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Paper Citation Record · LEDGER

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective

As of 15 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2507.07852.

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

pith.paper-citation-record.v1
2507.07852 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:40:08.867269Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

  • verified exact7
  • verified fuzzy6
  • unresolved12
  • parse uncertain0
  • malformed identifier0
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External citation measurements

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Outbound references

Observation 4aa8fdc6-8023-4dd8-8e2d-9a77b7886244 · outbound

This paper cites On one hand, we have σ2(H(t)) = sup ||f−f∗||2≤t PD ( (f (x,z,a)−f∗(x,z,a))4 ) ≤ 4PD ( (f (x,z,a)−f∗(x,z,a))2 ) ≤ 4t2.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective On one hand, we have σ2(H(t)) = sup ||f−f∗||2≤t PD ( (f (x,z,a)−f∗(x,z,a))4 ) ≤ 4PD ( (f (x,z,a)−f∗(x,z,a))2 ) ≤ 4t2

Reference 2

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ed260b21-4b72-45f0-96c4-0f5084f1a799 · outbound

This paper cites Automatic Doubly Robust Forests.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Automatic Doubly Robust Forests

Reference 4

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local_arxiv, observed 2026-08-06T18:40:10.464957Z

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Observation a4f0bf86-b20d-4a6a-879d-5e97e67db001 · outbound

This paper cites Statistically valid post-deployment monitoring should be standard for ai-based digital health.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Statistically valid post-deployment monitoring should be standard for ai-based digital health

Reference 7

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Observation 78ea4913-52bd-4b7a-804e-6e3d6f900333 · outbound

This paper cites Imputation Strategies for Rightcensored Wages in Longitudinal Datasets.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Imputation Strategies for Rightcensored Wages in Longitudinal Datasets

Reference 8

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local_arxiv, observed 2026-08-06T18:40:10.054975Z

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Observation 2cb8dadb-b5b9-401c-92bc-7e47b65138ca · outbound

This paper cites Linear Bandits with Partially Observable Features.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Linear Bandits with Partially Observable Features

Reference 12

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local_arxiv, observed 2026-08-06T18:40:09.824736Z

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Observation 4303a11c-a75f-488e-9d60-fbec911be0eb · outbound

This paper cites Concentration around the mean for maxima of empirical processes.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Concentration around the mean for maxima of empirical processes

Reference 13

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local_arxiv, observed 2026-08-06T18:40:09.699693Z

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Observation a5833662-5a43-44ba-82c8-fbd1a78993a8 · outbound

This paper cites LLM aided semi-supervision for Extractive Dialog Summarization.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective LLM aided semi-supervision for Extractive Dialog Summarization

Reference 15

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local_arxiv, observed 2026-08-06T18:40:09.534760Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation bbe00ed2-52f8-4d96-b1ac-64ea937a340b · outbound

This paper cites Synthetic data generation using large language models: Advances in text and code.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Synthetic data generation using large language models: Advances in text and code

Reference 16

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Observation 9e1655ca-6f50-4351-8b8d-eb608b110945 · outbound

This paper cites Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff

Reference 17

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Observation 8ef5998b-8c94-41ea-9df5-83f4088f51b5 · outbound

This paper cites Does Synthetic Data Generation of LLMs Help Clinical Text Mining?.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Does Synthetic Data Generation of LLMs Help Clinical Text Mining?

Reference 19

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Observation e4343245-8e01-4cda-b287-306e69445330 · outbound

This paper cites Handling censoring and censored data in survival analysis: a standalone systematic literature review.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Handling censoring and censored data in survival analysis: a standalone systematic literature review

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 25b2ef72-cae6-4e5a-a56d-0d285404a9a2 · outbound

This paper cites Prediction Aided by Surrogate Training.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Prediction Aided by Surrogate Training

Reference 21

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Observation cb2e7de0-e5db-4ec8-a385-470d767990f0 · outbound

This paper cites The Application of Large Language Models in Recommendation Systems.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective The Application of Large Language Models in Recommendation Systems

Reference 22

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local_arxiv, observed 2026-08-06T18:40:09.322157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 90f4ba64-30c6-4b50-96e9-56173154bb0d · outbound

This paper cites Zhang, Tiffany Tianhui Cai, Hongseok Namkoong, and Daniel Russo.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Zhang, Tiffany Tianhui Cai, Hongseok Namkoong, and Daniel Russo

Reference 23

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b4c73cc2-1642-4498-be1b-9a7070c480ed · outbound

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Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Unresolved cited work

Reference 24

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Observation 7658f477-c957-4743-a438-7b5f0d638e09 · outbound

This paper cites There is a function Q(r,t) increasing in the first argument r and Q(2r,t)≤ 2Q(r,t) for all r≥s, where s is some scalar.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective There is a function Q(r,t) increasing in the first argument r and Q(2r,t)≤ 2Q(r,t) for all r≥s, where s is some scalar

Reference 25

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Observation bcb0921e-e751-4451-80af-4e4a38515d3e · outbound

This paper cites data D ={(xi,ai,ri)}n i=1 where E[ri|xi,ai] = f∗(xi,ai).

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective data D ={(xi,ai,ri)}n i=1 where E[ri|xi,ai] = f∗(xi,ai)

Reference 27

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 5fba3e7e-def0-4ece-9494-8033ef68edaf · outbound

This paper cites Applying Dudley’s integral bound, we have Rn(t,Gδ0) ≲ inf α>0 { 4α + 12√n ∫t α √ logN (ε,Gδ0,L2(P))dε }.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Applying Dudley’s integral bound, we have Rn(t,Gδ0) ≲ inf α>0 { 4α + 12√n ∫t α √ logN (ε,Gδ0,L2(P))dε }

Reference 28

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d66afca2-83a6-4484-9692-fbe76a158533 · outbound

This paper cites Contextual Online Decision Making with Infinite-Dimensional Functional Regression.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Contextual Online Decision Making with Infinite-Dimensional Functional Regression

Reference 1996

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Observation 2a599467-08b5-40ec-9d2d-5e99043bbc53 · outbound

This paper cites Oracle inequalities in empirical risk minimization and sparse recovery prob- lems: ´Ecole D’ ´Et´ e de Probabilit´ es de Saint-Flour XXXVIII-2008, volume.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Oracle inequalities in empirical risk minimization and sparse recovery prob- lems: ´Ecole D’ ´Et´ e de Probabilit´ es de Saint-Flour XXXVIII-2008, volume

Reference 2005

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 9b16bfc4-08d6-41d9-9653-b3685d6f6924 · outbound

This paper cites Automatic debiased machine learning for covariate shifts.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Automatic debiased machine learning for covariate shifts

Reference 2017

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Observation a200d340-664b-42ca-8fd8-7d826c1256f4 · outbound

This paper cites CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Reference 2019

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Observation 2ff9ee44-441e-42af-87dd-d7b1038c77df · outbound

This paper cites Dynamic Pricing in the Linear Valuation Model using Shape Constraints.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Dynamic Pricing in the Linear Valuation Model using Shape Constraints

Reference 2020

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Observation afd707d6-e65f-4ad8-bd09-694d076a2439 · outbound

This paper cites Contextual Bandit with Missing Rewards.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Contextual Bandit with Missing Rewards

Reference 2021

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local_arxiv, observed 2026-08-06T18:40:10.864108Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 761847a0-0cbc-431c-b50f-9fb674ccefaa · outbound

This paper cites Data Augmentation for Intent Classification with Off-the-shelf Large Language Models.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Data Augmentation for Intent Classification with Off-the-shelf Large Language Models

Reference 2022

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Observation 7a1a4f5d-2e68-4943-a6a7-c10e22bb0090 · outbound

This paper cites Orthogonal Statistical Learning.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Orthogonal Statistical Learning

Reference 2023

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Observation 6204bb08-7889-4e4f-adc7-0d3f47ea75e6 · outbound

This paper cites Tractable Agreement Protocols.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Tractable Agreement Protocols

Reference 2024

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local_arxiv, observed 2026-08-06T18:40:10.239581Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2766e429-ca54-4b8b-b6f4-bcea474f7d2f · outbound

This paper cites Active Exploration via Autoregressive Generation of Missing Data.

Pre-Trained AI Model Assisted Online Decision-Making under Missing Covariates: A Theoretical Perspective Active Exploration via Autoregressive Generation of Missing Data

Reference 2025

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Pith citing papers

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