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Paper Citation Record · LEDGER

On Calibration in Multi-Distribution Learning

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.

pith.paper-citation-record.v1
2412.14142 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:33:25.445880Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

62 of 62 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d492aefd-650a-41af-bf8c-e85403fff99f · outbound

This paper cites On the coherence of expected shortfall, 2002.

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

This paper cites Out of distribution generalization in machine learning.

On Calibration in Multi-Distribution Learning Out of distribution generalization in machine learning

Reference 2

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Observation 7fa2aa29-48dc-4a90-ab6f-909ef3f03f55 · outbound

This paper cites Coherent measures of risk.

On Calibration in Multi-Distribution Learning Coherent measures of risk

Reference 3

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Observation ff8100bc-cd15-4e80-b85a-bf49b0ef6aa8 · outbound

This paper cites Exploiting task relatedness for multiple task learning.

On Calibration in Multi-Distribution Learning Exploiting task relatedness for multiple task learning

Reference 4

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Observation 876ce6d0-fcf9-4e6d-898d-d6c382543ab9 · outbound

This paper cites Ben-Tal, L.

On Calibration in Multi-Distribution Learning Ben-Tal, L

Reference 5

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Observation 0779eac5-7079-4558-8136-1ca469e623c1 · outbound

This paper cites Robust solutions of optimization problems affected by uncertain probabilities.

On Calibration in Multi-Distribution Learning Robust solutions of optimization problems affected by uncertain probabilities

Reference 6

Resolution
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Observation 14d78ce1-9a2b-4dd8-bb67-de45bb9dad67 · outbound

This paper cites Generalizing from several related classification tasks to a new unlabeled sample.

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

This paper cites Domain generalization by marginal transfer learning.

On Calibration in Multi-Distribution Learning Domain generalization by marginal transfer learning

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 0e9bb1c1-028b-4bc2-972f-df03526fee95 · outbound

This paper cites Collaborative pac learning.

On Calibration in Multi-Distribution Learning Collaborative pac learning

Reference 9

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Observation 97eff568-8dc0-489a-a61c-e36c4a8edf7a · outbound

This paper cites Communication-aware collaborative learning.

On Calibration in Multi-Distribution Learning Communication-aware collaborative learning

Reference 10

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This paper cites The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming.

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

Resolution
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This paper cites Reliability, sufficiency, and the decomposition of proper scores.

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

This paper cites Gender shades: Intersectional accuracy disparities in commercial gender classification.

On Calibration in Multi-Distribution Learning Gender shades: Intersectional accuracy disparities in commercial gender classification

Reference 13

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This paper cites Philip Dawid.

On Calibration in Multi-Distribution Learning Philip Dawid

Reference 14

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This paper cites Degroot and Stephen E.

On Calibration in Multi-Distribution Learning Degroot and Stephen E

Reference 15

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Observation 136028b9-9a34-4f3f-98d6-5041ff77047b · outbound

This paper cites Evaluation Metrics as Averaged Outcomes of Fair Gambles.

On Calibration in Multi-Distribution Learning Evaluation Metrics as Averaged Outcomes of Fair Gambles

Reference 16

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This paper cites Statistics of robust optimization: A generalized empirical likelihood approach.

On Calibration in Multi-Distribution Learning Statistics of robust optimization: A generalized empirical likelihood approach

Reference 17

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This paper cites Outcome indistinguishability.

On Calibration in Multi-Distribution Learning Outcome indistinguishability

Reference 18

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This paper cites u gelgen, Hamed Hassani, George J Pappas, and Bernhard Sch \.

On Calibration in Multi-Distribution Learning u gelgen, Hamed Hassani, George J Pappas, and Bernhard Sch \

Reference 19

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On Calibration in Multi-Distribution Learning The foundations of cost-sensitive learning

Reference 20

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Observation 88a55d93-5913-4b03-a9bc-5e4c903f4980 · outbound

This paper cites Data Models With Two Manifestations of Imprecision.

On Calibration in Multi-Distribution Learning Data Models With Two Manifestations of Imprecision

Reference 21

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This paper cites Risk measures and upper probabilities: Coherence and stratification.

On Calibration in Multi-Distribution Learning Risk measures and upper probabilities: Coherence and stratification

Reference 22

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On Calibration in Multi-Distribution Learning Scoring Rules and Calibration for Imprecise Probabilities

Reference 23

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On Calibration in Multi-Distribution Learning Williamson

Reference 24

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On Calibration in Multi-Distribution Learning Strictly proper scoring rules, prediction, and estimation

Reference 25

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Observation 258ce20c-b7b8-4600-9c7e-2cca132c8c1f · outbound

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On Calibration in Multi-Distribution Learning Omnipredictors

Reference 26

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On Calibration in Multi-Distribution Learning Unresolved cited work

Reference 27

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On Calibration in Multi-Distribution Learning Safe probability

Reference 28

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On Calibration in Multi-Distribution Learning The minimum description length principle

Reference 29

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On Calibration in Multi-Distribution Learning Game theory, maximum entropy, minimum discrepancy and robust bayesian decision theory

Reference 30

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On Calibration in Multi-Distribution Learning On calibration of modern neural networks

Reference 31

Resolution
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Observation 0e1aa700-3289-44c2-b76d-b153c08c2d96 · outbound

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On Calibration in Multi-Distribution Learning On-demand sampling: Learning optimally from multiple distributions

Reference 32

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On Calibration in Multi-Distribution Learning The reference class problem is your problem too

Reference 33

Resolution
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Observation 3d9ff8a7-689a-4a92-829e-8a80996f3e08 · outbound

This paper cites Fairness without demographics in repeated loss minimization.

On Calibration in Multi-Distribution Learning Fairness without demographics in repeated loss minimization

Reference 34

Resolution
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This paper cites Multicalibration: Calibration for the ( C omputationally-identifiable) masses.

On Calibration in Multi-Distribution Learning Multicalibration: Calibration for the ( C omputationally-identifiable) masses

Reference 35

Resolution
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Source-reported events for the cited work

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This paper cites On the richness of calibration.

On Calibration in Multi-Distribution Learning On the richness of calibration

Reference 36

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Source-reported events for the cited work

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Observation 664be81b-df8e-4108-bd4c-896358eba859 · outbound

This paper cites Toward efficient agnostic learning.

On Calibration in Multi-Distribution Learning Toward efficient agnostic learning

Reference 37

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.293600Z digest=sha256:51516e3fd0caf691cc1a66ae703118ce62985432ab0f5a2eb469022981ebd78e

Observation dd09def1-2d6e-4c4d-9d9b-36b45e7e7618 · outbound

This paper cites U-calibration: Forecasting for an unknown agent.

On Calibration in Multi-Distribution Learning U-calibration: Forecasting for an unknown agent

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:26.088041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.300221Z digest=sha256:99be7d53ad9413167e5c9ab0d1b5791bed0446aa097a89b68232e18afa4f0265

Observation 88510444-78b3-4c9d-852c-093b8e0cc292 · outbound

This paper cites Novel decompositions of proper scoring rules for classification: score adjustment as precursor to calibration.

On Calibration in Multi-Distribution Learning Novel decompositions of proper scoring rules for classification: score adjustment as precursor to calibration

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:26.064382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.305687Z digest=sha256:ca309742ceef81bff6f4363a2f92d889fd9fa526c8c666e84da75d532fde526f

Observation d7f1942d-a2d9-49b0-a269-40b3e9d4a43b · outbound

This paper cites On law invariant coherent risk measures.

On Calibration in Multi-Distribution Learning On law invariant coherent risk measures

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:26.040692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.311099Z digest=sha256:eee8463b8092930fcad81423a9a532d3b04e70d4e3aa8c1ee3bb7fef092eec6c

Observation 5283a304-9f58-48af-9cb7-6abaefa4f133 · outbound

This paper cites Domain adaptation with multiple sources.

On Calibration in Multi-Distribution Learning Domain adaptation with multiple sources

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:26.014572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.316796Z digest=sha256:0c6c7f7a79603d08bd8dc089459a92f1ed467c53742f662c8cb494b0f0d2cd87

Observation 9b4751a6-385e-4c91-9493-9f2259c939fe · outbound

This paper cites Minimax pareto fairness: A multi objective perspective.

On Calibration in Multi-Distribution Learning Minimax pareto fairness: A multi objective perspective

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.987404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.322242Z digest=sha256:af7e471aa2ca2dce3bd700b5f07660d3f62d9b80c57219b48b4939830d073542

Observation 44adbb8c-fa0d-4467-94db-81786e0cdc07 · outbound

This paper cites Stochastic optimization for spectral risk measures.

On Calibration in Multi-Distribution Learning Stochastic optimization for spectral risk measures

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.962469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.328134Z digest=sha256:c1e4b07165257f2e500758696687914cc2e05c4c5ac5326ab128399a07a5bc91

Observation 453538cc-441f-4dd8-883f-41877eb242c1 · outbound

This paper cites an unresolved cited work.

On Calibration in Multi-Distribution Learning Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:33:25.942330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.334024Z digest=sha256:f423cd8b7a15b3eadb23ebdd72c2a091f786b9e40478ba041ea6b272779899b2

Observation 78c5f336-c2f9-4dbc-904f-da4813dc4016 · outbound

This paper cites Agnostic federated learning.

On Calibration in Multi-Distribution Learning Agnostic federated learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.925200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.340834Z digest=sha256:dbcd6c6223ca877ae6aab1d24769547bd9a0b6902d3fc101f42f930712534fb4

Observation 5ac23588-2b6e-4c23-8200-80d8aa84cd4a · outbound

This paper cites Improved algorithms for collaborative pac learning.

On Calibration in Multi-Distribution Learning Improved algorithms for collaborative pac learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.908134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.346863Z digest=sha256:a89db2742492accfedfaf0d6ee82d231dbf29ff7ab6f6b7a2c347f12b3ee75a5

Observation dfaae85a-debe-4827-885f-b0dd5901bc5b · outbound

This paper cites Calibration for decision making: A principled approach to trustworthy ml, 2024.

On Calibration in Multi-Distribution Learning Calibration for decision making: A principled approach to trustworthy ml, 2024

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.890299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.352760Z digest=sha256:052889dfdfa1f1214a2d484efe9867c0ea58110dd332ea30f9df90e62be074f3

Observation 2882b277-28ab-4194-8cc0-17ad30c25982 · outbound

This paper cites Dissecting racial bias in an algorithm used to manage the health of populations.

On Calibration in Multi-Distribution Learning Dissecting racial bias in an algorithm used to manage the health of populations

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.873021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.358844Z digest=sha256:8b6122e890a1aef494915be400481580430879f96d22affe9da33b395def65cb

Observation 07918998-5212-433c-878e-1826ccdcd3df · outbound

This paper cites Proper scoring rules and bregman divergence.

On Calibration in Multi-Distribution Learning Proper scoring rules and bregman divergence

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.855435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.364808Z digest=sha256:f5320702690bc9f2f505f8e4d858799bbe42692303bf7d690af443af413808a2

Observation 2b6d189c-48e8-4b76-96ed-cb27d471f562 · outbound

This paper cites Frameworks and results in distributionally robust optimization.

On Calibration in Multi-Distribution Learning Frameworks and results in distributionally robust optimization

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.838200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.370579Z digest=sha256:e4a0b80df7d798be82af506755787fb24738e952d671e6d8d0f8b35f76dfc9cf

Observation fc2ee520-3990-4563-81f4-60b947047347 · outbound

This paper cites On measures of entropy and information.

On Calibration in Multi-Distribution Learning On measures of entropy and information

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.818807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.377200Z digest=sha256:186490fbdffa33b84272a90640ae58ab3951563161894a39bbca6f0d4843c4f6

Observation 6225612e-dfa6-47b7-a458-1b3a1a83e94d · outbound

This paper cites Convex analysis.

On Calibration in Multi-Distribution Learning Convex analysis

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.798614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.385310Z digest=sha256:36225084131edf9cddfed3e481eca769dcbf45595de6773f647033ca3f0b42b1

Observation b5c7e242-9a84-4dd5-825e-cec0e386c671 · outbound

This paper cites Coherent approaches to risk in optimization under uncertainty.

On Calibration in Multi-Distribution Learning Coherent approaches to risk in optimization under uncertainty

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.780120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.391018Z digest=sha256:0958fe1df86f6dad8673919e9914dd1c079e560deece61a7fad8c36b9997ee41

Observation 95bb4846-f42e-4360-a43f-deb5abccd872 · outbound

This paper cites Multi-group agnostic pac learnability.

On Calibration in Multi-Distribution Learning Multi-group agnostic pac learnability

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.758998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.397461Z digest=sha256:5aadf441e20ec9be1ba0a5856425957e7ec47ac7a1a43b5a6f0bf4835f9edaa0

Observation 9deaf1b9-ed68-499e-958a-2aea86205704 · outbound

This paper cites Hashimoto, and Percy Liang.

On Calibration in Multi-Distribution Learning Hashimoto, and Percy Liang

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.738392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.403925Z digest=sha256:0137d91f10be42f6f8f93f6bc34c69eba5ca66e3e6e249a2e01ede03882ea3fb

Observation b8d7fc61-8187-4ab0-a027-2bf5d0752ce4 · outbound

This paper cites Conditional Value-at-Risk (CVaR).

On Calibration in Multi-Distribution Learning Conditional Value-at-Risk (CVaR)

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.719170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.409937Z digest=sha256:c8558f91cc32189a1911a9e5abee3d2c5da92477d6f8dd5e311ea826fac3986a

Observation 806ca5c6-dab4-4474-b63f-a3a9f29ea7dd · outbound

This paper cites Evaluating model calibration in classification.

On Calibration in Multi-Distribution Learning Evaluating model calibration in classification

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.695826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.415615Z digest=sha256:21a8692e1e50a0faef4173e26623970594c8e4890af7746110562a2c711e908d

Observation 7a209a14-9715-4af5-9e3d-23dc941b5f0c · outbound

This paper cites A theory of the learnable.

On Calibration in Multi-Distribution Learning A theory of the learnable

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.676034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.421613Z digest=sha256:4256d2bd1f6b522396b4a89d7d7b796e599754c8fab8b28af948d35a717b36c6

Observation 401fd15b-7826-40e2-96d4-fa45927de0f4 · outbound

This paper cites The Wasserstein distances.

On Calibration in Multi-Distribution Learning The Wasserstein distances

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.654599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.427488Z digest=sha256:c763c6139faa479fa6bc302554528d1976951741c88f7e5ff8b7816992bc2fe6

Observation 6ef9a640-a232-48b1-90ca-534283d45380 · outbound

This paper cites Optimal multi-distribution learning.

On Calibration in Multi-Distribution Learning Optimal multi-distribution learning

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.633824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.434423Z digest=sha256:a0649b20c0ce5e235b138bf00505f1a04eefacf22ce2a38cdb30410cb0f5dd68

Observation 87b89dec-5740-47fb-8793-0e9ce758fe43 · outbound

This paper cites Calibrating predictions to decisions: A novel approach to multi-class calibration.

On Calibration in Multi-Distribution Learning Calibrating predictions to decisions: A novel approach to multi-class calibration

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:33:25.611712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T12:33:25.439923Z digest=sha256:bd91d9e7fd02417260569f5082d287a31c0087e3cd0658a604fca567069ae1ef

Observation c99f73d2-b95f-4b9a-8787-bd1686837843 · outbound

This paper cites write newline.

On Calibration in Multi-Distribution Learning write newline

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-11T12:33:25.445880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:33:25.445880Z digest=sha256:281e7938ff74ac1d090c7d393307a9e474d3db22e07f90240b065dbd70b57c16

Pith citing papers

No inbound Pith citation observations are available.