Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:45:13.719880Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 1 inbound Pith citation observation for arXiv:2506.23862.
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 2026-08-06T21:45:13.719880Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-25T04:56:55.294352Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T05:00:22.656473Z
76 of 76 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Bhattacharya and R
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Chernozhukov, I
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Chernozhukov, D
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Chernozhukov, J
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Adaptive Uncertainty Quantification for Generative AI
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Conformal Prediction with Large Language Models for Multi-Choice Question Answering
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression Unresolved cited work
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Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression GPT -4 Technical Report , Mar
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LLM Sparsity Prior for Robust Feature Selection Large Language Models for Statistical Inference: Context Augmentation with Applications to the Two-Sample Problem and Regression
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