Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.09792.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:26:17.890176Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T12:53:28.551765Z
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 8b55b2ec-2faa-4d9e-ac74-c675647040c2 · inbound
Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulation cites this paper.
Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulation Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T11:06:13.209053Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 95bb2062-0c67-4eee-8a47-3ca414599698 · inbound
DDFP: Data-dependent Frequency Prompt for Source Free Domain Adaptation of Medical Image Segmentation cites this paper.
DDFP: Data-dependent Frequency Prompt for Source Free Domain Adaptation of Medical Image Segmentation Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:26:17.890176Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 70925246-f7ba-417f-9f8a-0f820d2c7c82 · inbound
MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation cites this paper.
MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T12:53:28.553970Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.