Paper Citation Record · LEDGER

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.18278.

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

pith.paper-citation-record.v1
2607.18278 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:40:43.024616Z

measured 33 of 33 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 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

33 of 33 outbound references displayed

verified exact0
verified fuzzy0
unresolved32
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malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 83436d99-e530-4906-92cb-b11f37e6f51d · outbound

This paper cites Pitfalls of in- domain uncertainty estimation and ensembling in deep learning.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Pitfalls of in- domain uncertainty estimation and ensembling in deep learning

Reference 1

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Source-reported events for the cited work

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Observation 5d737c02-e8d4-4867-924e-3ed87353ce8e · outbound

This paper cites Addressing failure prediction by learning model confidence.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Addressing failure prediction by learning model confidence

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:38.920506Z

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Observation 80f435a7-66e2-4447-898f-f756a0c8ef6e · outbound

This paper cites Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:39.005075Z

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Unavailable: canonical work link unavailable.

Observation 6a31970b-2d63-42f6-aa53-04189dc73827 · outbound

This paper cites Phases of uncertainty: Confidence–calibration dynamics in language model training.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Phases of uncertainty: Confidence–calibration dynamics in language model training

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:39.144959Z

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Observation 2d741bdf-bee9-4127-9b67-2eb9ccb132e2 · outbound

This paper cites On the foundations of noise-free selective classification.Journal of Machine Learning Research, 11(5):1605–1641, 2010.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration On the foundations of noise-free selective classification.Journal of Machine Learning Research, 11(5):1605–1641, 2010

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:39.284749Z

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Unavailable: canonical work link unavailable.

Observation e55eb204-705c-478e-b5cc-18bf7ea4caf6 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:39.424754Z

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Observation 43faf19b-ae1e-488f-9657-b9a25082d7aa · outbound

This paper cites Datasheets for datasets.Communications of the ACM, 64(12):86–92, 2021.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Datasheets for datasets.Communications of the ACM, 64(12):86–92, 2021

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:39.572908Z

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Unavailable: canonical work link unavailable.

Observation ebbd52c1-e2a5-4b6c-a90a-5d7aad99255c · outbound

This paper cites Selective Classification for Deep Neural Networks.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Selective Classification for Deep Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:39.737356Z

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Observation 0b217baa-67fb-4aa5-9f25-aaddd8ccdc28 · outbound

This paper cites Selectivenet: A deep neural network with an integrated reject option.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Selectivenet: A deep neural network with an integrated reject option

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:39.910993Z

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Observation 467929dd-9a06-4812-8039-aab205c65756 · outbound

This paper cites an unresolved cited work.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:40.094211Z

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Observation 400a427b-5402-4a2f-986a-a1c352614331 · outbound

This paper cites Why do tree-based models still outperform deep learning on typical tabular data? InAdvances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Why do tree-based models still outperform deep learning on typical tabular data? InAdvances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:40.288201Z

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Observation 1823934c-1c7d-4f3f-9d1a-267e300f3360 · outbound

This paper cites Weinberger.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Weinberger

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:40.416693Z

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Observation b0d96079-2623-4f01-8c03-705427211002 · outbound

This paper cites A baseline for detecting misclassified and out-of-distribution examples in neural networks.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration A baseline for detecting misclassified and out-of-distribution examples in neural networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:40.544744Z

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Observation 84cb4d3d-5aa2-4e28-9e0b-fe73e66f4e89 · outbound

This paper cites Better by default: Strong pre-tuned MLPs and boosted trees on tabular data.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:40.679028Z

Source-reported events for the cited work

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Observation 7a079776-c904-41c9-a485-70207e334625 · outbound

This paper cites Guan, and Maya Gupta.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Guan, and Maya Gupta

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:40.824954Z

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Observation 5abd9f5f-f645-448c-8a0f-cca919e9e836 · outbound

This paper cites Accurate uncertainties for deep learning using calibrated regression.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Accurate uncertainties for deep learning using calibrated regression

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:40.942908Z

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Unavailable: canonical work link unavailable.

Observation 42a99b1a-82dd-4430-b54c-f3d36f5e4a39 · outbound

This paper cites Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with dirichlet calibration.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with dirichlet calibration

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:41.094840Z

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Unavailable: canonical work link unavailable.

Observation 132b7021-fb7d-44c7-8190-8af74dfd65b8 · outbound

This paper cites Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:41.224764Z

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Unavailable: canonical work link unavailable.

Observation d59892ad-8b6e-4a42-a1e4-765b38411002 · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:41.444758Z

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Observation c9b839a4-efe0-4d7e-81e9-efb9f353fce0 · outbound

This paper cites Owens, and Yixuan Li.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Owens, and Yixuan Li

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:41.556018Z

Source-reported events for the cited work

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Observation b7e05f9f-7fd7-4a42-b2d2-d1e8cdc51326 · outbound

This paper cites When do neural nets outperform boosted trees on tabular data? InAdvances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration When do neural nets outperform boosted trees on tabular data? InAdvances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:41.759938Z

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Observation a496416e-71ca-4569-9d1a-6d7339cc7e1c · outbound

This paper cites CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:41.846764Z

Source-reported events for the cited work

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Observation 86c3be45-8267-43a9-9bb6-135f464d758d · outbound

This paper cites Revisiting the calibration of modern neural networks.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Revisiting the calibration of modern neural networks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:41.972665Z

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Unavailable: canonical work link unavailable.

Observation 3ad6c22d-a69e-4574-8d2f-2e0f2ed0c19f · outbound

This paper cites Model cards for model reporting.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Model cards for model reporting

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:42.064656Z

Source-reported events for the cited work

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Observation 5bf7d92e-36af-420e-918d-7796549194c6 · outbound

This paper cites Cooper, and Milos Hauskrecht.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Cooper, and Milos Hauskrecht

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:42.132522Z

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Unavailable: canonical work link unavailable.

Observation 70975b74-efb1-44f9-a91e-fca60bcdd3b8 · outbound

This paper cites Predicting good probabilities with supervised learning.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Predicting good probabilities with supervised learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:42.224750Z

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Observation 595110c8-8d03-45d1-b005-bb9cafaad9b6 · outbound

This paper cites Sculley, Sebastian Nowozin, Joshua Dillon, Balaji Lakshminarayanan, and Jasper Snoek.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Sculley, Sebastian Nowozin, Joshua Dillon, Balaji Lakshminarayanan, and Jasper Snoek

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:42.398207Z

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Observation 81ed7e8d-da41-4893-b4b4-b83fdb338914 · outbound

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FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Unresolved cited work

Reference 28

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Observation df1144f8-696c-4d8a-aff1-8f7e4fe963da · outbound

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FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Unresolved cited work

Reference 29

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Observation cb103e8d-d629-446d-9882-4f8e055bdb10 · outbound

This paper cites an unresolved cited work.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:42.743482Z

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Observation 8ebb835a-c8ce-45fa-8feb-519100b043f3 · outbound

This paper cites Springer, 2005.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Springer, 2005

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:42.834751Z

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Observation dfcb4e9d-c0db-4623-9327-b2128864a8fd · outbound

This paper cites Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T09:40:42.924761Z

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Observation c7acf1d8-cf91-4e07-960e-f9e495b0725d · outbound

This paper cites Transforming classifier scores into accurate multiclass probability estimates.

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration Transforming classifier scores into accurate multiclass probability estimates

Reference 33

Resolution: malformed identifier; no resolver link, observed 2026-08-02T09:40:43.024616Z

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Pith citing papers

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