{"as_of":"2026-07-15T10:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6b3f8f78a00a681b80a72bd4efc8c6927c80930d263afd857998845da2f2281a","coverage":[{"denominator":53,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":53,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T18:51:54.881455Z","state":"measured"},{"denominator":53,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":53,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-07-15T06:30:58.975436+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/2606.08751/citation-record","integrity":"/paper/2606.08751/integrity","json":"/paper/2606.08751/citation-record.json","paper":"/paper/2606.08751"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:51:54.881455Z","title":"European Journal of Nuclear Medicine and Molecular Imaging , volume=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:5e659c2ab631dcfc6ca053d4fcfd8a8ea76351027ac41c4f6b77959838d264cc","observation_id":"d637632f-dc19-4429-9b86-4d8c859a8cc3","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"International Conference on Medical Image Computing and Computer-Assisted Intervention , pages=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:b161d819fea25eb086649a7a133db03479fa2f0faa337731e04e2ce76f456d9a","observation_id":"7e46d7db-72db-4d10-a431-e9c8fbb33736","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"Denoising","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:84bc8936785e9d23ae5c9e2d843765c647a35c43bb8ee6b9ac5fd251cb9bcc72","observation_id":"78b95786-bc87-4644-864a-9117738a281b","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2022 , eprint=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:ad4d131157858c294380df52b62337b964d88598685fddc79b5e4fc4ca953816","observation_id":"488b665f-11df-42ba-bef5-33c3b6668651","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2026 , eprint=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:c46304b36fafa20512b4878c5c1f778eaece3207113b9860e16280d2e0d28f99","observation_id":"99eedabc-b574-4290-acf6-8f43ed5b74e7","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"and Liu, Chi and Zhou, Bo , journal=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:b3d8e7d17ca4dabd704207b6b446782f60185dd62d6dbea33e91b42452f6011c","observation_id":"4beaf987-69c0-4752-94d9-0ba8d12e6b31","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:29cc969da06de144896b3bce6d80a6353adb4f43ef21ed38a81c96d26afdbad3","observation_id":"4a5c66de-dff1-49eb-bbf6-bcda2a5f48bb","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2014 , eprint=","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:a321c75bcc3554043726ac118969cccbada9f5ab4d210d8d31274790a373f143","observation_id":"34ca9dad-0669-4397-a709-d3ca3b426b8d","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"10.1007/s10462-024-10800-8","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T19:01:08.326024Z","title":"Artificial Intelligence Review , author =","venue":null,"work_id":"30bc159b-e226-4b16-9a15-80b3dbe7b773","year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:556db031a73023ff2a56aaadbab9d97ff3d7c1ace053e4ffa4ea815a4a1a43b0","observation_id":"07f89ce0-610c-40a9-bf0e-4639226adacb","resolution":{"observed_at":"2026-06-27T19:01:08.327304Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"2021 , eprint=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:8d0660c7add19b93ae5e05e5fcd7bbc428bb288b90c74f52608f015a896b9ad0","observation_id":"7d4e0f80-7dd8-41e5-97b6-e5e90f4feb1d","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2688.2022","doi":"10.1109/cvpr52688.2022","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"A ConvNet for the 2020s","venue":null,"work_id":"0a23d1b7-bd56-43cc-8a80-7c43ce994e1e","year":2022},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:dcd26e7e743a5c15e5e11f744323cb97aa201fbaf61ed840f906414ccb898e60","observation_id":"eaf5c915-f5fd-4a20-8cae-5217bce4c698","resolution":{"observed_at":"2026-06-27T19:01:08.322518Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-12T17:19:41.038772+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T17:19:41.038772+00:00","source":"openalex_status_cache"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:939f9ef9d016109b6bcda4d7b46055d184da74605432e841760fd694a4f497ac","observation_id":"81d8b540-10ab-41b4-90c0-f7eea34fe2ee","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) , month =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:23cf747e25c66a46ec10673a44514ad8ddbcfc4ef562fcff954ae4ae62d1d103","observation_id":"c92249dc-60d1-40fb-b451-bb4fa4708054","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:751ffb925faf172f8b3e0fb72a7727bf31bb4fca46a2eea80c6b4e6cfce41034","observation_id":"5c1a9928-c262-4288-9d68-477893d4e4c0","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2021 , eprint=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:a53dc801825f521b0c72e411c086ab3a2ad0c067e5008c72f3c9c96290911f66","observation_id":"aaec39bd-1cf2-44c3-b22a-1ac6d5607145","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2021 , eprint=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:d45021ede4b5e8672fda88a35a20c9969ee305452f68e51600a442d9a5022050","observation_id":"7a24bbe9-f54f-4480-bc33-ff34c38c7a84","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2024 , eprint=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:0aa3501f18137dabcb15f852f3d872e171b290f20008e0f487bd088619227e34","observation_id":"2a76c3ad-5e43-4e7c-992d-16be467aad4c","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2412.13059","doi":"10.48550/arxiv.2412.13059","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"3D MedDiffusion: A 3D medical latent diffusion model for controllable and high-quality medical image generation","venue":null,"work_id":"f7cdc428-2216-4223-a626-1f890305d035","year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:02d4a10c1209b2e4017f17dcb56ac478164ccdcb22e6b2072cb2ed2d29f04916","observation_id":"046122af-91c6-4d59-b540-d3b1e525ea3d","resolution":{"observed_at":"2026-06-27T19:01:08.307059Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15887","last_updated":"2023-07-14T01:27:28Z","snapshot_observed_at":"2026-07-06T15:33:11.344191Z","submitted_at":"2023-05-25T09:38:52Z","title":"Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising","version":2},"cited_work":{"arxiv_id":"2305.15887","doi":"10.48550/arxiv.2305.15887","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15887","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Diffusion","venue":null,"work_id":"3bb539be-e6bc-4988-811e-7a2e9455a3b3","year":null},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"cited_paper":"/paper/2305.15887","citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:a7eea4711ee9420cf4c109e7be202ce525e11fbc570dc9a02cddb00cf37314c2","observation_id":"61fbb5cb-1271-4f67-8808-49fef2ff3812","resolution":{"observed_at":"2026-06-27T19:01:08.319893Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2025.356518","doi":"10.1109/jbhi.2025.3565183","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"IEEE Journal of Biomedical and Health Informatics , author =","venue":null,"work_id":"e98998e6-4417-4157-bf8d-0fa1ffc0d232","year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:d490894f8c7bfdf756ef6d8cbd7f669013637b46aa6d83e8feb330e8398f5405","observation_id":"20ff3001-c1f0-491d-b687-5cc2c20e7cef","resolution":{"observed_at":"2026-06-27T19:01:08.304434Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"MICCAI 2025 - Open Access , author =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:53a1b0127584e917de9d8820da8255f25b0aab2352149c6608935c06a78ba4e3","observation_id":"97a03aef-89e2-4caa-b586-27ef0e1ec99b","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.05243","last_updated":"2022-07-16T21:06:31Z","snapshot_observed_at":"2026-07-06T11:56:34.288687Z","submitted_at":"2021-10-08T08:42:03Z","title":"Score-based diffusion models for accelerated MRI","version":3},"cited_work":{"arxiv_id":"2110.05243","doi":"10.48550/arxiv.2110.05243","metadata_source":"arxiv_reference","pith_arxiv_id":"2110.05243","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Score-based diffusion models for accelerated","venue":null,"work_id":"80b21092-6320-4122-ad01-54b6fde95ac7","year":2022},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"cited_paper":"/paper/2110.05243","citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:f043c26b3cdbc1085c909ed860f03df59b482e94dd22e44e37801a374ce9335d","observation_id":"327ce9f9-41e3-402a-9d99-a129fb370bbf","resolution":{"observed_at":"2026-06-27T19:01:08.325327Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"2022 , eprint=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:717393ad47e841050677d6fc099aca92f8ad1f0c67467ed721b7fbe009ea6e13","observation_id":"0b21b42f-754f-46e0-aab0-7b1e7e80c8ba","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2022 , eprint=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:d2c748d7eb1281a098cf3a518698680bbd9caa65447db23818a0a57135f6f877","observation_id":"b1380334-3647-4328-9a03-f3f5b035ce73","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"10.1007/s11633-025-1562-4","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T17:51:14.693631Z","title":"Machine Intelligence Research22(4), 730–751 (2025).https: //doi.org/10.1007/s11633-025-1562-4,https://www.mi-research.net/en/ article/doi/10.1007/s11633-025-1562-4","venue":null,"work_id":"c092d258-05ec-4abc-949b-4bd7bed59eef","year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:cda5322115257d2285ffd5a33f68d21c1d429b6bd65b68ddfdcefbda9a43ea64","observation_id":"ad1843b7-7576-4f7b-84ad-ba62300c3457","resolution":{"observed_at":"2026-06-27T19:01:08.301656Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-05-22T14:52:31.208449+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T14:52:31.208449+00:00","source":"openalex_status_cache"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"2024 , eprint=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:6251dab614f83ddef63c55afcc741d9036068454b994528e0eaa48ac6e0b5dfa","observation_id":"22b76b00-0c9c-496d-bdb9-aea25e103f19","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2025 , eprint=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:96ee32182b7ec10c1b3210d410acf9028bfbff51e46d96bc1e389f576a04b683","observation_id":"2ff3ec5f-2638-402a-afb0-f8bb6c537ebb","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2505.16864","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T22:27:26.259476Z","title":"Training-free efficient video gener- ation via dynamic token carving","venue":null,"work_id":"7b739720-fa30-4330-b5b5-bb401753b77c","year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:b14a6b3218945ed65c6e4061786f171a35550d68c9fb051c092f5a2b962a8ce9","observation_id":"1e736adc-3ae4-4017-bda1-f812a25fc174","resolution":{"observed_at":"2026-07-02T22:27:26.261286Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"2024 , eprint=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:5b3332f4de2467f5484108337aaa659a44bfb445dbbab89610413575ab88cc85","observation_id":"c0efc2fe-54ee-49ce-92db-0c74d8156a7e","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2025 , eprint=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:177ef8d57913daf784a36ca83ac9db33c9c733e19216765451d862135f86a4e5","observation_id":"01b2ee72-1ca7-4453-a43f-9d30dac7ce2f","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2025 , eprint=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:28d2155fdb941f90906b451482571ae3ae108a3be14cd2adde147ef6541d6319","observation_id":"0e5d07ab-2cc7-4193-b23a-f5f70e065202","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.20404","last_updated":"2024-12-29T08:52:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-29T08:52:49Z","title":"Open-Sora: Democratizing Efficient Video Production for All","version":1},"cited_work":{"arxiv_id":"2412.20404","doi":"10.48550/arxiv.2412.20404","metadata_source":"pith","pith_arxiv_id":"2412.20404","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Open-Sora: Democratizing Efficient Video Production for All","venue":"cs.CV","work_id":"8b29ba7b-3d84-4281-85b7-9eaf905afd7f","year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"cited_paper":"/paper/2412.20404","citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:3ec31e46a3a7dca1d1ca1770cd9425c16b01ee877db67d3cc0253b04c0abb5bd","observation_id":"5b015bba-804e-4cef-a763-ef4940ecd923","resolution":{"observed_at":"2026-07-02T22:27:26.265411Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"2022 , eprint=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:ebf7254e7a619b93280bb8f520c978d8f964971aab589ecc0505d8c959cda0c8","observation_id":"591784d9-2ef8-4985-bf12-66afafad4283","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"10.1007/s00259-021-05644-1","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T19:01:08.315515Z","title":"European Journal of Nuclear Medicine and Molecular Imaging , author =","venue":null,"work_id":"f916d512-ac4b-4afd-b989-adaa43971e16","year":2022},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:58f5ea384200c73aea502b7a5c97c4859ffabedd77d49389985219e3dac7d7f0","observation_id":"5cc2dc74-b0db-4e7e-976d-735ce358febf","resolution":{"observed_at":"2026-06-27T19:01:08.316678Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"Computerized Medical Imaging and Graphics , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:6c8273d7466769f0a1461a951cae0f219006f99dd090fb0a399868fc1af02ea8","observation_id":"1b6697ab-a299-45c8-95c2-08554dbbe395","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:a3246ae0bf1624fa98e923bb45640efd5a775e3e7729009e0e99db6b40e1e19e","observation_id":"eb4b66e8-5835-4a83-b501-a0b9f97b7306","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"International Workshop on Computational Methods for Molecular Imaging , pages=","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:92e6f4809ccc4980528efbb32d34f6c44d76de9f22cc2a6c6e89c7486d011e6f","observation_id":"39e472bb-1a36-4f93-aba2-1c0c8ca02da2","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2020.101770","doi":"10.1016/j.media.2020.101770","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"2020 , issn =","venue":null,"work_id":"02da18ca-f772-40bb-b5f1-b4549cfa5dc5","year":2020},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:e2737e8d673d0faa451086f3fa27b2a4f53bbb97a6aa89c5d60694ba5b665484","observation_id":"e2da83d5-c215-4790-a094-d5cc45330fdd","resolution":{"observed_at":"2026-06-27T19:01:08.312976Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":", booktitle=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:1bceb9db24eb68a5ebcebd5a5430ba2ba736af0e9d6d465015f6e645417d3417","observation_id":"74701553-808a-4a53-b3d2-6b90d8a28e36","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"10.1016/j.neuroimage.2018.03.045","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T19:01:08.308842Z","title":"2018 , issn =","venue":null,"work_id":"067ffa3a-2ffb-4226-8390-132acce26100","year":2018},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:716d1a9172cbb61c8b9954e17cb09f3281b35ef147e1e44dc270d5d71d13efab","observation_id":"443b8b7d-5bf3-4eef-99eb-579453f8ee17","resolution":{"observed_at":"2026-06-27T19:01:08.310027Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image Denoising , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:53669b0b1bd2699c1e7927c06d4ba5a0ab0bff04aab7256c1f519096e0a7a000","observation_id":"94cbc3c0-cb15-4dda-af47-cbb72c1a6990","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"Journal of digital imaging , volume=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:277bc5173f82ce639d73b8abc93065ecd4f2e751691c8f14ed2dcfe21a119c6b","observation_id":"853582e2-1194-4f65-a8fd-4b8c386c217e","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"IEEE transactions on radiation and plasma medical sciences , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:9fb150af0e939169314da2c3541043aef1920fff7a32fc72bdff007d2a28405f","observation_id":"e3761b1c-1f70-460a-8a59-ac05f8bb6f33","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"Neurocomputing , volume=","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:da2de8e52bb3be51659bb7ff5e9ff21cb2adbc6db9747101eca0b9491981c537","observation_id":"b8dde40c-1bd9-4cad-a518-8da6627ada51","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"Radiology , volume=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:5d996c9e54aff0e0019c02c5f2f42b86ef811d1c35e2955d0f9a03b6091d5c76","observation_id":"a8164e46-3e33-4692-8b4a-992884b77330","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:8a53475c8dece0ebafda1a35bf90504781fbd2db814dda5e0b114d5a162d0aa4","observation_id":"83db5ffa-d0b1-4ccc-9090-55d3d472ff09","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2025 , eprint=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:952293ce71b3bfb51f6486da1a80713dee906d7cd2a97ff1624bfba8c4e111f5","observation_id":"b81d41fe-7ba4-4d6c-9219-4dcdbcca71e9","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2026 , eprint=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:90fc9e547daea03cd71ad6576c1054041d73a48c851bbf05eb1c69a5d1e037bb","observation_id":"cbe7b8c0-043e-4255-80d8-4181bcdfa493","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"10.1007/s10278-018-0150-3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T19:01:08.319417Z","title":"Journal of Digital Imaging , author =","venue":null,"work_id":"7442032c-ca9f-48ed-a570-e86a6155c5a6","year":2019},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:9e1fb60f0682d4a63230e08a638c916d45882351242c211ebdf3066d21cfc6e3","observation_id":"85950322-b43d-4899-ad61-3000c021f257","resolution":{"observed_at":"2026-06-27T19:01:08.320581Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+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":"2026-06-27T18:51:54.881455Z","title":"UDPET: Ultra-low Dose PET Imaging Challenge Dataset","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:8ca84318767402eac1aa9ce4d6df9109a519641d641a0316b6a06d9d61a341a2","observation_id":"709c9f63-4e4f-4c5b-a0ff-a268256caaf9","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2024 , eprint=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:184a0e15fd4c20e322b10892d6331d4ec98f9d7338494ef72cf7d9a564ffdfe0","observation_id":"19d30a9b-8d6c-43ac-a0a7-cd4f170a0f0a","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026-06-27T18:51:54.881455Z","title":"2024 IEEE International Symposium on Biomedical Imaging (ISBI) , pages=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:cb6658b84cd41859f511f5ec8fb37641e11da7ce16e8fb3e4fac7a3b9e1337c1","observation_id":"0b757685-b4c1-4ad5-98ed-5b000af8e152","resolution":{"observed_at":"2026-06-27T18:51:54.881455Z","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":"2026.104039","doi":"10.1016/j.media.2026.104039","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Spencer and Wei Ji and Xiongchao Chen and Qiong Liu and Xueqi Guo and Menghua Xia and Yinchi Zhou and Hui Liu and Liang Guo and Hongyu An and Ulugbek S","venue":null,"work_id":"abb3c9d9-f0fc-4fe0-806d-905ed0948bd7","year":2026},"citing_paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-06-27T18:51:54.881455Z"},"links":{"citing_paper":"/paper/2606.08751"},"observation_digest":"sha256:6cd1dbde4bd4dee823eee1feb3b03ae391803ab39ba0ff56e51657b5c2ecbe0f","observation_id":"c14e8f75-78fb-4e2c-bd50-75a8ce85ef74","resolution":{"observed_at":"2026-06-27T19:01:08.314817Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-15T06:30:58.975436+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2606.08751","last_updated":"2026-06-07T17:51:58Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T23:48:11.819398Z","submitted_at":"2026-06-07T17:51:58Z","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction"},"reference_resolution":{"displayed":53,"state_counts":{"malformed_identifier":0,"metadata_mismatch":5,"parse_uncertain":0,"unresolved":39,"verified_exact":9,"verified_fuzzy":0},"total_outbound_references":53},"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":"2026-07-15T06:30:58.975436+00:00","source":"crossref"},{"observed_at":"2026-07-15T06:30:54.025283+00:00","source":"retraction_watch"}],"thesis":"As of 15 July 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2606.08751."}