14484ee9d5db37f83b1ca13aa23cc82282e209e5572af","observation_id":"d74a3359-28be-4eb2-ada0-25cfef1bede3","resolution":{"observed_at":"2026-08-06T20:40:26.861079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:26.605463Z","title":"Conv-TasNet: Surpassing idea l time– frequency magnitude masking for speech separation,","venue":null,"work_id":"8f730829-093f-4bed-97f1-792bb7070b6e","year":2019},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.528200Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:d1bd50ab6bf80e4f743e9c7327ec1f2d9b3809a0cb972db0d2ab8cde318fb29d","observation_id":"a26fe851-eaf5-4cd2-b9dc-476d1408e1fb","resolution":{"observed_at":"2026-08-06T20:40:26.693127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:26.446920Z","title":"Unsupervised s peech enhance- ment with diffusion-based generative models,","venue":null,"work_id":"c2bd92bd-b272-4127-8a8e-661662a46fb4","year":2024},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.630318Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:333a6efc1c12c87e7d2171521ec6a445b01bb92fc7a8798af4d5024cc18c7aa2","observation_id":"4c8c13ac-ac6c-4805-94fd-3dc04f830399","resolution":{"observed_at":"2026-08-06T20:40:26.520385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:26.273825Z","title":"Diffusion- based unsupervised audio-visual speech enhancement,","venue":null,"work_id":"2ed032b6-1bae-4a4c-9982-03ced1f8c89e","year":2025},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.717705Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:66efa0cc77e22c736724c1ce191de26ef39dceb9fdf0574033fdf1c5f3f0cb4e","observation_id":"67596a5c-56a6-4f47-b0ab-86d6dfc10677","resolution":{"observed_at":"2026-08-06T20:40:26.347958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:26.094638Z","title":"UnDiff: Unsupervised V oice Restoration with Uncondition al Diffusion Model,","venue":null,"work_id":"38eb4294-acd4-4ad1-afe5-16a4f24ed7dd","year":2023},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.803997Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:cd2145347ba0537573120b0102f06f0a936f616a4cf619386028bb10d5b05599","observation_id":"8c58c2ed-784b-4fa2-a5f5-b5cabde922ca","resolution":{"observed_at":"2026-08-06T20:40:26.184816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:25.868728Z","title":"BUDDy: Single-channel blind unsupervised dereverberati on with dif- fusion models,","venue":null,"work_id":"088894d4-04d7-4def-ab95-ff826296712e","year":2024},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.891818Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:6a6905f45f5a325bb106118e3f7b11309ee13560fb3d354b02cb46bcbc0356f1","observation_id":"9ee03c42-aaa0-4699-afd1-b4026edc97fc","resolution":{"observed_at":"2026-08-06T20:40:25.963842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:25.685955Z","title":"Diffusion models for audio restoration: A rev iew,","venue":null,"work_id":"902864bc-9a90-4840-b09f-5e41f460d8c3","year":2025},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:20.979404Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:c89dfdbcc2b6aed436c415298829768614f6228a0acd713e1caae8d910cfa867","observation_id":"70165729-bf1f-49d5-8283-063846f78a64","resolution":{"observed_at":"2026-08-06T20:40:25.789505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:25.560118Z","title":"Diffusion posterior sampling for general noisy inverse pr oblems,","venue":null,"work_id":"c1567be9-fdd2-4b4a-991b-012b641cc241","year":2023},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.051254Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:9f84c134a5d11ea6559889078a4cf004ea704154171415ea76288f3e4afa8046","observation_id":"0c983a88-0dbc-4bee-bee2-812f7b1bae4d","resolution":{"observed_at":"2026-08-06T20:40:25.606833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:25.407453Z","title":"Diffusion model based poster ior sampling for noisy linear inverse problems,","venue":null,"work_id":"b182fe5d-5cc3-46a9-938e-63cfdfad5005","year":2024},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.116878Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:6dfb43fa9f67ab76c0b7d0f21079e22025e3fbdb288c60193892f736421ac983","observation_id":"4289089d-37f1-43a4-a7ad-63b9957678e5","resolution":{"observed_at":"2026-08-06T20:40:25.485067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:21.181159Z","title":"Reverse-time diffusion equation mod- els,","venue":null,"work_id":null,"year":1982},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.181159Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:0e3c1e8f786a6a02f80c7407e3644319e68d9f02988c093b883f4dab5122deb4","observation_id":"d2463806-4dc9-4728-8e99-296ec9c934fb","resolution":{"observed_at":"2026-08-06T20:40:21.181159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:25.211436Z","title":"Understanding diffusion objec tives as the ELBO with simple data augmentation,","venue":null,"work_id":"8e66f032-22a3-462c-be56-b9c8c3863998","year":2023},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.277476Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:10fcc43f1957d1f2dc1098ee221352c68c1f8868dce86db684feef255c9a94ba","observation_id":"6e9426ce-fffe-4921-be49-a6b2e1d3ca6d","resolution":{"observed_at":"2026-08-06T20:40:25.299549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:21.377076Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.377076Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:665cd1e1acd1776c15c8e862d35603c509cd10749134664fed4bd7a9214b0b8c","observation_id":"bde5380a-a93b-4bbf-bac5-0d74360f5e5b","resolution":{"observed_at":"2026-08-06T20:40:21.377076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:21.456853Z","title":"Tweedie’s formula and selection bias,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.456853Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:9e5ae4e1d4f9ed391844a27177c5f31f3cd4d9380fbd8e5cdb91a82acdd47431","observation_id":"3103772d-abce-435a-96b8-f392d597590b","resolution":{"observed_at":"2026-08-06T20:40:21.456853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:24.995621Z","title":"Solving inverse problems in medical imaging with score-based generative models,","venue":null,"work_id":"90e811df-5213-49b7-bf8c-7f8af9706c36","year":2022},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.558763Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:6db8cbc98cbd2c3bfc93b76fe861bd8534be0770822d5d2784b76eef4607a717","observation_id":"d282816e-ba51-4508-927b-b60e50d824d0","resolution":{"observed_at":"2026-08-06T20:40:25.088116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:24.805063Z","title":"UDiffSE Supplementary Material,","venue":null,"work_id":"33d9dae5-705f-47c9-b822-bf2a210513a5","year":2024},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.667497Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:c5b001d989dcd6094f98e660d8ab3e3b0abbde2cef4f43e767900a88e169a48b","observation_id":"d8bfa41a-0ca8-4d9e-82a8-7d343a7264a2","resolution":{"observed_at":"2026-08-06T20:40:24.898185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:24.515580Z","title":"Diffusion posterior sampling for li near inverse problem solving: A filtering perspective,","venue":null,"work_id":"d986b137-7719-4176-9f70-9ce92573f898","year":2024},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.751753Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:1a7be17b0eaf5b9289e283ef3d14fa061fd3f58370e081881d0c684bada22947","observation_id":"8a281f5a-efe7-4a64-865f-3ce366b8da18","resolution":{"observed_at":"2026-08-06T20:40:24.667113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:24.331053Z","title":"A recurrent variational autoencoder for speech enhancement,","venue":null,"work_id":"078da784-7e46-4907-b5dc-9c2951bf5821","year":2020},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.831459Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:adb9621093518a799d793ecce2bb3bff1c508cf42c3524b86adcf62cb80088e9","observation_id":"76ae0c81-9e2b-4a55-b858-9c6488d62ebc","resolution":{"observed_at":"2026-08-06T20:40:24.430685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:24.104343Z","title":"In vestigating rnn-based speech enhancement methods for noise-robust tex t-to-speech,","venue":null,"work_id":"3667ce39-a6ca-4c84-ae19-96fb80a7a704","year":2016},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.900989Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:d08505b995823cb315142ea5a94870feae12ec3d1d6b21d6bdfdc42b2df0e167","observation_id":"7674e8e1-8235-4402-8ebb-9526a38b0e03","resolution":{"observed_at":"2026-08-06T20:40:24.229395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:23.862111Z","title":"CSR-I (W SJ0) complete LDC93S6B,","venue":null,"work_id":"6ee85c06-6a85-4d79-8213-e192ca4e5f08","year":1993},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:21.990317Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:bb5f57121859701a4b29d11e550ea8fc453db0351a8b00638ecdf18a10fb2e3f","observation_id":"3811b261-6c11-469c-a792-d8bab1be8bc3","resolution":{"observed_at":"2026-08-06T20:40:23.990045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:23.618943Z","title":"The QUT-NOISE-SRE protocol for the evalu ation of noisy speaker recognition,","venue":null,"work_id":"c8567985-17ee-4236-8111-ad34350f92fd","year":2015},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:22.092316Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:e23464fc20e1f8e048051e3bf61362b097b00aa444758f375ac0b739b1739139","observation_id":"6f56b344-31b2-4e0d-9315-7f76fb4590da","resolution":{"observed_at":"2026-08-06T20:40:23.749278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:23.431172Z","title":"The diverse enviro nments multi- channel acoustic noise database (DEMAND): A database of mul tichan- nel environmental noise recordings,","venue":null,"work_id":"87c54f8e-1b23-4b18-bb58-47714f0ae065","year":2013},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:22.175856Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:cb7e86bacaa83b4098b67e19d0586fa9921b5aa8c80128a49c1250fa914f60e2","observation_id":"1470403d-fdae-477e-98a2-6386a4b241ea","resolution":{"observed_at":"2026-08-06T20:40:23.520895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:23.230629Z","title":"SDR –half- baked or well done?","venue":null,"work_id":"8f027731-c80f-441e-b3a5-92819b49277b","year":2019},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:22.297385Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:e86f1e8958ccd0f94165c33f78f8d894fea72cccf81d92be91a390a17fbc5387","observation_id":"580c9574-e8f1-4292-8d0e-69cfc6b69b72","resolution":{"observed_at":"2026-08-06T20:40:23.338440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:23.008215Z","title":"An algorithm for predicting th e intelligibility of speech masked by modulated noise maskers,","venue":null,"work_id":"68b9c9cb-dca5-4612-acc1-d68867c6ab70","year":2009},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:22.390053Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:5bf167d5c76fa960585f0ee815ac81ae8c0fa78214eddbf168ad9f57103fdbcd","observation_id":"7575a0bb-c82b-41a1-b76f-1b7882cf7ee9","resolution":{"observed_at":"2026-08-06T20:40:23.132756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:40:22.791838Z","title":"Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs,","venue":null,"work_id":"03177e22-747a-438b-b1a6-844756eba326","year":2001},"citing_paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:40:22.468532Z"},"links":{"citing_paper":"/paper/2507.02391"},"observation_digest":"sha256:8c765681f4d577b3721460f5697b101f29a41dd4551f4c10f77e3bac69520b7a","observation_id":"4120a06d-77cc-461d-84d0-ae988642471f","resolution":{"observed_at":"2026-08-06T20:40:22.875843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.02391","last_updated":"2025-07-03T07:42:02Z","latest_version":1,"primary_category":"cs.SD","snapshot_observed_at":"2026-08-06T20:28:04.353466Z","submitted_at":"2025-07-03T07:42:02Z","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement"},"reference_resolution":{"displayed":34,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":29},"total_outbound_references":34},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2507.02391."}