Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T11:17:50.456958Z
Paper Citation Record · LEDGER
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression
As of 9 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2509.03012.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
15 of 15 outbound references displayed
- verified exact6
- verified fuzzy5
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ba260054-35fd-4987-9a3f-96e491ba7a52 · outbound
This paper cites Calibration of Model Uncertainty for Dropout Variational Inference.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Calibration of Model Uncertainty for Dropout Variational Inference
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:17:50.608288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2804b8ff-7434-4a07-bf25-e20fdaf894b4 · outbound
This paper cites DEJA VU: Continual Model Generalization For Unseen Domains.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression DEJA VU: Continual Model Generalization For Unseen Domains
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:17:50.589323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b5db2161-2d12-4290-a826-4e0c65da89d1 · outbound
This paper cites Neural Unsupervised Domain Adaptation in NLP---A Survey.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Neural Unsupervised Domain Adaptation in NLP---A Survey
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:17:50.570792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ade6282d-ea36-4020-b9a3-b37a61540d66 · outbound
This paper cites HypUC: Hyperfine Uncertainty Calibration with Gradient-boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression HypUC: Hyperfine Uncertainty Calibration with Gradient-boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:17:50.533116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 76af75b6-86f5-4ec9-9738-ecb6c172d0ec · outbound
This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Tent: Fully Test-time Adaptation by Entropy Minimization
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:17:50.449339Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef39eef8-178d-4699-8252-f4f5da54d2b5 · outbound
This paper cites Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:17:50.497319Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d37c006e-64b2-4856-9411-24b02fbda841 · outbound
This paper cites Domain adaptation with structural correspondence learning.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Domain adaptation with structural correspondence learning
Reference 2010
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T11:17:50.721108Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8b0ff6ab-addb-42b0-9bdd-74f0c3bca112 · outbound
This paper cites Deep ordinal regres- sion network for monocular depth estimation.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Deep ordinal regres- sion network for monocular depth estimation
Reference 2013
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T11:17:50.707291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 06cd630d-8360-48f2-9692-2ca6282993fc · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Adam: A Method for Stochastic Optimization
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:17:50.410910Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2336795d-aa43-4708-b5ea-134c19f88a85 · outbound
This paper cites Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:17:50.415876Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f6d298a-ad06-4474-a6c0-e0f78d7a2c4c · outbound
This paper cites Learning to combine: Knowledge aggregation for multi-source domain adaptation.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Learning to combine: Knowledge aggregation for multi-source domain adaptation
Reference 2019
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T11:17:50.655445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1ad19bed-5104-4456-86bb-5520093478f5 · outbound
This paper cites USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolution.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolution
Reference 2020
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:17:50.552754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2d727229-bbcf-49a1-b534-f794ad35e26d · outbound
This paper cites Online domain adaptation for semantic segmentation in ever-changing conditions.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Online domain adaptation for semantic segmentation in ever-changing conditions
Reference 2021
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T11:17:50.684793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c081a611-e5e9-49cf-a89f-6f5f19108d47 · outbound
This paper cites Domain-adversarial training of neural networks.The journal of machine learning research, 17(1):2096–2030,.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Domain-adversarial training of neural networks.The journal of machine learning research, 17(1):2096–2030,
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:17:50.406660Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 662bc5b2-499b-46e9-8842-d7b7814eaefb · outbound
This paper cites Monocular depth estimation in new environments with absolute scale.
Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression Monocular depth estimation in new environments with absolute scale
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T11:17:50.670166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Pith citing papers
No inbound Pith citation observations are available.