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Paper Citation Record · LEDGER

Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:1906.02530.

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

pith.paper-citation-record.v1
1906.02530 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:19:21.049525Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

654
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c06d53d8-131d-410b-926d-d1848d31926c · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 195

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T15:42:47.537381Z

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=arxiv_source observed=2026-05-10T15:42:47.274448Z digest=sha256:50749d918ccc147d09a4f1efb7eae053d6dabec045ff27748d21b306097de5e1

Observation 26dccf14-7689-49e4-8c33-4c325d735331 · inbound

Revisiting Bayesian Model Averaging in the Era of Foundation Models cites this paper.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T13:25:03.408251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:25:03.408251Z digest=sha256:e0420eb2c3123141d8b23b18c66d82367c7d082bea0acb7453ab1a2eb1439328

Observation a7af000c-fd6a-45a6-8d01-ef59fd58388e · inbound

BD at BEA 2025 Shared Task: MPNet Ensembles for Pedagogical Mistake Identification and Localization in AI Tutor Responses cites this paper.

BD at BEA 2025 Shared Task: MPNet Ensembles for Pedagogical Mistake Identification and Localization in AI Tutor Responses Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T11:35:48.635519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:35:48.635519Z digest=sha256:36b23b7676112cfb2c4687f95fb7cd64ac11108654fd3c3a4e037155f32f19ea

Observation fe690e5e-af6c-477c-a7d7-022ffe94f14b · inbound

PaTAS: A Framework for Trust Propagation in Neural Networks Using Subjective Logic cites this paper.

PaTAS: A Framework for Trust Propagation in Neural Networks Using Subjective Logic Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-03T20:19:44.387122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:19:44.387122Z digest=sha256:f7a61cc4cbb33555b9fbacd1f9b9c9655c62d5c6297e05b20ba55b1c85c7ed1b

Observation 175aeb27-6708-4a04-b992-0b88f9396709 · inbound

Variance-Gated Ensembles: An Epistemic-Aware Framework for Uncertainty Estimation cites this paper.

Variance-Gated Ensembles: An Epistemic-Aware Framework for Uncertainty Estimation Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-03T03:26:55.714514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:26:55.714514Z digest=sha256:4b769963430f70f23718256dffda62aa99ce4223335b36e5f4d4f8ba9aa7b8ef

Observation 819a2046-b593-4841-94e1-a40c1cd87898 · inbound

Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification cites this paper.

Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T00:15:52.177728Z

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=2026-05-10T18:38:30.129473Z digest=sha256:fbd50b7e558c1374cc89fe4bd51c2080a6940992315472df3caceaedc3b17ad3

Observation 752b91c7-008d-456e-9bec-37e18e59a8c6 · inbound

Prior-Aligned Data Cleaning for Tabular Foundation Models cites this paper.

Prior-Aligned Data Cleaning for Tabular Foundation Models Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:31:16.959775Z

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=2026-05-07T16:47:31.905149Z digest=sha256:8566f63dd43b634b1ef73ed0b7b65f3dedb4d668fb2a5a4fa050bd9f67475246

Observation 94c4bd7a-97cb-4d6c-a48a-c288f87d8f86 · inbound

Operator learning for the 2D incompressible Navier-Stokes equations: a conformal prediction approach in the data-scarce regime cites this paper.

Operator learning for the 2D incompressible Navier-Stokes equations: a conformal prediction approach in the data-scarce regime Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:47:25.758717Z

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=2026-06-27T18:39:56.578189Z digest=sha256:c49c60ddb1e326380f9a31ad8a044ac42d508892b5882f7f0bb1d374de18fb56

Observation 67117028-5131-401b-baa4-992f0cee2f64 · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 184

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T07:11:45.332149Z

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=arxiv_source observed=2026-06-28T07:05:18.026601Z digest=sha256:43591fcd9a28273dfffe9c25dd979d5cdf52fcde28c104f74b30a9c8e86399c7

Observation 430dac04-9c4a-43bc-bf1b-06c5b4316666 · inbound

Collaborative Large and Small Language Models for Accurate and Scalable Data Repair cites this paper.

Collaborative Large and Small Language Models for Accurate and Scalable Data Repair Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T23:19:04.259597Z

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=2026-06-26T22:25:39.533017Z digest=sha256:d27aba71344fdb7b6b7410cd414110be82d3b660f9ad9eb66031265a539a4aa5

Observation 67314425-a0cc-4175-afd1-c92fef317dc8 · inbound

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language cites this paper.

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 47

Resolution
unresolved
no resolver link, observed 2026-07-11T23:16:58.545731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T23:16:58.545731Z digest=sha256:7721edbbdcf7acdb3c4b0cdbb447eb32a19668049e5b2effae7fd824bdacb7f6

Observation 2f994fcc-6dd6-472b-a3cd-67fd93245a14 · inbound

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language cites this paper.

Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 47

Resolution
unresolved
no resolver link, observed 2026-07-13T07:02:13.140334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T07:02:13.140334Z digest=sha256:005853e91d34dfd1ed682ceabdc07df3b1f6f2c47958449bcb7544bae99a92a3

Observation 37e7be3d-96d2-4858-8be1-871f1e0b5a5b · inbound

Condition-Stratified Robustness Analysis of Post-Hoc Calibration Methods for Probabilistic Classifiers cites this paper.

Condition-Stratified Robustness Analysis of Post-Hoc Calibration Methods for Probabilistic Classifiers Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-14T04:52:20.985671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T04:52:20.985671Z digest=sha256:0533aa9bcf4709f40116f15eb480716217422c004b1c95e16c591451f535bafc

Observation 59b928a4-bdb2-4ca1-ae40-ab33406053ce · inbound

Validity, Reliability, and Transparency in Artificial Intelligence Regulation cites this paper.

Validity, Reliability, and Transparency in Artificial Intelligence Regulation Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T23:19:21.049525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:19:21.049525Z digest=sha256:41d41833bcd48ca1c5ad01b084b1d267ecec20f5a72e6a10f444e44a211bfb3d