Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:59:42.412963Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 10 inbound Pith citation observations for arXiv:2505.23854.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:59:42.412963Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T20:21:55.864745Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
55 of 55 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Observation eeabaf38-434a-4669-9f7d-f022633efb8e · outbound
Revisiting Uncertainty Estimation and Calibration of Large Language Models Large language models in medicine.Nature medicine, 29(8):1930–1940, 2023
Reference 1
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Adapted large language models can outperform medical experts in clinical text summa- rization.Nature medicine, 30(4):1134–1142, 2024
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Revisiting Uncertainty Estimation and Calibration of Large Language Models MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects.Authorea Preprints, 1:1–26, 2023
Reference 4
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Large language models in law: A survey.AI Open, 2024
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Us debt ceiling deal clears major hurdle in congress, 2023
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Shifting attention to relevance: Towards the uncertainty estimation of large language models
Reference 9
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Semantic calibration of llms through the lens of temperature scaling
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Mitigating object hallucinations in large vision-language models via attention calibration.arXiv preprint arXiv:2502.01969, 2025
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Llama 4: Multimodal intelligence
Reference 23
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Revisiting Uncertainty Estimation and Calibration of Large Language Models TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
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Reference 27
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Mmlu-pro: A more robust and challenging multi-task language understanding benchmark
Reference 28
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Discovering latent knowledge in language models without supervision
Reference 29
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Language Models (Mostly) Know What They Know
Reference 30
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630, 2024
Reference 31
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Reference 32
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Reference 35
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Revisiting Uncertainty Estimation and Calibration of Large Language Models The Llama 3 Herd of Models
Reference 36
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Revisiting Uncertainty Estimation and Calibration of Large Language Models DeepSeek-V3 Technical Report
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Reference 42
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Reference 43
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Revisiting Uncertainty Estimation and Calibration of Large Language Models The kendall rank correlation coefficient.Encyclopedia of measurement and statistics, 2:508–510, 2007
Reference 46
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Revisiting Uncertainty Estimation and Calibration of Large Language Models i’m not sure, but
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Revisiting Uncertainty Estimation and Calibration of Large Language Models The internal state of an llm knows when it’s lying
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Revisiting Uncertainty Estimation and Calibration of Large Language Models Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey
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Hallucinations Undermine Trust; Metacognition is a Way Forward Revisiting Uncertainty Estimation and Calibration of Large Language Models
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Epistemic Uncertainty for Test-Time Discovery Revisiting Uncertainty Estimation and Calibration of Large Language Models
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