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Paper Citation Record · LEDGER

HRFormer: High-Resolution Transformer for Dense Prediction

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2110.09408.

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

pith.paper-citation-record.v1
2110.09408 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:27:41.820067Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T06:38:05.749993Z

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 2377853e-d169-473b-b0f4-c55d90ee455e · inbound

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving cites this paper.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving HRFormer: High-Resolution Transformer for Dense Prediction

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T11:27:41.820067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:27:41.820067Z digest=sha256:a28a1337299d6253bb23077249dab7b540c2103658853956c849d132923f0dcc

Observation f18e451b-8161-46c2-b772-7e2613bbefce · inbound

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment cites this paper.

FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment HRFormer: High-Resolution Transformer for Dense Prediction

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-06T22:46:19.990624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:46:19.990624Z digest=sha256:977cd39890ca1f820e91fd66470b3e53e36145e437915d79bcadf7dab5cacbec

Observation 2d8289d9-32c5-4689-b2d0-f2de7b9836a2 · inbound

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model cites this paper.

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model HRFormer: High-Resolution Transformer for Dense Prediction

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-06T17:22:14.730911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:22:14.730911Z digest=sha256:536ae3eed543ae2f6ff57a75af6b39c83abbcd8ca64a182465a42c6e065738c7

Observation a03cc7d0-14dc-4a22-97fc-d0089f64b267 · inbound

Dynamic Pattern Alignment Learning for Pretraining Lightweight Human-Centric Vision Models cites this paper.

Dynamic Pattern Alignment Learning for Pretraining Lightweight Human-Centric Vision Models HRFormer: High-Resolution Transformer for Dense Prediction

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-05T22:22:58.911985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:22:58.911985Z digest=sha256:74db9faa7f792f98bcefc50d861bbd49696762482fcc85741a6a4b20d7567495

Observation 0eb1e0b0-81eb-46ac-810a-cb2f1f225a0b · inbound

Accelerating Vision Transformers with Adaptive Patch Sizes cites this paper.

Accelerating Vision Transformers with Adaptive Patch Sizes HRFormer: High-Resolution Transformer for Dense Prediction

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-18T05:42:24.430461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T05:41:48.429067Z digest=sha256:5e51b5b4f6dbf62aa78f96194915d19e095ca466f2a626fdb56f9fc602b921d6

Observation c16600e9-b3a5-4c1f-b0ab-50c328c102d0 · inbound

Dual-Prompt CLIP with Hybrid Visual Encoders for Occluded Person Re-Identification cites this paper.

Dual-Prompt CLIP with Hybrid Visual Encoders for Occluded Person Re-Identification HRFormer: High-Resolution Transformer for Dense Prediction

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-20T06:38:05.752161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T06:36:04.441946Z digest=sha256:b35d9072f838e1faff30d455a58727bf6a3c281bf335dc008f147e73ee07372a