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Paper Citation Record · LEDGER

HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2306.05390.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2306.05390 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:38:35.231995Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-16T07:59:32.723527Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 765984a9-eb1e-4be8-97bc-ad4fc20caa44 · inbound

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? cites this paper.

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:59:32.725723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-16T07:59:32.638758Z digest=sha256:ee03f73d607c06187622c70bc18230ca86fec9ec4bae52dcfee037a34c82a5e5

Observation 7975458a-8785-40ce-9946-5b2fed593892 · inbound

UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularity cites this paper.

UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularity HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-10T23:34:51.305389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:34:51.305389Z digest=sha256:76406b3c255386926dfd0fcefe231afe687faee7b110d0ac3b775a973b728b65

Observation 2f36bdd4-6afc-4347-af47-0fb8d95ba3b3 · inbound

Visual Autoregressive Modeling for Image Super-Resolution cites this paper.

Visual Autoregressive Modeling for Image Super-Resolution HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-09T21:47:59.585416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T21:47:59.585416Z digest=sha256:79e397e70c0d40a256c43b41348e605e3ca389465fdad8143366afe4eed4c6ed

Observation 64ed37da-04c3-422c-a7d2-bf89a10db3cc · inbound

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study cites this paper.

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-16T11:38:35.231995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:38:35.231995Z digest=sha256:80a6d23dfdde484653cbdf1132eb3d5d442ab7e4a8bfae0b4c81016ea646b20a

Observation 1879ab85-4c57-428d-b0db-929350a65d4f · inbound

UniCustom: Unified Visual Conditioning for Multi-Reference Image Generation cites this paper.

UniCustom: Unified Visual Conditioning for Multi-Reference Image Generation HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:02:23.953369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-13T05:53:21.851578Z digest=sha256:6a6d40922edc5608f9d76adcb476feb241c1faa8639dd6307ce6c687f1b08b73

Observation 98c3470e-a455-4088-82d0-c4a6c16ea383 · inbound

UniCustom: Unified Visual Conditioning for Multi-Reference Image Generation cites this paper.

UniCustom: Unified Visual Conditioning for Multi-Reference Image Generation HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:03:03.318400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-14T22:00:01.349754Z digest=sha256:5a043bfc157a2ce0b087f338346fd7e6e2f73a3118616ca59580444882560219

Observation 33df100a-a9ec-4b61-8c83-e6807b47a55b · inbound

MDTD-ArtIR: Benchmarking Image Editing and Restoration Models for Art Image Restoration under Texture-Overlay Degradations cites this paper.

MDTD-ArtIR: Benchmarking Image Editing and Restoration Models for Art Image Restoration under Texture-Overlay Degradations HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T00:29:10.843392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:29:10.843392Z digest=sha256:ab3bf532a1abb650cd71cd59ba6f55ef0e8b4312c1bfdf2b0f868009fd1afa0d

Observation 9b8f2759-7d94-4dca-a0fe-1ec9c9bb1635 · inbound

InSight-doc: Agentic Visual Perception for Long-Document Understanding cites this paper.

InSight-doc: Agentic Visual Perception for Long-Document Understanding HQ-50K: A Large-scale, High-quality Dataset for Image Restoration

Reference 102

Resolution
unresolved
no resolver link, observed 2026-08-12T20:43:52.607804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:43:52.607804Z digest=sha256:0f42c82ae5db54141d1c962992e4345737631ef4125a87340bf398eecb18a67f