Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models | Paper Citation Record

Observation 1fc9b29b-caa9-4b48-8678-10493764c22f · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55, 2025.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1–55, 2025

Reference 1

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Observation bd7a68d5-7975-45ca-9620-cc087fb97c66 · outbound

This paper cites The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models

Reference 2

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Observation b6f8e618-f77a-4ac1-9e55-596c94a85807 · outbound

This paper cites Sources of Hallucination by Large Language Models on Inference Tasks.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Sources of Hallucination by Large Language Models on Inference Tasks

Reference 3

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Observation 6255a5b7-d4c3-485a-9f95-e805c6ae47fa · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630, 2024

Reference 4

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This paper cites Machine-learning applications of algorithmic randomness.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Machine-learning applications of algorithmic randomness

Reference 5

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Observation 7320411a-06c2-4d67-8a7d-94c9c2c6c233 · outbound

This paper cites Transduction with confidence and credibility.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Transduction with confidence and credibility

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.459625Z

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Observation fcdb03b8-ce49-492f-8398-4e48a9dbb15e · outbound

This paper cites Springer, 2005.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Springer, 2005

Reference 7

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Observation 61d5c348-e711-4d2c-af9a-c5254f2116cb · outbound

This paper cites Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents

Reference 8

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This paper cites A tutorial on conformal prediction.Journal of Machine Learning Research, 9(3), 2008.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models A tutorial on conformal prediction.Journal of Machine Learning Research, 9(3), 2008

Reference 9

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This paper cites Conformalized quantile regression.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Conformalized quantile regression

Reference 10

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Observation 57c8c605-3924-451b-848b-473ac7b9b202 · outbound

This paper cites Uncertainty Sets for Image Classifiers using Conformal Prediction.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Uncertainty Sets for Image Classifiers using Conformal Prediction

Reference 11

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Observation 40c0155a-b5b4-4b2b-acc3-e5e8a8ae0ded · outbound

This paper cites Distribution-free predictive inference for regression.Journal of the American Statistical Associ- ation, 113(523):1094–1111, 2018.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Distribution-free predictive inference for regression.Journal of the American Statistical Associ- ation, 113(523):1094–1111, 2018

Reference 12

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Observation b495a3eb-a22f-4920-8baf-91dc122b33f1 · outbound

This paper cites Jaakkola, and Regina Barzilay.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Jaakkola, and Regina Barzilay

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.413800Z

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Observation f4aabf6c-fb15-47c3-83ed-c3221db3862f · outbound

This paper cites Conformal generative modeling with improved sample efficiency through sequential greedy filtering, 2025.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Conformal generative modeling with improved sample efficiency through sequential greedy filtering, 2025

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.399561Z

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Observation 3fbc7ea4-3f0f-48c6-9de7-c562f60e8fc2 · outbound

This paper cites Good-turing frequency estimation without tears.Journal of quantitative linguistics, 2(3):217–237, 1995.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Good-turing frequency estimation without tears.Journal of quantitative linguistics, 2(3):217–237, 1995

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.385171Z

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Observation 09e05459-5b00-4ca2-89b8-cd8d5e043ccb · outbound

This paper cites Competitive distribution estimation: Why is good-turing good.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Competitive distribution estimation: Why is good-turing good

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.372732Z

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Observation 801e97ce-7ad3-40f7-9ce4-a1a463787e1a · outbound

This paper cites On the convergence rate of good-turing estimators.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models On the convergence rate of good-turing estimators

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.355645Z

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Observation 68d05c90-4780-4a46-9119-24a7d3460c9e · outbound

This paper cites Always good turing: Asymptotically optimal probability estimation.Science, 302(5644):427–431, 2003.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Always good turing: Asymptotically optimal probability estimation.Science, 302(5644):427–431, 2003

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.341270Z

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Observation 6ba8522f-7989-4709-88f3-0a45c745637f · outbound

This paper cites Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander M.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander M

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.322437Z

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Observation 6b41c7d9-9f4d-459f-806f-f63a13c1bd47 · outbound

This paper cites Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression

Reference 20

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This paper cites Api is enough: Conformal prediction for large language models without logit-access, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Api is enough: Conformal prediction for large language models without logit-access, 2024

Reference 21

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Observation c75e0af2-f4c5-4521-bef4-3a09ba384da9 · outbound

This paper cites Mitigating llm hallucinations via conformal abstention, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Mitigating llm hallucinations via conformal abstention, 2024

Reference 22

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This paper cites Learning conformal abstention policies for adaptive risk management in large language and vision-language models, 2025.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Learning conformal abstention policies for adaptive risk management in large language and vision-language models, 2025

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.287764Z

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Observation c482d8b8-0aaf-433f-9e24-98e62f92a6b3 · outbound

This paper cites To believe or not to believe your llm, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models To believe or not to believe your llm, 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.272395Z

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Observation 0b269032-8177-42ec-a2e5-caaee06762c7 · outbound

This paper cites an unresolved cited work.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 25

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Observation 8b7f40eb-3778-40e1-97c3-129020a593c8 · outbound

This paper cites Conformal alignment: Knowing when to trust foundation models with guarantees, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Conformal alignment: Knowing when to trust foundation models with guarantees, 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.244994Z

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Observation ec26df06-083d-4875-aa79-a0ccd69b63df · outbound

This paper cites Conformal prediction with large language models for multi-choice question answering, 2023.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Conformal prediction with large language models for multi-choice question answering, 2023

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.231203Z

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Observation ef52dfd6-dc21-41da-8888-9119edcd2ff6 · outbound

This paper cites Cherian, Isaac Gibbs, and Emmanuel J.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Cherian, Isaac Gibbs, and Emmanuel J

Reference 28

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Observation 40e2cdd5-7a7d-418c-a657-972ef2b00521 · outbound

This paper cites Language models with conformal factuality guarantees, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Language models with conformal factuality guarantees, 2024

Reference 29

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This paper cites Multi-group uncertainty quantification for long-form text generation, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Multi-group uncertainty quantification for long-form text generation, 2024

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.194014Z

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Observation f1a3d5ff-2ff1-4e91-a035-459fe620bb37 · outbound

This paper cites Conformal language model reasoning with coherent factuality.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Conformal language model reasoning with coherent factuality

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.179852Z

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Observation b452c446-74cb-4804-80ff-72b56a59aa7b · outbound

This paper cites Least ambiguous set-valued classifiers with bounded error levels.Journal of the American Statistical Association, 114(525):223–234, 2019.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Least ambiguous set-valued classifiers with bounded error levels.Journal of the American Statistical Association, 114(525):223–234, 2019

Reference 32

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Observation 0b4c3dea-8c40-490b-bff6-45c00a19846f · outbound

This paper cites Length optimization in conformal prediction.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Length optimization in conformal prediction

Reference 33

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Observation 772ea179-6515-484f-b168-e17592bfd437 · outbound

This paper cites Le, Ed H.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Le, Ed H

Reference 34

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Observation dd9ec98c-ee72-47da-9e1b-078e46fdfcce · outbound

This paper cites The llama 3 herd of models, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models The llama 3 herd of models, 2024

Reference 35

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Observation b2295cb4-ff9d-4647-bc33-5f731afb63d3 · outbound

This paper cites Training verifiers to solve math word problems, 2021.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Training verifiers to solve math word problems, 2021

Reference 36

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This paper cites Mixtral of experts, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Mixtral of experts, 2024

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.106288Z

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This paper cites Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation, 2023.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation, 2023

Reference 38

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This paper cites Determination of sample sizes for setting tolerance limits.The Annals of Mathematical Statistics, 12(1):91–96, 1941.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Determination of sample sizes for setting tolerance limits.The Annals of Mathematical Statistics, 12(1):91–96, 1941

Reference 39

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Observation 0cf80e83-9e56-4c64-96ab-9451b8d82f77 · outbound

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Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 40

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Observation 9be205d5-7b7b-43fe-941a-bbd3d2bbc246 · outbound

This paper cites Saunders, A.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Saunders, A

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.055881Z

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Observation ca42ccb1-77ba-47b1-b2f1-2cb2f059e39d · outbound

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Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 42

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Observation 3b41738f-4df4-4880-b633-351d94e731ec · outbound

This paper cites Conformal prediction with neural networks.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Conformal prediction with neural networks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.027817Z

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Observation f7896d9e-7b50-42bc-aec6-e6933e7eb7eb · outbound

This paper cites Inductive confidence machines for regression.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Inductive confidence machines for regression

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:15.010428Z

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Observation 00518d91-9a8c-40b9-aea8-27b7cd28b25a · outbound

This paper cites Tibshirani, and Larry Wasserman.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Tibshirani, and Larry Wasserman

Reference 45

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Observation 599a3da2-9e0f-430d-9bb3-a63acf29570d · outbound

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Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:30:14.985743Z

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Observation 3167cb1b-4422-4d93-a990-9b42467e30dd · outbound

This paper cites an unresolved cited work.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:30:14.967179Z

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Observation ad62f1a0-1ad1-48fc-bcc0-610515b53124 · outbound

This paper cites Learning optimal conformal classifiers, 2022.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Learning optimal conformal classifiers, 2022

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.952610Z

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Observation 6b4a1235-6c9a-46f4-997e-d6f2377b5e1e · outbound

This paper cites Uncertainty estimation and quantification for llms: A simple supervised approach, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Uncertainty estimation and quantification for llms: A simple supervised approach, 2024

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.937033Z

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Observation 27332605-c160-4ef9-9ec7-05fbeeaf5ad5 · outbound

This paper cites Semantically diverse language generation for uncertainty estimation in language models, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Semantically diverse language generation for uncertainty estimation in language models, 2024

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.922127Z

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Observation 8c4834ba-c96a-47b2-82de-d0ba23aaed72 · outbound

This paper cites Shifting attention to relevance: Towards the predictive uncertainty quantification of free-form large language models, 2024.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Shifting attention to relevance: Towards the predictive uncertainty quantification of free-form large language models, 2024

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.905058Z

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This paper cites Self-consistency improves chain of thought reasoning in language models, 2023.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Self-consistency improves chain of thought reasoning in language models, 2023

Reference 52

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Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 53

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This paper cites Concentration inequalities for the missing mass and for histogram rule error.J.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Concentration inequalities for the missing mass and for histogram rule error.J

Reference 54

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Observation cbf23991-c901-495a-9986-706cbb7404b8 · outbound

This paper cites On the concentration of the missing mass, 2012.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models On the concentration of the missing mass, 2012

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.855969Z

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Observation 22286960-03b7-4f61-a48e-201bfb4bcff7 · outbound

This paper cites Ohannessian.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Ohannessian

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.842400Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0df5b5ca-b36b-4ed5-862b-e3506d2b7685 · outbound

This paper cites Concentration and tail bounds for missing mass.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Concentration and tail bounds for missing mass

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.828380Z

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Observation 0035695b-23a8-40b0-a1b7-9d56a1b63a47 · outbound

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Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:30:14.806089Z

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Observation 34e595a4-348f-44dd-8bef-3bf6c6a9c0a1 · outbound

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Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Optimal probability estimation with applications to prediction and classification

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.789966Z

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Observation 80842557-81aa-40ac-8f94-847c41427655 · outbound

This paper cites Competitive distribution estimation: Why is good-turing good.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Competitive distribution estimation: Why is good-turing good

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.774599Z

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Observation 8824162e-ba0b-4902-8332-4a65f6020bed · outbound

This paper cites The power of absolute discounting: all-dimensional distribution estimation.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models The power of absolute discounting: all-dimensional distribution estimation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.760299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 43752f1e-21fc-4525-a450-4cec03244492 · outbound

This paper cites Ohannessian.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Ohannessian

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.746649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e2a5cc50-84c5-4c15-b385-8c2347510085 · outbound

This paper cites Competitive distribution estimation, 2015.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Competitive distribution estimation, 2015

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.730966Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 72923d55-fc50-4f76-bebf-bc7822372bbe · outbound

This paper cites Mean-squared accuracy of good-turing estimator.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Mean-squared accuracy of good-turing estimator

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.717347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8019c374-7429-4d1e-bb44-b5e8849a58d2 · outbound

This paper cites McAllester and Robert E.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models McAllester and Robert E

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.701964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2a7c8280-55c4-424f-870f-fcc360972fa1 · outbound

This paper cites Improved tail bounds for missing mass and confidence intervals for good-turing estimator.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Improved tail bounds for missing mass and confidence intervals for good-turing estimator

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.683407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7627cc5a-c599-4e15-920f-eefe1c199b65 · outbound

This paper cites an unresolved cited work.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:30:14.670300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 142a5254-641f-43f8-94d2-6fe69fc34cc0 · outbound

This paper cites an unresolved cited work.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:30:14.657351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0da7725e-5fb3-4a6e-9b4d-b9c8272f7b25 · outbound

This paper cites John Wiley & Sons, 1969.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models John Wiley & Sons, 1969

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.643530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6adc8924-0e2e-4cbe-ad9a-d17c9f57142c · outbound

This paper cites Lecture 11: The good–turing estimate.

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models Lecture 11: The good–turing estimate

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:30:14.631465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Outbound references

Pith citing papers