Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T12:33:25.445880Z
Paper Citation Record · LEDGER
As of 15 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2412.14142.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T12:33:25.445880Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
62 of 62 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation d492aefd-650a-41af-bf8c-e85403fff99f · outbound
On Calibration in Multi-Distribution Learning On the coherence of expected shortfall, 2002
Reference 1
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Observation 0fe850c4-44f7-4227-9de8-83fa64189567 · outbound
On Calibration in Multi-Distribution Learning Out of distribution generalization in machine learning
Reference 2
Source-reported events for the cited work
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Observation 7fa2aa29-48dc-4a90-ab6f-909ef3f03f55 · outbound
On Calibration in Multi-Distribution Learning Coherent measures of risk
Reference 3
Source-reported events for the cited work
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Observation ff8100bc-cd15-4e80-b85a-bf49b0ef6aa8 · outbound
On Calibration in Multi-Distribution Learning Exploiting task relatedness for multiple task learning
Reference 4
Source-reported events for the cited work
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Reference 5
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On Calibration in Multi-Distribution Learning Robust solutions of optimization problems affected by uncertain probabilities
Reference 6
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On Calibration in Multi-Distribution Learning Generalizing from several related classification tasks to a new unlabeled sample
Reference 7
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Observation 536e6f23-0cb5-42ee-a848-0a8f90178ae6 · outbound
On Calibration in Multi-Distribution Learning Domain generalization by marginal transfer learning
Reference 8
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Observation 0e9bb1c1-028b-4bc2-972f-df03526fee95 · outbound
On Calibration in Multi-Distribution Learning Collaborative pac learning
Reference 9
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Observation 97eff568-8dc0-489a-a61c-e36c4a8edf7a · outbound
On Calibration in Multi-Distribution Learning Communication-aware collaborative learning
Reference 10
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Observation be40522d-87ca-4b5d-a2d0-05024431480e · outbound
On Calibration in Multi-Distribution Learning The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
Reference 11
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Observation b0a5674f-b426-4ba5-a3b4-0774d91c53b2 · outbound
On Calibration in Multi-Distribution Learning Reliability, sufficiency, and the decomposition of proper scores
Reference 12
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Observation 4f6760e8-3aaa-4103-94f2-7150a09f13e3 · outbound
On Calibration in Multi-Distribution Learning Gender shades: Intersectional accuracy disparities in commercial gender classification
Reference 13
Source-reported events for the cited work
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Observation 2bf4dac3-eb3e-454f-8547-0c8a11d74372 · outbound
On Calibration in Multi-Distribution Learning Philip Dawid
Reference 14
Source-reported events for the cited work
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Observation d990c186-ac5f-4ace-8350-8b82c56f3948 · outbound
On Calibration in Multi-Distribution Learning Degroot and Stephen E
Reference 15
Source-reported events for the cited work
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Observation 136028b9-9a34-4f3f-98d6-5041ff77047b · outbound
On Calibration in Multi-Distribution Learning Evaluation Metrics as Averaged Outcomes of Fair Gambles
Reference 16
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Observation dcac3555-2318-4392-90cf-3191f3d45af0 · outbound
On Calibration in Multi-Distribution Learning Statistics of robust optimization: A generalized empirical likelihood approach
Reference 17
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Observation 5798ec2d-aa90-453a-8531-0eb8feca2cc8 · outbound
On Calibration in Multi-Distribution Learning Outcome indistinguishability
Reference 18
Source-reported events for the cited work
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Observation 80ac8e52-a568-4c2d-904b-5676c048799a · outbound
On Calibration in Multi-Distribution Learning u gelgen, Hamed Hassani, George J Pappas, and Bernhard Sch \
Reference 19
Source-reported events for the cited work
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Observation 65c26b58-60e9-4668-a569-346a1be6fde0 · outbound
On Calibration in Multi-Distribution Learning The foundations of cost-sensitive learning
Reference 20
Source-reported events for the cited work
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Observation 88a55d93-5913-4b03-a9bc-5e4c903f4980 · outbound
On Calibration in Multi-Distribution Learning Data Models With Two Manifestations of Imprecision
Reference 21
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Observation abba659b-6951-4f30-b791-d0a6c1f2dc9a · outbound
On Calibration in Multi-Distribution Learning Risk measures and upper probabilities: Coherence and stratification
Reference 22
Source-reported events for the cited work
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Observation b2fe8375-5eda-4e89-89de-eb3205500e05 · outbound
On Calibration in Multi-Distribution Learning Scoring Rules and Calibration for Imprecise Probabilities
Reference 23
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Reference 24
Source-reported events for the cited work
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Observation f9aa68c1-1e2c-49a2-be53-b41904450258 · outbound
On Calibration in Multi-Distribution Learning Strictly proper scoring rules, prediction, and estimation
Reference 25
Source-reported events for the cited work
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Observation 258ce20c-b7b8-4600-9c7e-2cca132c8c1f · outbound
On Calibration in Multi-Distribution Learning Omnipredictors
Reference 26
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Observation d1f4b043-7993-49ed-9372-a6fd2f590bb3 · outbound
On Calibration in Multi-Distribution Learning Unresolved cited work
Reference 27
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Observation 984273d7-32b6-4dee-9d9b-336106c3030d · outbound
On Calibration in Multi-Distribution Learning Safe probability
Reference 28
Source-reported events for the cited work
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Observation 7dfa0bae-bf95-4848-8efc-4a8df8b40f66 · outbound
On Calibration in Multi-Distribution Learning The minimum description length principle
Reference 29
Source-reported events for the cited work
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Observation d53c4cde-1b51-4681-b9e4-b71d6697c0f2 · outbound
On Calibration in Multi-Distribution Learning Game theory, maximum entropy, minimum discrepancy and robust bayesian decision theory
Reference 30
Source-reported events for the cited work
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Observation 43bb09fd-8709-4613-b01f-44da8cbfa511 · outbound
On Calibration in Multi-Distribution Learning On calibration of modern neural networks
Reference 31
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Observation 0e1aa700-3289-44c2-b76d-b153c08c2d96 · outbound
On Calibration in Multi-Distribution Learning On-demand sampling: Learning optimally from multiple distributions
Reference 32
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Observation 87045bd5-3d94-49bd-9348-1066cb5b549f · outbound
On Calibration in Multi-Distribution Learning The reference class problem is your problem too
Reference 33
Source-reported events for the cited work
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Observation 3d9ff8a7-689a-4a92-829e-8a80996f3e08 · outbound
On Calibration in Multi-Distribution Learning Fairness without demographics in repeated loss minimization
Reference 34
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On Calibration in Multi-Distribution Learning Multicalibration: Calibration for the ( C omputationally-identifiable) masses
Reference 35
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Observation d7d893ad-a2f3-4468-9c7e-f81048598d31 · outbound
On Calibration in Multi-Distribution Learning On the richness of calibration
Reference 36
Source-reported events for the cited work
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Observation 664be81b-df8e-4108-bd4c-896358eba859 · outbound
On Calibration in Multi-Distribution Learning Toward efficient agnostic learning
Reference 37
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Observation dd09def1-2d6e-4c4d-9d9b-36b45e7e7618 · outbound
On Calibration in Multi-Distribution Learning U-calibration: Forecasting for an unknown agent
Reference 38
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Observation 88510444-78b3-4c9d-852c-093b8e0cc292 · outbound
On Calibration in Multi-Distribution Learning Novel decompositions of proper scoring rules for classification: score adjustment as precursor to calibration
Reference 39
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Observation d7f1942d-a2d9-49b0-a269-40b3e9d4a43b · outbound
On Calibration in Multi-Distribution Learning On law invariant coherent risk measures
Reference 40
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On Calibration in Multi-Distribution Learning Domain adaptation with multiple sources
Reference 41
Source-reported events for the cited work
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Observation 9b4751a6-385e-4c91-9493-9f2259c939fe · outbound
On Calibration in Multi-Distribution Learning Minimax pareto fairness: A multi objective perspective
Reference 42
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Observation 44adbb8c-fa0d-4467-94db-81786e0cdc07 · outbound
On Calibration in Multi-Distribution Learning Stochastic optimization for spectral risk measures
Reference 43
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On Calibration in Multi-Distribution Learning Unresolved cited work
Reference 44
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Observation 78c5f336-c2f9-4dbc-904f-da4813dc4016 · outbound
On Calibration in Multi-Distribution Learning Agnostic federated learning
Reference 45
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Observation 5ac23588-2b6e-4c23-8200-80d8aa84cd4a · outbound
On Calibration in Multi-Distribution Learning Improved algorithms for collaborative pac learning
Reference 46
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Observation dfaae85a-debe-4827-885f-b0dd5901bc5b · outbound
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Reference 47
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Reference 48
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On Calibration in Multi-Distribution Learning Proper scoring rules and bregman divergence
Reference 49
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On Calibration in Multi-Distribution Learning Frameworks and results in distributionally robust optimization
Reference 50
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Observation fc2ee520-3990-4563-81f4-60b947047347 · outbound
On Calibration in Multi-Distribution Learning On measures of entropy and information
Reference 51
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On Calibration in Multi-Distribution Learning Convex analysis
Reference 52
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Observation b5c7e242-9a84-4dd5-825e-cec0e386c671 · outbound
On Calibration in Multi-Distribution Learning Coherent approaches to risk in optimization under uncertainty
Reference 53
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On Calibration in Multi-Distribution Learning Multi-group agnostic pac learnability
Reference 54
Source-reported events for the cited work
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On Calibration in Multi-Distribution Learning Hashimoto, and Percy Liang
Reference 55
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Observation b8d7fc61-8187-4ab0-a027-2bf5d0752ce4 · outbound
On Calibration in Multi-Distribution Learning Conditional Value-at-Risk (CVaR)
Reference 56
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Observation 806ca5c6-dab4-4474-b63f-a3a9f29ea7dd · outbound
On Calibration in Multi-Distribution Learning Evaluating model calibration in classification
Reference 57
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Observation 7a209a14-9715-4af5-9e3d-23dc941b5f0c · outbound
On Calibration in Multi-Distribution Learning A theory of the learnable
Reference 58
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On Calibration in Multi-Distribution Learning The Wasserstein distances
Reference 59
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On Calibration in Multi-Distribution Learning Optimal multi-distribution learning
Reference 60
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On Calibration in Multi-Distribution Learning Calibrating predictions to decisions: A novel approach to multi-class calibration
Reference 61
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Reference 62
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.