Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2307.02457.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:31:34.942871Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T22:18:59.568679Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation d541edde-ec6a-410d-afd5-0e4a80bb99ed · inbound
Incorporating Uncertainty-Guided and Top-k Codebook Matching for Real-World Blind Image Super-Resolution DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7f22d33-8d03-48de-8de3-9224c6d98b2f · inbound
RAGSR: Regional Attention Guided Diffusion for Image Super-Resolution DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 48
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1afdfddf-bd24-42e9-b4bc-638e8ebe1f9c · inbound
DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7e498552-78fa-4c7f-b56e-6d924e37137e · inbound
Allo{SR}$^2$: Rectifying One-Step Super-Resolution to Stay Real via Allomorphic Generative Flows DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 49
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d8f0903f-0d1b-4ae2-b0f7-db8e47aab5f2 · inbound
GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 20b49c7e-fd48-42d7-b360-443cfe8dbc21 · inbound
SR-Prominence: A Crowdsourced Protocol and Dataset Suite for Perceptually-Weighted Super-Resolution Artifact Evaluation DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b3129f54-841e-41f6-bd49-e1b71ec3222e · inbound
DreamSR: Towards Ultra-High-Resolution Image Super-Resolution via a Receptive-Field Enhanced Diffusion Transformer DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 64
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b47b1b62-78ce-4591-adce-e861ea89b721 · inbound
Language-Assisted Super-Resolution from Real-World Low-Resolution Patches DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 97
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 3c6537aa-77ee-4105-b881-163c8b6f0a42 · inbound
Language-Assisted Super-Resolution from Real-World Low-Resolution Patches DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Reference 97
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.