Paper Citation Record · LEDGER

Multiply Robust Conformal Risk Control with Coarsened Data

As of 19 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2508.15489.

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

pith.paper-citation-record.v1
2508.15489 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:55:28.419287Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T18:44:00.812851Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:37:26.378078Z

Reference resolution

50 of 50 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2442e3cd-5712-4aab-a0fc-cdbdb16796ff · outbound

This paper cites Conformal Risk Control.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal Risk Control

Reference 1

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Source-reported events for the cited work

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Observation 03bde6fe-d359-414e-b7fa-13aceca3fed7 · outbound

This paper cites Near-optimal rate of consistency for linear models with missing values.

Multiply Robust Conformal Risk Control with Coarsened Data Near-optimal rate of consistency for linear models with missing values

Reference 2

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Source-reported events for the cited work

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Observation 1ba624c5-37c3-41ff-ad2e-334654ef8bc7 · outbound

This paper cites Predictive inference with the jackknife+.

Multiply Robust Conformal Risk Control with Coarsened Data Predictive inference with the jackknife+

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:34.639655Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 03ee71f9-eec2-41d9-9abe-92c988495330 · outbound

This paper cites Conformal prediction beyond exchangeability.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal prediction beyond exchangeability

Reference 4

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Source-reported events for the cited work

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Observation 699cc15e-6fa8-44fe-a823-0f99b4632018 · outbound

This paper cites Predictive inference with weak supervision.

Multiply Robust Conformal Risk Control with Coarsened Data Predictive inference with weak supervision

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:34.456617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 29a60c44-07c0-49f6-822b-64d04b07f1db · outbound

This paper cites Robust validation: Confident predictions even when distributions shift.

Multiply Robust Conformal Risk Control with Coarsened Data Robust validation: Confident predictions even when distributions shift

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:34.281982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ebf79f39-f5cf-4f4c-bc1a-27b0fa6f6d2d · outbound

This paper cites Distributional conformal prediction.

Multiply Robust Conformal Risk Control with Coarsened Data Distributional conformal prediction

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:34.049585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6ca6928a-282f-444d-ba0b-a7c2f2284d35 · outbound

This paper cites Methotrexate and mortality in patients with rheumatoid arthritis: a prospective study.

Multiply Robust Conformal Risk Control with Coarsened Data Methotrexate and mortality in patients with rheumatoid arthritis: a prospective study

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:33.865542Z

Source-reported events for the cited work

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Observation 698a0876-be62-441f-93f0-b02b27dba9ae · outbound

This paper cites Relative expected instantaneous loss bounds.

Multiply Robust Conformal Risk Control with Coarsened Data Relative expected instantaneous loss bounds

Reference 9

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Source-reported events for the cited work

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Observation 4a11be22-ed08-472c-9f13-ecc5464269ef · outbound

This paper cites The limits of distribution-free conditional predictive inference.

Multiply Robust Conformal Risk Control with Coarsened Data The limits of distribution-free conditional predictive inference

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:33.716816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa8fde9c-2354-455d-983e-ab8bf64e8f8c · outbound

This paper cites Conformal Prediction With Conditional Guarantees.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal Prediction With Conditional Guarantees

Reference 11

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Source-reported events for the cited work

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Observation 68329b20-54a4-4fff-b814-d5f41a1c4956 · outbound

This paper cites Nearest neighbor based conformal prediction.

Multiply Robust Conformal Risk Control with Coarsened Data Nearest neighbor based conformal prediction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:33.501429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 577c8d89-6985-46cc-ba83-60da97db7ce3 · outbound

This paper cites Introduction to the special section on missing data.

Multiply Robust Conformal Risk Control with Coarsened Data Introduction to the special section on missing data

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:33.296674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dc597395-8098-46f6-83c3-3d7ab82bfe41 · outbound

This paper cites On the consistency of supervised learning with missing values.

Multiply Robust Conformal Risk Control with Coarsened Data On the consistency of supervised learning with missing values

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:33.114190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aa363db5-4329-4ea3-a67c-0b79e4daaa02 · outbound

This paper cites Batch Multivalid Conformal Prediction.

Multiply Robust Conformal Risk Control with Coarsened Data Batch Multivalid Conformal Prediction

Reference 15

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Source-reported events for the cited work

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Observation 07dc14b6-3e8c-42c3-8a30-88bf35577cc2 · outbound

This paper cites Predictive inference is free with the jackknife+-after-bootstrap.

Multiply Robust Conformal Risk Control with Coarsened Data Predictive inference is free with the jackknife+-after-bootstrap

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f87a2f9-0b00-40d9-a078-3479dfd4ce63 · outbound

This paper cites Exchangeability, Conformal Prediction, and Rank Tests.

Multiply Robust Conformal Risk Control with Coarsened Data Exchangeability, Conformal Prediction, and Rank Tests

Reference 17

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Source-reported events for the cited work

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Observation b46431af-1ebf-4762-9ddb-a0ebbd7fddd0 · outbound

This paper cites Unified methods for censored longitudinal data and causality.

Multiply Robust Conformal Risk Control with Coarsened Data Unified methods for censored longitudinal data and causality

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:32.703953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 41399f77-8764-4d37-ad12-9ab0a6d9694e · outbound

This paper cites Neumiss networks: differentiable programming for supervised learning with missing values.

Multiply Robust Conformal Risk Control with Coarsened Data Neumiss networks: differentiable programming for supervised learning with missing values

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3f699ca4-4ed8-41af-af75-59f8080ddfc8 · outbound

This paper cites Linear predictor on linearly-generated data with missing values: non consistency and solutions.

Multiply Robust Conformal Risk Control with Coarsened Data Linear predictor on linearly-generated data with missing values: non consistency and solutions

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:32.308869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7ed6ef9c-5f0f-416e-ac9f-2b6f576e5013 · outbound

This paper cites What’sa good imputation to predict with missing values? Advances in Neural Information Processing Systems, 34: 0 11530--11540, 2021.

Multiply Robust Conformal Risk Control with Coarsened Data What’sa good imputation to predict with missing values? Advances in Neural Information Processing Systems, 34: 0 11530--11540, 2021

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:32.099920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4fa1fedd-1916-42c4-9cf5-c3b5037bf4d9 · outbound

This paper cites Distribution-free prediction bands for non-parametric regression.

Multiply Robust Conformal Risk Control with Coarsened Data Distribution-free prediction bands for non-parametric regression

Reference 22

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Source-reported events for the cited work

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Observation ecbdc0df-7c97-4b55-ba31-ab9ae9620d7c · outbound

This paper cites Distribution-free prediction sets.

Multiply Robust Conformal Risk Control with Coarsened Data Distribution-free prediction sets

Reference 23

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Source-reported events for the cited work

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Observation 6bf7926a-58ce-4a25-a378-1a54d2762c59 · outbound

This paper cites Distribution-free predictive inference for regression.

Multiply Robust Conformal Risk Control with Coarsened Data Distribution-free predictive inference for regression

Reference 24

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Observation 6d4e00ec-f105-4eac-821b-a721167e3626 · outbound

This paper cites Conformal inference of counterfactuals and individual treatment effects.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal inference of counterfactuals and individual treatment effects

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:31.884606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 243701ef-24b6-47ba-9544-fd3cbc35564d · outbound

This paper cites Statistical analysis with missing data.

Multiply Robust Conformal Risk Control with Coarsened Data Statistical analysis with missing data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:31.696136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 372bad17-19d3-4e73-a745-5ad56d80f78a · outbound

This paper cites Inductive confidence machines for regression.

Multiply Robust Conformal Risk Control with Coarsened Data Inductive confidence machines for regression

Reference 27

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Observation 4e6a26a3-1e90-4ab3-b5d2-65a6eed2d012 · outbound

This paper cites Super learner in prediction.

Multiply Robust Conformal Risk Control with Coarsened Data Super learner in prediction

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57add95d-9472-479f-855b-ed4c85f6138a · outbound

This paper cites Prediction sets adaptive to unknown covariate shift.

Multiply Robust Conformal Risk Control with Coarsened Data Prediction sets adaptive to unknown covariate shift

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:31.311643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c12a4e33-67cb-46f3-81ed-a0a4efd9790b · outbound

This paper cites Non-response models for the analysis of non-monotone ignorable missing data.

Multiply Robust Conformal Risk Control with Coarsened Data Non-response models for the analysis of non-monotone ignorable missing data

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:31.076824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b52a62e-2d58-4d6a-b2bc-003c985183a7 · outbound

This paper cites Estimation of regression coefficients when some regressors are not always observed.

Multiply Robust Conformal Risk Control with Coarsened Data Estimation of regression coefficients when some regressors are not always observed

Reference 31

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Source-reported events for the cited work

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Observation bf59f8b5-52ba-4b83-9ebb-bae55cf4f435 · outbound

This paper cites Conformalized quantile regression.

Multiply Robust Conformal Risk Control with Coarsened Data Conformalized quantile regression

Reference 32

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Source-reported events for the cited work

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Observation 7f323edf-3c24-4d71-8d2e-e818e1cc484d · outbound

This paper cites Classification with valid and adaptive coverage.

Multiply Robust Conformal Risk Control with Coarsened Data Classification with valid and adaptive coverage

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:30.892129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2208127f-7720-4faf-934d-9d6459cc4fcb · outbound

This paper cites Characterization of parameters with a mixed bias property.

Multiply Robust Conformal Risk Control with Coarsened Data Characterization of parameters with a mixed bias property

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:30.746042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8a7bd707-56bc-464a-9a83-75f1e2b03403 · outbound

This paper cites Conformal prediction using conditional histograms.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal prediction using conditional histograms

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:30.558434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9754bc79-19e9-43f9-8c92-2cc6706a67d9 · outbound

This paper cites Conformal time-series forecasting.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal time-series forecasting

Reference 36

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Observation bb3190a1-2031-48c2-9006-b074f0c696d5 · outbound

This paper cites On inverse probability weighting for nonmonotone missing at random data.

Multiply Robust Conformal Risk Control with Coarsened Data On inverse probability weighting for nonmonotone missing at random data

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:30.384010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 899c7ad6-0bc6-406a-beae-b17509a9e234 · outbound

This paper cites Inverse-probability-weighted estimation for monotone and nonmonotone missing data.

Multiply Robust Conformal Risk Control with Coarsened Data Inverse-probability-weighted estimation for monotone and nonmonotone missing data

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:30.176690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 958fb0cc-819f-4c01-9421-42ca5e9c48a0 · outbound

This paper cites Statistical methods for robust inference in causal and missing data models.

Multiply Robust Conformal Risk Control with Coarsened Data Statistical methods for robust inference in causal and missing data models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:29.973708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d64ed154-3938-415a-b906-397fecc74276 · outbound

This paper cites Conformal prediction under covariate shift.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal prediction under covariate shift

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:29.796808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 991c20ac-ee76-4d07-905e-3bf108824428 · outbound

This paper cites Semiparametric theory and missing data, volume 4.

Multiply Robust Conformal Risk Control with Coarsened Data Semiparametric theory and missing data, volume 4

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:29.646225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0d2da155-5e33-492c-8705-2ed3103f459d · outbound

This paper cites The missing indicator method: From low to high dimensions.

Multiply Robust Conformal Risk Control with Coarsened Data The missing indicator method: From low to high dimensions

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:29.403626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 663d64ec-1129-49ea-8e51-e29067f941a3 · outbound

This paper cites Conditional validity of inductive conformal predictors.

Multiply Robust Conformal Risk Control with Coarsened Data Conditional validity of inductive conformal predictors

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:29.228846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b2a52913-bf79-496a-bc69-04e0bef1e833 · outbound

This paper cites Mondrian confidence machine.

Multiply Robust Conformal Risk Control with Coarsened Data Mondrian confidence machine

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:29.060969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 453123d6-e314-4bea-b899-655a5e1ad47a · outbound

This paper cites Algorithmic learning in a random world, volume 29.

Multiply Robust Conformal Risk Control with Coarsened Data Algorithmic learning in a random world, volume 29

Reference 45

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40f47165-04fe-4dba-83e8-0c6afe49bcfb · outbound

This paper cites Selection and Aggregation of Conformal Prediction Sets.

Multiply Robust Conformal Risk Control with Coarsened Data Selection and Aggregation of Conformal Prediction Sets

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T17:55:28.069509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64869cdd-e018-4059-927b-985a5e8c0610 · outbound

This paper cites Forster-Warmuth Counterfactual Regression: A Unified Learning Approach.

Multiply Robust Conformal Risk Control with Coarsened Data Forster-Warmuth Counterfactual Regression: A Unified Learning Approach

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T17:55:28.176227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3a4a727-53e8-4b70-a7aa-49a4fda14f08 · outbound

This paper cites Doubly robust calibration of prediction sets under covariate shift.

Multiply Robust Conformal Risk Control with Coarsened Data Doubly robust calibration of prediction sets under covariate shift

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:28.906852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36fcb36f-412e-4377-8dd0-65bfe5e83b02 · outbound

This paper cites Conformal prediction with missing values.

Multiply Robust Conformal Risk Control with Coarsened Data Conformal prediction with missing values

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T17:55:28.789562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 428a55ec-83cd-4fbd-a935-5e6efaf359bb · outbound

This paper cites Predictive Uncertainty Quantification with Missing Covariates.

Multiply Robust Conformal Risk Control with Coarsened Data Predictive Uncertainty Quantification with Missing Covariates

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T17:55:28.419287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation a5d537b1-6b2b-4884-a8f6-1ceda37db258 · inbound

A Joint Finite-Sample Certificate for Adaptive Selective Conformal Risk Control cites this paper.

A Joint Finite-Sample Certificate for Adaptive Selective Conformal Risk Control Multiply Robust Conformal Risk Control with Coarsened Data

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:37:26.379980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.