Consensus-Driven Active Model Selection | Paper Citation Record

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This paper cites Invariant Risk Minimization.

Consensus-Driven Active Model Selection Invariant Risk Minimization

Reference 1

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Observation 1e4384c0-7ee2-427b-bbcb-9e498db1b4d2 · outbound

This paper cites From detection of individual metastases to classification of lymph node status at the pa- tient level: the camelyon17 challenge.

Consensus-Driven Active Model Selection From detection of individual metastases to classification of lymph node status at the pa- tient level: the camelyon17 challenge

Reference 2

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Observation 0901b579-034e-43cd-8d51-ab2ad801290a · outbound

This paper cites Recognition in terra incognita.

Consensus-Driven Active Model Selection Recognition in terra incognita

Reference 3

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Observation 1ec199eb-b8f3-49bc-a3e2-3ba3e05490b4 · outbound

This paper cites The iWildCam 2018 Challenge Dataset.

Consensus-Driven Active Model Selection The iWildCam 2018 Challenge Dataset

Reference 4

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Observation 3e8476ee-b6ef-4a9e-9594-675f8ecbb85d · outbound

This paper cites Nuanced metrics for measur- ing unintended bias with real data for text classification.

Consensus-Driven Active Model Selection Nuanced metrics for measur- ing unintended bias with real data for text classification

Reference 5

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Observation 70c9522c-66f2-4920-a1ad-619c53ee2575 · outbound

This paper cites Lean crowdsourcing: Combining humans and machines in an on- line system.

Consensus-Driven Active Model Selection Lean crowdsourcing: Combining humans and machines in an on- line system

Reference 6

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Observation 2d16ce0f-5c7d-4af1-9c4a-d28a165f911c · outbound

This paper cites A general model for aggregating annota- tions across simple, complex, and multi-object annotation tasks.

Consensus-Driven Active Model Selection A general model for aggregating annota- tions across simple, complex, and multi-object annotation tasks

Reference 7

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Observation ae3e8a38-9d91-4fb2-8f75-a48d03b24c52 · outbound

This paper cites MONAI: An open-source framework for deep learning in healthcare.

Consensus-Driven Active Model Selection MONAI: An open-source framework for deep learning in healthcare

Reference 8

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Observation 6629cb1e-31a2-478f-a5f3-f31873777ae3 · outbound

This paper cites Transferability vs.

Consensus-Driven Active Model Selection Transferability vs

Reference 9

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Observation fb557729-b6f8-4c31-be44-0f025806aa40 · outbound

This paper cites Functional map of the world.

Consensus-Driven Active Model Selection Functional map of the world

Reference 10

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Observation 4abaffef-da15-47df-857d-b99fd0e74464 · outbound

This paper cites Towards discriminability and diversity: Batch nuclear-norm maximization under label in- sufficient situations.

Consensus-Driven Active Model Selection Towards discriminability and diversity: Batch nuclear-norm maximization under label in- sufficient situations

Reference 11

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Observation 517cf4fc-a906-447d-88cf-633ea205713a · outbound

This paper cites Gradually vanishing bridge for adver- sarial domain adaptation.

Consensus-Driven Active Model Selection Gradually vanishing bridge for adver- sarial domain adaptation

Reference 12

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Observation 387d7572-ab8b-40ef-9910-62d991533c43 · outbound

This paper cites Committee-based sampling for training probabilistic classifiers.

Consensus-Driven Active Model Selection Committee-based sampling for training probabilistic classifiers

Reference 13

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Observation a0fef7d2-1d79-496c-a60d-122289996bb6 · outbound

This paper cites Maximum like- lihood estimation of observer error-rates using the em algo- rithm.

Consensus-Driven Active Model Selection Maximum like- lihood estimation of observer error-rates using the em algo- rithm

Reference 14

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Observation 166bf8ed-0fbb-4885-8151-dc62723aada6 · outbound

This paper cites Better prac- tices for domain adaptation.

Consensus-Driven Active Model Selection Better prac- tices for domain adaptation

Reference 15

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Observation c0b68464-bd0d-477a-bcd5-ac77efc760f1 · outbound

This paper cites On Statistical Bias In Active Learning: How and When To Fix It.

Consensus-Driven Active Model Selection On Statistical Bias In Active Learning: How and When To Fix It

Reference 16

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This paper cites Domain-adversarial training of neural networks.

Consensus-Driven Active Model Selection Domain-adversarial training of neural networks

Reference 17

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Observation 635c795d-ca4c-4068-86fc-2e5b379ea5d1 · outbound

This paper cites Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation.

Consensus-Driven Active Model Selection Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation

Reference 18

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This paper cites Learning whom to trust with mace.

Consensus-Driven Active Model Selection Learning whom to trust with mace

Reference 19

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Observation fbfb7f57-9a26-4513-ad97-a03598ac1956 · outbound

This paper cites Towards reliable model selection for unsupervised domain adaptation: An empirical study and a certified baseline.

Consensus-Driven Active Model Selection Towards reliable model selection for unsupervised domain adaptation: An empirical study and a certified baseline

Reference 20

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Observation b030c36c-ed0f-4a7a-bde6-63159dab1e20 · outbound

This paper cites Does distributionally robust supervised learning give robust classifiers? In International Conference on Machine Learn- ing, pages 2029–2037.

Consensus-Driven Active Model Selection Does distributionally robust supervised learning give robust classifiers? In International Conference on Machine Learn- ing, pages 2029–2037

Reference 21

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Observation 78d07972-b655-444d-8c5e-6a5ca007bea2 · outbound

This paper cites HuggingFace Models, 2025.

Consensus-Driven Active Model Selection HuggingFace Models, 2025

Reference 22

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Observation c83bbf06-e6e9-4d76-9ff7-7608e5ee8d3e · outbound

This paper cites Minimum class confusion for versatile domain adaptation.

Consensus-Driven Active Model Selection Minimum class confusion for versatile domain adaptation

Reference 23

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Observation d24cceac-b1c0-4f76-8fd4-91ae73166449 · outbound

This paper cites Uda-bench: Revisiting common assumptions in un- 9 supervised domain adaptation using a standardized frame- work.

Consensus-Driven Active Model Selection Uda-bench: Revisiting common assumptions in un- 9 supervised domain adaptation using a standardized frame- work

Reference 24

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Observation d9dfc992-a6c8-49d9-b83f-e8b42d2e55d2 · outbound

This paper cites Online active model selection for pre-trained classifiers.

Consensus-Driven Active Model Selection Online active model selection for pre-trained classifiers

Reference 25

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Observation fd3f7b2c-fdf7-4dec-8f8a-d6fc04b18ce8 · outbound

This paper cites Anytime model selection in linear ban- dits, 2023.

Consensus-Driven Active Model Selection Anytime model selection in linear ban- dits, 2023

Reference 26

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Observation 988d1ad9-67e3-41ba-9ce6-5fa9dcdbd1c8 · outbound

This paper cites The caltech fish counting dataset: A benchmark for multiple- object tracking and counting.

Consensus-Driven Active Model Selection The caltech fish counting dataset: A benchmark for multiple- object tracking and counting

Reference 27

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Observation 60ce1592-4473-4d54-9100-ddea4085d4af · outbound

This paper cites Unsuper- vised domain adaptation in the real world: A case study in sonar video.

Consensus-Driven Active Model Selection Unsuper- vised domain adaptation in the real world: A case study in sonar video

Reference 28

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Observation e5450ccb-a9aa-40c3-b89c-b665a1d9bb0c · outbound

This paper cites Align and Distill: Unifying and Improving Domain Adaptive Object Detection.

Consensus-Driven Active Model Selection Align and Distill: Unifying and Improving Domain Adaptive Object Detection

Reference 29

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Observation f487026b-53e1-4eea-aad1-803c489d2d0e · outbound

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

Consensus-Driven Active Model Selection Wilds: A benchmark of in-the- wild distribution shifts

Reference 30

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Observation 7dff2d76-3a17-4955-917d-54ea03759099 · outbound

This paper cites Active testing: Sample-efficient model evalu- ation.

Consensus-Driven Active Model Selection Active testing: Sample-efficient model evalu- ation

Reference 31

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Observation ffae6e46-7ef3-4b6b-a867-a3ce8e780cdc · outbound

This paper cites Active surrogate estimators: An active learning approach to label-efficient model evaluation.

Consensus-Driven Active Model Selection Active surrogate estimators: An active learning approach to label-efficient model evaluation

Reference 32

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Observation 56702a18-7a57-42f2-bbdf-5f4e9a3fe5d5 · outbound

This paper cites Learning multiple layers of features from tiny images.

Consensus-Driven Active Model Selection Learning multiple layers of features from tiny images

Reference 33

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This paper cites Deeper, broader and artier domain generaliza- tion.

Consensus-Driven Active Model Selection Deeper, broader and artier domain generaliza- tion

Reference 34

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Observation b7850992-4467-4845-baff-ee844f409199 · outbound

This paper cites A survey on deep active learning: Recent advances and new frontiers.

Consensus-Driven Active Model Selection A survey on deep active learning: Recent advances and new frontiers

Reference 35

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Observation 48053c62-ef32-4812-bb39-d814b9a1511d · outbound

This paper cites Domain adaptation with auxiliary target domain-oriented classifier.

Consensus-Driven Active Model Selection Domain adaptation with auxiliary target domain-oriented classifier

Reference 36

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Observation d57557b5-c209-4bb9-8f37-e4f3454dfe7c · outbound

This paper cites Contextual active online model selection with expert advice.

Consensus-Driven Active Model Selection Contextual active online model selection with expert advice

Reference 37

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Observation 83c8498a-cdc1-4093-96a6-1873924f09a9 · outbound

This paper cites Learning transferable features with deep adaptation net- works.

Consensus-Driven Active Model Selection Learning transferable features with deep adaptation net- works

Reference 38

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Observation 9ae4d86a-4582-4a4b-922f-3506f55f3b34 · outbound

This paper cites Conditional adversarial domain adapta- tion.

Consensus-Driven Active Model Selection Conditional adversarial domain adapta- tion

Reference 39

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Observation 31dc1740-a86c-4470-8521-3e5dbcac7ff9 · outbound

This paper cites Active model selection: A variance minimization approach.

Consensus-Driven Active Model Selection Active model selection: A variance minimization approach

Reference 40

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Observation ece2aa3e-f315-439e-90c4-f14bcfb83808 · outbound

This paper cites Accuracy on the line: on the strong correlation between out-of-distribution and in- distribution generalization.

Consensus-Driven Active Model Selection Accuracy on the line: on the strong correlation between out-of-distribution and in- distribution generalization

Reference 41

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Observation dcdee6ba-0e73-4ab3-9201-d6599c63056c · outbound

This paper cites Unsupervised Domain Adaptation: A Reality Check.

Consensus-Driven Active Model Selection Unsupervised Domain Adaptation: A Reality Check

Reference 42

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Observation f6a08ed9-8d0e-4d94-9aef-91b4f8d26fc5 · outbound

This paper cites Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation.

Consensus-Driven Active Model Selection Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation

Reference 43

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Observation 38554e62-2286-4a6b-b946-9a0eb9223545 · outbound

This paper cites Active testing: An efficient and robust framework for estimating ac- curacy.

Consensus-Driven Active Model Selection Active testing: An efficient and robust framework for estimating ac- curacy

Reference 44

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Observation 6f265f80-931a-48f8-a442-991ab2b728cc · outbound

This paper cites All models are wrong, some are useful: Model Selection with Limited Labels.

Consensus-Driven Active Model Selection All models are wrong, some are useful: Model Selection with Limited Labels

Reference 45

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Observation db6f626c-9732-4324-a48f-8c11d03e039c · outbound

This paper cites Bioimage model zoo: a community-driven resource for accessible deep learning in bioimage analysis.

Consensus-Driven Active Model Selection Bioimage model zoo: a community-driven resource for accessible deep learning in bioimage analysis

Reference 46

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Observation 5f064e50-cd4a-45b8-b1ca-baa16d8ab3c8 · outbound

This paper cites The benefits of a model of annotation.

Consensus-Driven Active Model Selection The benefits of a model of annotation

Reference 47

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Observation 50d40479-984f-49df-b21b-b9300a57d7d1 · outbound

This paper cites Comparing bayesian models of annotation.

Consensus-Driven Active Model Selection Comparing bayesian models of annotation

Reference 48

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Observation 0bc3ec5d-f043-4eb5-ba04-da63f2c958bc · outbound

This paper cites Moment matching for multi-source domain adaptation.

Consensus-Driven Active Model Selection Moment matching for multi-source domain adaptation

Reference 49

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Observation ec59ef3e-de44-4467-b55e-bfd020a0d1d5 · outbound

This paper cites Snorkel: Rapid train- ing data creation with weak supervision.

Consensus-Driven Active Model Selection Snorkel: Rapid train- ing data creation with weak supervision

Reference 50

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Observation 4855429b-3adc-4435-a938-c189a030ff96 · outbound

This paper cites Do CIFAR-10 Classifiers Generalize to CIFAR-10?.

Consensus-Driven Active Model Selection Do CIFAR-10 Classifiers Generalize to CIFAR-10?

Reference 51

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Observation 8d986c45-b2b9-4cf0-a0fa-c95242cc1001 · outbound

This paper cites Do imagenet classifiers generalize to im- agenet? In International conference on machine learning , pages 5389–5400.

Consensus-Driven Active Model Selection Do imagenet classifiers generalize to im- agenet? In International conference on machine learning , pages 5389–5400

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.622749Z

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Observation 6fd1b246-f721-4562-9ea8-534dfc2f0e2d · outbound

This paper cites Ad- versarial branch architecture search for unsupervised domain adaptation.

Consensus-Driven Active Model Selection Ad- versarial branch architecture search for unsupervised domain adaptation

Reference 53

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Observation e98c1080-b400-4cc9-a12e-1566d86d0cf5 · outbound

This paper cites Maximum classifier discrepancy for unsuper- vised domain adaptation.

Consensus-Driven Active Model Selection Maximum classifier discrepancy for unsuper- vised domain adaptation

Reference 54

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Observation acf05595-7774-402d-a272-8bf6139f24ee · outbound

This paper cites Semi-supervised domain adaptation via minimax entropy.

Consensus-Driven Active Model Selection Semi-supervised domain adaptation via minimax entropy

Reference 55

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This paper cites Tune it the right way: Unsupervised validation of domain adaptation via soft neighborhood density.

Consensus-Driven Active Model Selection Tune it the right way: Unsupervised validation of domain adaptation via soft neighborhood density

Reference 56

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This paper cites Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation.

Consensus-Driven Active Model Selection Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation

Reference 57

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This paper cites Active comparison of prediction models.

Consensus-Driven Active Model Selection Active comparison of prediction models

Reference 58

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This paper cites Active learning literature survey.

Consensus-Driven Active Model Selection Active learning literature survey

Reference 59

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This paper cites Evaluat- ing multiple models using labeled and unlabeled data.

Consensus-Driven Active Model Selection Evaluat- ing multiple models using labeled and unlabeled data

Reference 60

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This paper cites Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation.

Consensus-Driven Active Model Selection Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation

Reference 61

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This paper cites Deep coral: Correlation alignment for deep domain adaptation.

Consensus-Driven Active Model Selection Deep coral: Correlation alignment for deep domain adaptation

Reference 62

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This paper cites Influence of ai’s uncertainty in the dawid- skene aggregation for human-ai crowdsourcing.

Consensus-Driven Active Model Selection Influence of ai’s uncertainty in the dawid- skene aggregation for human-ai crowdsourcing

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.504208Z

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This paper cites Id and ood performance are sometimes inversely correlated on real-world datasets.

Consensus-Driven Active Model Selection Id and ood performance are sometimes inversely correlated on real-world datasets

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.489552Z

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Observation dd74ccd7-7eb2-4e1c-ae62-a7ecff18b0cd · outbound

This paper cites Lean multiclass crowdsourcing.

Consensus-Driven Active Model Selection Lean multiclass crowdsourcing

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.474152Z

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This paper cites An overview of statistical learning the- ory.

Consensus-Driven Active Model Selection An overview of statistical learning the- ory

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.459965Z

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Observation b3116fda-8e67-40eb-b06e-05e4d140981c · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Consensus-Driven Active Model Selection GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 67

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Consensus-Driven Active Model Selection The multidimensional wisdom of crowds

Reference 68

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Observation eab95581-3743-4a4e-8c7c-0718e55cced2 · outbound

This paper cites Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?.

Consensus-Driven Active Model Selection Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?

Reference 69

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This paper cites Towards accurate model selection in deep unsuper- vised domain adaptation.

Consensus-Driven Active Model Selection Towards accurate model selection in deep unsuper- vised domain adaptation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.430895Z

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Observation d353583f-f0d1-4c2c-81e3-9072c1589e59 · outbound

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Consensus-Driven Active Model Selection Success rate

Reference 71

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Observation b42190da-dc50-4301-9717-4acd9f613e69 · outbound

This paper cites Dawid-Skene data generating process cyi ci c 1.true class drawn from item categorical prior 2.

Consensus-Driven Active Model Selection Dawid-Skene data generating process cyi ci c 1.true class drawn from item categorical prior 2

Reference 72

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Observation 803a6ee9-3f49-4204-b8d5-b9eabbc9f343 · outbound

This paper cites A visual depiction of the Dawid-Skene [14] data gener- ating process that we adapt to active model selection.

Consensus-Driven Active Model Selection A visual depiction of the Dawid-Skene [14] data gener- ating process that we adapt to active model selection

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.382022Z

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Observation 245b57d7-88fa-427a-bf24-7418b998f5ed · outbound

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Consensus-Driven Active Model Selection Unresolved cited work

Reference 74

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Observation 815f3c49-a431-452d-a4f7-d384ed24a64f · outbound

This paper cites To accommodate Bayesian updates, we initialize each θk,c to be a Dirich- let prior.

Consensus-Driven Active Model Selection To accommodate Bayesian updates, we initialize each θk,c to be a Dirich- let prior

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:29:56.346644Z

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Observation b3a61bab-06a5-4059-b9de-c706d7a2ef8d · outbound

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Consensus-Driven Active Model Selection Unresolved cited work

Reference 76

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Observation b805dd01-1b5e-4af3-92c5-656c1cd6f831 · outbound

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Consensus-Driven Active Model Selection Unresolved cited work

Reference 77

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Observation 88fd4193-ba05-4880-8baf-a98446fa984b · outbound

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Consensus-Driven Active Model Selection source-only

Reference 78

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