Paper Citation Record · LEDGER

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences

As of 13 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 6 inbound Pith citation observations for arXiv:2502.01126.

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

pith.paper-citation-record.v1
2502.01126 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

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measured 61 of 61 standing notices

One-hop event checks from named stored sources.

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measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T18:08:46.660526Z

Reference resolution

55 of 55 outbound references displayed

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External citation measurements

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Outbound references

Observation 038a8a8a-2c88-40a9-a9ea-9749e2ffe95e · outbound

This paper cites Claude 3.5 Sonnet.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Claude 3.5 Sonnet

Reference 1

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Unresolved cited work

Reference 2

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Observation e509e91f-eca9-494a-ab27-11b4242163d4 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Constitutional AI: Harmlessness from AI Feedback

Reference 3

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Unresolved cited work

Reference 4

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Observation dd974ade-36e1-4551-b740-d9bc4a07e3e4 · outbound

This paper cites Deep reinforcement learning from human preferences.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Deep reinforcement learning from human preferences

Reference 5

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This paper cites DeGroot and Stephen E.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences DeGroot and Stephen E

Reference 6

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Observation c20c354f-7fac-4b5d-bcd9-8fce50d63381 · outbound

This paper cites The Llama 3 Herd of Models.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences The Llama 3 Herd of Models

Reference 7

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Observation 5bab9d77-0b27-4b7b-b112-dc3b5792b670 · outbound

This paper cites Sivakumar.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Sivakumar

Reference 8

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Observation 25bb767f-3e02-4c55-a6fd-94ae2ecbea01 · outbound

This paper cites On the foundations of noise-free selective classification.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences On the foundations of noise-free selective classification

Reference 9

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Observation 96c38c8d-dad7-473d-8026-6f82bf3b170c · outbound

This paper cites The Rating of Chessplayers, Past and Present.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences The Rating of Chessplayers, Past and Present

Reference 10

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Observation 9ae8e036-984d-401d-bdb6-f64009ff1e13 · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences KTO: Model Alignment as Prospect Theoretic Optimization

Reference 11

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Observation 9aa76400-b106-48be-b37c-9b7786440684 · outbound

This paper cites Selective prediction-set models with coverage guarantees.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Selective prediction-set models with coverage guarantees

Reference 12

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Observation 84c0728d-b3a4-4b59-9740-b39a87669bfe · outbound

This paper cites Gptscore: Evaluate as you desire.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Gptscore: Evaluate as you desire

Reference 13

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Observation 3feebc79-0d96-458c-95dd-9bf0520e9029 · outbound

This paper cites On Calibration of Modern Neural Networks.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences On Calibration of Modern Neural Networks

Reference 14

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This paper cites Weinberger.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Weinberger

Reference 15

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This paper cites A baseline for detecting misclassified and out-of-distribution examples in neural networks.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences A baseline for detecting misclassified and out-of-distribution examples in neural networks

Reference 16

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Observation 24e92e21-8248-4067-b93c-ffb1897ae9a2 · outbound

This paper cites Measuring massive multitask language understanding.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Measuring massive multitask language understanding

Reference 17

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Observation 8f8a93b4-2247-4cdd-9bfd-ceab9fcf0f74 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Measuring Mathematical Problem Solving With the MATH Dataset

Reference 18

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Observation 7598ce1d-e0dd-466c-8826-c37ce81c98b7 · outbound

This paper cites Minka, and Thore Graepel.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Minka, and Thore Graepel

Reference 19

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Observation ff0b0cc7-f982-4dc0-999b-8b60016070d5 · outbound

This paper cites What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Reference 20

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Selective classification can magnify disparities across groups

Reference 21

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This paper cites Language models (mostly) know what they know, 2022.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Language models (mostly) know what they know, 2022

Reference 22

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Kemeny and J

Reference 23

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This paper cites Unanimous prediction for 100\ In Association for Computational Linguistics (ACL), 2016.

Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Unanimous prediction for 100\ In Association for Computational Linguistics (ACL), 2016

Reference 24

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Holistic Evaluation of Language Models

Reference 25

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences TruthfulQA: Measuring How Models Mimic Human Falsehoods

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Teaching models to express their uncertainty in words

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Self-Refine: Iterative Refinement with Self-Feedback

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Can a suit of armor conduct electricity? a new dataset for open book question answering

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Murphy and Robert L

Reference 30

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Cooper, and Milos Hauskrecht

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Cooper, and Milos Hauskrecht

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Negahban, Sewoong Oh, and Devavrat Shah

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Introducing chatgpt

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Training language models to follow instructions with human feedback

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences The pagerank citation ranking : Bringing order to the web

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Direct Preference Optimization: Your Language Model is Secretly a Reward Model

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences GPQA: A Graduate-Level Google-Proof Q&A Benchmark

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences SocialIQA: Commonsense Reasoning about Social Interactions

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Commonsenseqa: A question answering challenge targeting commonsense knowledge

Reference 43

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Fine-tuning Language Models for Factuality

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Nicolaus Tideman

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Minimum weighted feedback arc sets for ranking from pairwise comparisons

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Self-Consistency Improves Chain of Thought Reasoning in Language Models

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Tree of Thoughts: Deliberate Problem Solving with Large Language Models

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Self-Rewarding Language Models

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Navigating the grey area: Expressions of overconfidence and uncertainty in language models, 2023

Reference 53

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences Fine-Tuning Language Models from Human Preferences

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Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences write newline

Reference 55

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Inertia in Moral and Value Judgments of Large Language Models cites this paper.

Inertia in Moral and Value Judgments of Large Language Models Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences

Reference 45

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Reasoning Strategies in Large Language Models: Can They Follow, Prefer, and Optimize? cites this paper.

Reasoning Strategies in Large Language Models: Can They Follow, Prefer, and Optimize? Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences

Reference 21

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Generalization of Fine-Tuned Uncertainty Communication and Metacognition in Large Language Models cites this paper.

Generalization of Fine-Tuned Uncertainty Communication and Metacognition in Large Language Models Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences

Reference 701

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CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation cites this paper.

CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:36:01.641462Z

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Quantifying Consistency in LLM Logical Reasoning via Structural Uncertainty cites this paper.

Quantifying Consistency in LLM Logical Reasoning via Structural Uncertainty Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-03T18:08:46.662298Z

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MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperation cites this paper.

MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperation Language Models Prefer What They Know: Relative Confidence Estimation via Confidence Preferences

Reference 124

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