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Paper Citation Record · LEDGER

Bayesian Active Learning By Distribution Disagreement

As of 12 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2501.01248.

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

pith.paper-citation-record.v1
2501.01248 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:36:41.470003Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 03f913aa-6b80-4ffa-b558-bc69cf8bd9e9 · outbound

This paper cites Escaping the sample trap: Fast and accurate epistemic uncertainty estimation with pairwise-distance estimators.

Bayesian Active Learning By Distribution Disagreement Escaping the sample trap: Fast and accurate epistemic uncertainty estimation with pairwise-distance estimators

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T22:36:41.361149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2071bd24-50b0-4f68-9bb1-c96e13d22323 · outbound

This paper cites Normalizing flow ensembles for rich aleatoric and epistemic uncertainty model- ing.

Bayesian Active Learning By Distribution Disagreement Normalizing flow ensembles for rich aleatoric and epistemic uncertainty model- ing

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.916957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 8f6653c2-95e0-47b9-8700-e629941051ec · outbound

This paper cites Sequential graph convolutional network for active learning.

Bayesian Active Learning By Distribution Disagreement Sequential graph convolutional network for active learning

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.901534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.372792Z digest=sha256:15bebfecad95cf089b180f35b57e9a1c0f4770eb56751561abb82b2c236b5e49

Observation 67bdc7a3-7d8b-4fc3-91c4-f25fdde14f42 · outbound

This paper cites Neural spline flows.

Bayesian Active Learning By Distribution Disagreement Neural spline flows

Reference 4

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unresolved
no resolver link, observed 2026-08-10T22:36:41.377643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 60f25a90-2fc8-4b03-8afc-97124cbd7f36 · outbound

This paper cites Sarcos Data.

Bayesian Active Learning By Distribution Disagreement Sarcos Data

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.873729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.383258Z digest=sha256:55a0568f0fbc4e2351dc2c3762f88633fa745fca386dfaf2fbdc1d3eb6efb459

Observation 7a08f384-29ea-469e-93cd-7d0bc99ce178 · outbound

This paper cites DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks.

Bayesian Active Learning By Distribution Disagreement DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

Reference 6

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unresolved
no resolver link, observed 2026-08-10T22:36:41.389554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 59020a6b-6000-4d86-be69-b65f00f12b85 · outbound

This paper cites Deep bayesian active learning with image data.

Bayesian Active Learning By Distribution Disagreement Deep bayesian active learning with image data

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.856552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.395596Z digest=sha256:dbbdf2b68c25f757429c8a64ec1bf7db0ef50a0913a194bb4cb244778f029936

Observation c93f7bc4-30c5-4c1e-882d-4aa61b1cb47d · outbound

This paper cites Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets.

Bayesian Active Learning By Distribution Disagreement Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T22:36:41.400773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b6786a7e-b4b8-4a4f-a92d-cbc511f240ec · outbound

This paper cites Superconductivty Data.

Bayesian Active Learning By Distribution Disagreement Superconductivty Data

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T22:36:41.405812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:36:41.405812Z digest=sha256:a63b35155164c3ce4814d3b777bdefdcc1148e48bc79b87ac233358a8fca8bec

Observation 3a30aa93-1abd-4d2b-a57d-8427311fb45e · outbound

This paper cites Randomness is the root of all evil: More reliable evaluation of deep active learning.

Bayesian Active Learning By Distribution Disagreement Randomness is the root of all evil: More reliable evaluation of deep active learning

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.840280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.411429Z digest=sha256:8bca2ad07b00f91844264ed129ad8cda18471ff62f57b45f1b9c6c0dbbe4d53c

Observation ffa21bb0-8c2b-49cd-a0b4-793134533504 · outbound

This paper cites Regression tree-based active learning.

Bayesian Active Learning By Distribution Disagreement Regression tree-based active learning

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.823611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.417514Z digest=sha256:8a5877b107d85274b2b1f172187577e0fa9909348cbf77deab582b5bc43fb73c

Observation 60204523-7dee-429b-ae0f-f7b9e00dbf69 · outbound

This paper cites Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning.

Bayesian Active Learning By Distribution Disagreement Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.808878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.423232Z digest=sha256:2dca2e6ca6477d710b1c7a9b9cdb2bda4bfde6f03ef132c208c89547258f6dba

Observation e6a1ce3f-b539-4034-a4db-4b8e4fc3ce91 · outbound

This paper cites Navigating the pitfalls of active learning evaluation: A systematic framework for meaningful performance assessment.

Bayesian Active Learning By Distribution Disagreement Navigating the pitfalls of active learning evaluation: A systematic framework for meaningful performance assessment

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.792698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.429024Z digest=sha256:167d2d457dea89e86670d7808d82ade5adf36c9abe63cd4de4d8734f6e794e81

Observation 9632cb94-ba2f-47aa-8943-e386c5ace53a · outbound

This paper cites Hyperparameter tuning mlp’s for probabilistic time series forecasting.

Bayesian Active Learning By Distribution Disagreement Hyperparameter tuning mlp’s for probabilistic time series forecasting

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.776680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.434875Z digest=sha256:365ca34e7d3b7c2e190e60cbb95cd785e1dac1e9ddab608a59c2cf54b2809f28

Observation 9d1605d3-b0a4-43b6-a9de-4330deebcc48 · outbound

This paper cites Diamonds Data.

Bayesian Active Learning By Distribution Disagreement Diamonds Data

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.759562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.439873Z digest=sha256:643f984a31c66bc0f4ef8ee96fa1871456f3bd618d4b5661015b815dcd04173f

Observation 9e548f73-de6c-4468-879f-9edefb40066a · outbound

This paper cites Masked autoregressive flow for density estimation.

Bayesian Active Learning By Distribution Disagreement Masked autoregressive flow for density estimation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T22:36:41.445366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:36:41.445366Z digest=sha256:fdfcda1331086e95aa2834084ec7aef109445e2df3142584b540c7013be3bbd3

Observation 25e496e4-6bd6-4b88-b5f8-ca9c7666ac63 · outbound

This paper cites Ac- tiveglae: A benchmark for deep active learning with transformers.

Bayesian Active Learning By Distribution Disagreement Ac- tiveglae: A benchmark for deep active learning with transformers

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.732470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.450051Z digest=sha256:ad743d6efb7c22151634f7566207bc10451302b99dd06625aaa58a1a29754a64

Observation b313b96f-e55a-426f-8c9e-a53efb463433 · outbound

This paper cites Bayesian active learning with fully bayesian gaussian processes.

Bayesian Active Learning By Distribution Disagreement Bayesian active learning with fully bayesian gaussian processes

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.716495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.454876Z digest=sha256:f3c63d356ad47c7987569d2123acd57c0f123bc0e63b3e6abca3c50e0e458e25

Observation 4f2ad1bf-07ba-4f13-a8c6-2af3c1624b44 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

Bayesian Active Learning By Distribution Disagreement Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T22:36:41.459811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:36:41.459811Z digest=sha256:67e5a01c3e42ebc964af6a4c12e141ba591e2019b005300afa97f9fd7f656d55

Observation 35b0179a-c677-414d-9d80-27446543cf46 · outbound

This paper cites Parkinsons Telemonitoring.

Bayesian Active Learning By Distribution Disagreement Parkinsons Telemonitoring

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T22:36:41.465220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:36:41.465220Z digest=sha256:3861ae2c3fc9deaeab4e90f461f6e5486b45b6d0f06e3e711f1cc3e5d5de010a

Observation 1dd33a1a-0c50-4e1c-954b-8ca763d9d510 · outbound

This paper cites A cross-domain benchmark for active learning, 2024.

Bayesian Active Learning By Distribution Disagreement A cross-domain benchmark for active learning, 2024

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:36:41.699858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T22:36:41.470003Z digest=sha256:e4f69c3d5c6fc7e47f8c54d524a3385b23fa00360f0e2fabd2b4e10e2cc1e16b

Pith citing papers

No inbound Pith citation observations are available.