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Paper Citation Record · LEDGER

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization

As of 9 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2506.16189.

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

pith.paper-citation-record.v1
2506.16189 v1

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:48:27.817236Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

66 of 66 outbound references displayed

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  • verified fuzzy55
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e725086-6e09-4759-a382-afacbd2a723e · outbound

This paper cites Turner, Eric Nalisnick, and José Miguel Hernández-Lobato.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Turner, Eric Nalisnick, and José Miguel Hernández-Lobato

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1b569a59-f688-4fa2-ad12-308b2c4814ff · outbound

This paper cites Adaptive Conformal Prediction by Reweighting Nonconformity Score.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Adaptive Conformal Prediction by Reweighting Nonconformity Score

Reference 2

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Source-reported events for the cited work

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Observation b1b88628-b396-46f5-bb93-57a8c0159e53 · outbound

This paper cites Conformal pid control for time series prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal pid control for time series prediction

Reference 3

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Source-reported events for the cited work

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Observation 7dce510f-9c7a-4beb-b1d9-b834ca96b406 · outbound

This paper cites Conformal prediction: A gentle introduction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction: A gentle introduction

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a8fabd4f-e5aa-4b8e-a45e-5e5cbc5ba6ce · outbound

This paper cites Theoretical Foundations of Conformal Prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Theoretical Foundations of Conformal Prediction

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:48:22.984747Z digest=sha256:0fc36480ce31d038926ce82df496dafce9777a58df13d6eb57c5c88465b2be24

Observation 564bc8a0-bca9-4d8d-bc1c-78f628443496 · outbound

This paper cites Conformal risk control.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal risk control

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f87d48fd-272f-4f07-9d08-66397ece798f · outbound

This paper cites Online conformal prediction with decaying step sizes.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Online conformal prediction with decaying step sizes

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:23.228736Z digest=sha256:9d718764e6991404bad65674d1e9a1c9bed12cd4048def4d1b9d2c6d4f393a5e

Observation ba19ad65-bb47-4a9f-a8bf-d73ae3abd88c · outbound

This paper cites Frame averaging for equivariant shape space learning.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Frame averaging for equivariant shape space learning

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:23.323316Z digest=sha256:f33233c0aa0d54a2a860ae89744b0091dbb171f63c57a9032e931ef6d149ddab

Observation 8fb1ae37-7269-4507-a7ef-150bc7ca4470 · outbound

This paper cites Conformal prediction beyond exchangeability.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction beyond exchangeability

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation eea7d01d-b311-4cf9-8e04-6dcedfeb74f2 · outbound

This paper cites Varshney.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Varshney

Reference 10

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b8c37690-db65-4469-a099-7208b1422cdd · outbound

This paper cites Varshney, Lav R.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Varshney, Lav R

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e2d118c2-88c1-4491-8774-73e4fc187b99 · outbound

This paper cites The need for uncertainty quantification in machine-assisted medical decision making.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization The need for uncertainty quantification in machine-assisted medical decision making

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation dd194b16-a3b1-4164-9639-c84ef3727131 · outbound

This paper cites B-spline cnns on lie groups.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization B-spline cnns on lie groups

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation dbbaff6d-90df-47d0-893e-9698519785db · outbound

This paper cites Probabilistic symmetries and invariant neural networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Probabilistic symmetries and invariant neural networks

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 559ee8d3-40f8-4729-940a-50030962b093 · outbound

This paper cites Does equivariance matter at scale?.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Does equivariance matter at scale?

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:48:23.885348Z digest=sha256:a9dbe4dcf1ffd971f632a3098fe3004403eedffafac75f8cabbe1118e1217bdc

Observation 4211aa2b-53e1-41a4-bdb7-d21c2edfb31c · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 16

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no resolver link, observed 2026-08-06T23:48:23.944511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:48:23.944511Z digest=sha256:e7b344e3cef6769d62e8e7682e32cd629775fac19abb2b4a2a73015d57daf545

Observation 9ce3c31d-9e1f-407d-88ac-8ef97b5dc975 · outbound

This paper cites Knowing what you know: Valid and validated confidence sets in multiclass and multilabel prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Knowing what you know: Valid and validated confidence sets in multiclass and multilabel prediction

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b6385c79-cba4-4f7b-b58f-95f4035b3de3 · outbound

This paper cites Group equivariant convolutional networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Group equivariant convolutional networks

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation cb1824e0-062c-41ff-b166-f8354ad84792 · outbound

This paper cites Gauge equivariant convolutional networks and the icosahedral CNN.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Gauge equivariant convolutional networks and the icosahedral CNN

Reference 19

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ea98d84e-586f-4f0a-8033-4ce544ceeec1 · outbound

This paper cites an unresolved cited work.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 96500fb2-e0b4-41ac-be95-1c09f264d7c4 · outbound

This paper cites Malliaros, Yoshua Bengio, and David Rolnick.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Malliaros, Yoshua Bengio, and David Rolnick

Reference 21

Resolution
verified fuzzy
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7d535c16-4d93-432d-b795-38a3fcfaa435 · outbound

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CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6369fb4f-dea3-4e5b-bf03-f620c4c8d634 · outbound

This paper cites Generalizing convolutional neural networks for equivariance to lie groups on arbitrary continuous data.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Generalizing convolutional neural networks for equivariance to lie groups on arbitrary continuous data

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2641d597-b9f6-408d-a640-073b42871732 · outbound

This paper cites A practical method for constructing equivariant multilayer perceptrons for arbitrary matrix groups.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization A practical method for constructing equivariant multilayer perceptrons for arbitrary matrix groups

Reference 24

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verified fuzzy
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b7f1a37a-1c8d-4429-96a8-3cab5f994d91 · outbound

This paper cites Guest editorial special issue on geometric deep learning in medical imaging.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Guest editorial special issue on geometric deep learning in medical imaging

Reference 25

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verified fuzzy
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8cc204e9-8f61-4773-b333-34713d72d8f7 · outbound

This paper cites A survey of uncertainty in deep neural networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization A survey of uncertainty in deep neural networks

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 960a7e0b-8a04-4e21-97f5-6730c754f2a5 · outbound

This paper cites Cand \`e s.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Cand \`e s

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:33.816937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation af4671aa-7cc8-4213-aed9-4a88538db9ae · outbound

This paper cites Localized conformal prediction: A generalized inference framework for conformal prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Localized conformal prediction: A generalized inference framework for conformal prediction

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-06T23:48:33.648784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 982bc5a8-9d57-4738-8e0c-9f8335eb3b1a · outbound

This paper cites Batch Multivalid Conformal Prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Batch Multivalid Conformal Prediction

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 73382903-1b10-4f12-9161-6c20ca5d640f · outbound

This paper cites Equivariance with learned canonicalization functions.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Equivariance with learned canonicalization functions

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-06T23:48:33.186848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a73d6d84-9d4f-4e8b-9347-7e44269f6c66 · outbound

This paper cites idecode: In-distribution equivariance for conformal out-of-distribution detection.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization idecode: In-distribution equivariance for conformal out-of-distribution detection

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:33.053700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation cc793487-877b-436b-afac-f9fefc32eb56 · outbound

This paper cites Comprehensive review of neural network-based prediction intervals and new advances.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Comprehensive review of neural network-based prediction intervals and new advances

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:32.933192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8310a8e0-eb4c-4314-9aed-6bc4c1df86a3 · outbound

This paper cites Learning probabilistic symmetrization for architecture agnostic equivariance.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Learning probabilistic symmetrization for architecture agnostic equivariance

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-06T23:48:32.821725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.124038Z digest=sha256:e93a895b8ada5817079c74f0d8c8f1e1dc74fa6bd49f16e4396416d89723e776

Observation fdc0d41f-bbdc-405d-9529-b77ce2394c91 · outbound

This paper cites Wilds: A benchmark of in-the-wild distribution shifts.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Wilds: A benchmark of in-the-wild distribution shifts

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:32.717077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.210921Z digest=sha256:9865dd68abdae6cc9035a36706410875ce0b24f20e4f1553001cda9c084bdefe

Observation 3e98072e-45b0-4d54-8ab0-78e971d16e92 · outbound

This paper cites Empirical frequentist coverage of deep learning uncertainty quantification procedures.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Empirical frequentist coverage of deep learning uncertainty quantification procedures

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:32.609656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.257520Z digest=sha256:de2ae3dcebe8b6c19ff77b0d13179c9b1ea2aec483eee62f37dcf54ab9851a5f

Observation 3fc4ca45-6b99-41e7-85ac-d78bf6c30343 · outbound

This paper cites Forecasting and uncertainty: A survey.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Forecasting and uncertainty: A survey

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:32.508112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.335453Z digest=sha256:d14a5c142df0dd575dd1d61bb74814fb526eff86e7892cd941333a1536daafe6

Observation d42b1c8b-4967-4461-a64e-20a596798071 · outbound

This paper cites Equivariant adaptation of large pretrained models.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Equivariant adaptation of large pretrained models

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:32.296727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.430252Z digest=sha256:301bfd6af41d180faa671dfde4a8662541aa0e5a0ddcba2787c4f63330bf8eb5

Observation d8e5daa2-a351-442d-b4b5-4c245c7ef974 · outbound

This paper cites Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:32.021027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.500750Z digest=sha256:89352045c34edcdfc545747f6692db4ab45c230752737a6862c365dc6d0aee03

Observation 876baef4-0f3d-4695-a5f2-675876067c80 · outbound

This paper cites Uncertain about uncertainty: How qualitative expressions of forecaster confidence impact decision-making with uncertainty visualizations.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Uncertain about uncertainty: How qualitative expressions of forecaster confidence impact decision-making with uncertainty visualizations

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:31.900147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.592137Z digest=sha256:35e0af70e3841374c68489d2854731450ab99f21fd1a026dde4624bb08bd8bcc

Observation 8654e9d6-2a86-4623-bb53-77b33c4a935a · outbound

This paper cites Improved canonicalization for model agnostic equivariance.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Improved canonicalization for model agnostic equivariance

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:31.802989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.663969Z digest=sha256:67b872f24f61a40f05e65ccd2d5bd46ce3bdfb8f0f7ef4f5f34e62e6b5fdff78

Observation a19b95d4-2ef7-4668-a799-3da3a8648bb6 · outbound

This paper cites Conformal prediction with Neural Networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction with Neural Networks

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:31.656863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.743486Z digest=sha256:a949451dafe23c438253a5e007229df3b9e3e2656cda3ca783d6a43fa5a5de77

Observation 9ea1bc28-b6f5-4dfd-a7b2-1f821f79c41c · outbound

This paper cites Distribution-free uncertainty quantification for classification under label shift.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Distribution-free uncertainty quantification for classification under label shift

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:31.403884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.828095Z digest=sha256:55abaa74adac440020e081962700105ae86352682882e0dc1ef51afe1f03d1cc

Observation daad0664-4606-4f71-b276-d934ef36a523 · outbound

This paper cites Conformal validity guarantees exist for any data distribution (and how to find them).

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal validity guarantees exist for any data distribution (and how to find them)

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:31.200005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.899728Z digest=sha256:afed11d66608d21312734b06e73c50f69b6f78861a8624252a785487fb8eab18

Observation 8efbf8af-5a79-4b53-8418-91e82d552b3e · outbound

This paper cites Conformal time series decomposition with component-wise exchangeability.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal time series decomposition with component-wise exchangeability

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:30.988421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:25.989450Z digest=sha256:6576aebb3ee2883cfe1997a56f5e5a5d45a003afa989df3eec2c0103ad9a220a

Observation 9fabf6bd-3c1e-4af8-a4de-9476fca7eff1 · outbound

This paper cites Smith, Ishan Misra, Aditya Grover, and Yaron Lipman.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Smith, Ishan Misra, Aditya Grover, and Yaron Lipman

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:30.768724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.067615Z digest=sha256:e2f8752d9d25f12c91babeae0b7746b3b3098756d306b9d2da86cd46b66e12eb

Observation c13ce386-aa68-4d75-a804-e510de30c16f · outbound

This paper cites an unresolved cited work.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:48:30.645266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.087529Z digest=sha256:d65cc1db1b285fe55577f22aa2ae7f5230238b5fe68343c59c97088708f8dbfe

Observation 810079fc-9553-4cab-a6ef-21ba5a712a10 · outbound

This paper cites Dataset shift in machine learning.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Dataset shift in machine learning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:30.524476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.182218Z digest=sha256:4fff6a3ff01cec4dcb3b6af41dba7769cdc79ec37388e9318462fd21da8ae4f7

Observation b781d472-dc7d-4838-b191-e81c9848adfb · outbound

This paper cites With Malice Towards None : Assessing Uncertainty via Equalized Coverage.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization With Malice Towards None : Assessing Uncertainty via Equalized Coverage

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:30.405277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.298520Z digest=sha256:6f81d8f124ba29142ce62abe31573feddbeb24e0bd90326e1894f535486085dd

Observation 7b881fa1-3d19-46ce-b9ec-ff804cce5978 · outbound

This paper cites an unresolved cited work.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:48:30.281795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.375043Z digest=sha256:a0899c995540e2dae19baa11afb2dd81bdd376aacbf860ce2afa9ad3e80f61bc

Observation a8348428-7e4f-44df-a38d-0982c4a3c711 · outbound

This paper cites Romero and Suhas Lohit.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Romero and Suhas Lohit

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:30.133775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.447684Z digest=sha256:577dc72aae2fe85421e96ed7ff02d3f6d1e1cb013c59ce011745624836581199

Observation 5c83bdae-08ed-4e3f-9271-ed14fb157f62 · outbound

This paper cites Clifford group equivariant neural networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Clifford group equivariant neural networks

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:30.021713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.545320Z digest=sha256:0e15002585c49d59de4011d207e8c9fe8d7fc580b101c2aedac92ada50c753b2

Observation dd3ec5b6-4587-4c27-a27b-2b3bc4b94b65 · outbound

This paper cites Least ambiguous set-valued classifiers with bounded error levels.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Least ambiguous set-valued classifiers with bounded error levels

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:29.885740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.670079Z digest=sha256:f5b65d8bca9f809bd2d3647e42ecd5d183fa5cc7344f02509c25dd61c32ee49c

Observation c54a16ee-4244-4868-9576-47d51553c79b · outbound

This paper cites Conformal Prediction using Conditional Histograms.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal Prediction using Conditional Histograms

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:29.781465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.725808Z digest=sha256:3c496b2504fd5c2c721df235b20763b653bafc8742fa5a78c3bf54e68eabb928

Observation 6cad7883-e453-4283-b404-5491392a7915 · outbound

This paper cites Conformal prediction using conditional histograms.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction using conditional histograms

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:29.660769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.797521Z digest=sha256:f43e60ad1ba83637de4aad3fa0912519a3d471ad26e8f2284be004c46d007309

Observation 406bfd9e-a68f-481b-a7d8-40eee16e1cb4 · outbound

This paper cites A tutorial on conformal prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization A tutorial on conformal prediction

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:29.530173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.910483Z digest=sha256:3e017ba8685783767d28389223b14dbf891493b35497c3a7aa8af0f028b61b31

Observation 8e7de2a0-2108-4c08-b182-dd4cc47bd545 · outbound

This paper cites Conformal prediction under covariate shift.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction under covariate shift

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:29.332718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:26.972463Z digest=sha256:e0901a4de70393243018bae3279a7f6b85f978bff828dde3c76d6e876f043023

Observation a6761123-dfce-454d-be73-ed7fda880c29 · outbound

This paper cites Adaptive bounding box uncertainties via two-step conformal prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Adaptive bounding box uncertainties via two-step conformal prediction

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:29.170013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.067664Z digest=sha256:6bd2b104f93de4de9bb862c0b202e579abf64438739899072d49d6f0ae393074

Observation 35b229be-a3ad-4479-8b5b-6fb36830d6d6 · outbound

This paper cites Combination of inductive mondrian conformal predictors.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Combination of inductive mondrian conformal predictors

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:29.020644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.128398Z digest=sha256:19cffff64bd412324315a9074b7cbb406220dda995543d3f284cdb9f1f72479d

Observation 960b2b50-8554-4d26-bbd4-f846f28cf477 · outbound

This paper cites an unresolved cited work.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:48:28.866078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.221279Z digest=sha256:eedf67a70a0d418fce4f27d6e3f5cc84073c16763950303f93811bb88f2ab5d9

Observation 1f721928-f412-4ef9-ac94-d3c8a5bd676b · outbound

This paper cites Probing Equivariance and Symmetry Breaking in Convolutional Networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Probing Equivariance and Symmetry Breaking in Convolutional Networks

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T23:48:27.282258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:48:27.282258Z digest=sha256:1cd422b5ea9ecc4a56e4e20b84e6837b7cc978b46e19309ebe19696bc8d1a53e

Observation d4052ab8-6025-4c24-9005-44dba26648d2 · outbound

This paper cites van der Linden, Alejandro García-Castellanos, Sharvaree Vadgama, Thijs P.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization van der Linden, Alejandro García-Castellanos, Sharvaree Vadgama, Thijs P

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:28.676775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.386131Z digest=sha256:1f979b63c2a70a0f9d377a6b725790ef79d338cc1ba64a176d45ead13a897aef

Observation db5ff9aa-b026-49ce-9167-a3b0255f9750 · outbound

This paper cites Algorithmic learning in a random world.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Algorithmic learning in a random world

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T23:48:27.497258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:48:27.497258Z digest=sha256:fbb99181b06dffdb3c0f2e7c3ca8e4b0bf2de7a9c1925922a1c6e167e7af9b43

Observation 8d6c6006-4c3d-4a27-a31c-c5bd6a736cda · outbound

This paper cites Sarma, Michael M.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Sarma, Michael M

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:28.534222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.552480Z digest=sha256:38af339e68fedd8abee4de10b66bb81021a8ed2912cc638e2eb94dd4282fe629

Observation 9bc7b78a-06fc-4887-a6e6-753d37296335 · outbound

This paper cites General e(2)-equivariant steerable cnns.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization General e(2)-equivariant steerable cnns

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:28.355991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.612029Z digest=sha256:eea6cc81f7a77784c902ed7aeb9898986778cae0621a2d513dd6a6249d677811

Observation 4ccf8097-3ba6-4edc-adb4-d01d4ee580ce · outbound

This paper cites Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:28.199199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.681066Z digest=sha256:cc88cbfb91d651f3fd1c253837a9626ef0eea835e4f58322cb1852124a097d75

Observation b3ca30df-92d8-4259-9e89-5a4168cd9b26 · outbound

This paper cites Adaptive conformal predictions for time series.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Adaptive conformal predictions for time series

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:48:28.003561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T23:48:27.817236Z digest=sha256:0b404fe4f53697a18a33eb9197eb291fc28af3018d3b0d57be64aaa547452700

Pith citing papers

No inbound Pith citation observations are available.