Paper Citation Record · LEDGER

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation

As of 20 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.04332.

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

pith.paper-citation-record.v1
2507.04332 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:57:21.478885Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

33 of 33 outbound references displayed

verified exact1
verified fuzzy26
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c8820ea4-d770-453e-a5d2-879d51565086 · outbound

This paper cites Validating causal inference models via influence functions.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Validating causal inference models via influence functions

Reference 1

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Observation 1ddbb12c-ed99-487a-9fc4-431c7efba494 · outbound

This paper cites From real-world patient data to individualized treatment effects using machine learning: current and future methods to address underlying challenges.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation From real-world patient data to individualized treatment effects using machine learning: current and future methods to address underlying challenges

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:26.163166Z

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Observation 1048517b-46aa-456a-a58d-b2a18608c3b0 · outbound

This paper cites Causalml: Python package for causal machine learning, 2020.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Causalml: Python package for causal machine learning, 2020

Reference 3

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Observation be8d4005-c23b-4f23-bad2-6fc10f12e790 · outbound

This paper cites Nonparametric estimation of heterogeneous treatment effects: From theory to learning algorithms.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Nonparametric estimation of heterogeneous treatment effects: From theory to learning algorithms

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:26.002310Z

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Observation bbab68e5-14b9-4983-9e63-9ea40ea3c034 · outbound

This paper cites A large scale benchmark for uplift modeling.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation A large scale benchmark for uplift modeling

Reference 5

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Source-reported events for the cited work

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Observation 62ea7a3d-e7e7-441b-ba86-99c8e92d0b49 · outbound

This paper cites Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:25.667906Z

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Observation e3b39690-1400-4e0b-a907-b530e571edda · outbound

This paper cites Subgroup identification from randomized clinical trial data.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Subgroup identification from randomized clinical trial data

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:25.474228Z

Source-reported events for the cited work

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Observation b5a0da8a-8eef-42d9-a456-df3152dd1241 · outbound

This paper cites Conversion uplift in e-commerce: A systematic benchmark of modeling strategies.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Conversion uplift in e-commerce: A systematic benchmark of modeling strategies

Reference 8

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Observation add601ab-2e3c-4613-91af-be7d2b6e1d1c · outbound

This paper cites Causal inference and uplift modelling: A review of the literature.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Causal inference and uplift modelling: A review of the literature

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:25.121894Z

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Observation 1a643cbe-b774-4709-b808-cb61f56835d8 · outbound

This paper cites Incremental value modeling.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Incremental value modeling

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:24.937699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c25a20ac-58e2-4e15-9eb1-b3c1f44cadb6 · outbound

This paper cites Bayesian nonparametric modeling for causal inference.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Bayesian nonparametric modeling for causal inference

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:24.765621Z

Source-reported events for the cited work

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Observation a8833674-277e-42cb-90c9-9f583a7bf5ea · outbound

This paper cites Uplift modeling for clinical trial data.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Uplift modeling for clinical trial data

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:24.626442Z

Source-reported events for the cited work

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Observation a0448802-19f7-4a6b-b820-620633a925ce · outbound

This paper cites Learning representations for counterfactual inference.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Learning representations for counterfactual inference

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:24.433532Z

Source-reported events for the cited work

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Observation 58b1a571-ccc9-4b66-9883-d84fb2870b7e · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Lightgbm: A highly efficient gradient boosting decision tree

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:24.293176Z

Source-reported events for the cited work

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Observation 337ad0be-ed73-4d5e-bd3f-4f4d289e3dc9 · outbound

This paper cites Towards optimal doubly robust estimation of heterogeneous causal effects.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Towards optimal doubly robust estimation of heterogeneous causal effects

Reference 15

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Observation d695eba8-4b68-49a6-8c16-43dca4437f20 · outbound

This paper cites Double machine learning-based programme evaluation under unconfoundedness.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Double machine learning-based programme evaluation under unconfoundedness

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:24.159484Z

Source-reported events for the cited work

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Observation 52ea0430-ac75-46e5-a065-4d548346ad13 · outbound

This paper cites o ren R K \.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation o ren R K \

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:24.026899Z

Source-reported events for the cited work

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Observation 43d789ff-1d0b-48a6-ad35-4061965a7f2a · outbound

This paper cites Bigtarget hackathon hosted by lenta and microsoft.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Bigtarget hackathon hosted by lenta and microsoft

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:23.866708Z

Source-reported events for the cited work

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Observation 7cff2dbf-f4da-4f5f-b5f0-f5deba012f84 · outbound

This paper cites The true lift model: a novel data mining approach to response modeling in database marketing.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation The true lift model: a novel data mining approach to response modeling in database marketing

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:23.673820Z

Source-reported events for the cited work

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Observation 2e7fda2c-8aac-4212-9921-53181cf574b6 · outbound

This paper cites Quasi-oracle estimation of heterogeneous treatment effects.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Quasi-oracle estimation of heterogeneous treatment effects

Reference 20

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Source-reported events for the cited work

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Observation 4e8f72ac-0512-48e5-93b0-32a24f667642 · outbound

This paper cites Using control groups to target on predicted lift: Building and assessing uplift model.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Using control groups to target on predicted lift: Building and assessing uplift model

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:23.465468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9d7918bb-bc13-455e-a4f7-86775274ae7a · outbound

This paper cites Estimating causal effects of treatments in randomized and nonrandomized studies.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Estimating causal effects of treatments in randomized and nonrandomized studies

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:57:20.627943Z

Source-reported events for the cited work

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Observation c9abebd9-1d99-4671-a947-da3eccc90947 · outbound

This paper cites Causal inference using potential outcomes: Design, modeling, decisions.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Causal inference using potential outcomes: Design, modeling, decisions

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:23.262105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b902eb24-0db2-4d78-b8af-4312127b7634 · outbound

This paper cites Decision trees for uplift modeling.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Decision trees for uplift modeling

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:23.069714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 39ee383d-b7ec-43aa-8bab-e54aaf93332a · outbound

This paper cites Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T19:57:20.830178Z

Source-reported events for the cited work

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Observation 498f45d3-5e5f-4907-a69e-fdf58eeb6b35 · outbound

This paper cites Benchmarking Framework for Performance-Evaluation of Causal Inference Analysis.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Benchmarking Framework for Performance-Evaluation of Causal Inference Analysis

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T19:57:20.907424Z

Source-reported events for the cited work

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Observation a9d18d07-d32c-4714-a877-437679259e97 · outbound

This paper cites Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:22.916711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bea6f4f8-2fb2-4078-aeca-ab0916cf18c1 · outbound

This paper cites Data of x5 retailhero uplift modeling competition.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Data of x5 retailhero uplift modeling competition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:22.707658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 97f6f26a-a05f-4947-b72d-c18963be2953 · outbound

This paper cites Estimating heterogeneous treatment effects with observa- tional data.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Estimating heterogeneous treatment effects with observa- tional data

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:22.548607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6df61cb2-1582-4c71-8d3e-b73aa09ee5cd · outbound

This paper cites Representation learning for treatment effect estimation from observational data.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Representation learning for treatment effect estimation from observational data

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:22.421601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 254aee7d-4422-4a16-aaf6-de87bd1f2595 · outbound

This paper cites A unified survey of treatment effect heterogeneity modelling and uplift modelling.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation A unified survey of treatment effect heterogeneity modelling and uplift modelling

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:22.247657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 91ef5c7c-6aa5-4749-805e-684281ca3b04 · outbound

This paper cites Treatment effect estimation with disentangled latent factors.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Treatment effect estimation with disentangled latent factors

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:57:22.051015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3f9d5e59-4011-432e-9763-374ae6eee447 · outbound

This paper cites Synthetic data for uplift modeling and heterogenous treatment effect with known counterfactuals and ite, March 2022.

Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Synthetic data for uplift modeling and heterogenous treatment effect with known counterfactuals and ite, March 2022

Reference 33

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:57:21.804828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.