Paper Citation Record · LEDGER

Missing value imputation with adversarial random forests -- MissARF

As of 19 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2507.15681.

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

pith.paper-citation-record.v1
2507.15681 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:32:10.694968Z

measured 49 of 49 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T22:21:54.822901Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z

Reference resolution

47 of 47 outbound references displayed

verified exact2
verified fuzzy39
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d8e69c08-b9ba-4197-834b-e17820003bfd · outbound

This paper cites Inference and missing data.

Missing value imputation with adversarial random forests -- MissARF Inference and missing data

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T15:32:09.108541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 509c0329-8cbb-4e65-a9cb-3b049a3c6590 · outbound

This paper cites Flexible Imputation of Missing Data.

Missing value imputation with adversarial random forests -- MissARF Flexible Imputation of Missing Data

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.559359Z

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 ebb097dc-4a09-4f38-9f9e-e10891fdeeb9 · outbound

This paper cites CRC Press, 2015.

Missing value imputation with adversarial random forests -- MissARF CRC Press, 2015

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.544206Z

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 46684222-3a19-4cc9-8611-21e07c44228c · outbound

This paper cites Classification and regression trees.

Missing value imputation with adversarial random forests -- MissARF Classification and regression trees

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.529185Z

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 38344de9-6b1f-4ce5-9889-3e11c5725e55 · outbound

This paper cites XGBoost: A scalable tree boosting system.

Missing value imputation with adversarial random forests -- MissARF XGBoost: A scalable tree boosting system

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.514075Z

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 e9b117d2-b6e8-4c54-ab3a-a7578bbba4f6 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017.

Missing value imputation with adversarial random forests -- MissARF Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T15:32:09.668781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bfe6a16-0348-43a8-a961-a1bbb02625af · outbound

This paper cites Random forest missing data algorithms.

Missing value imputation with adversarial random forests -- MissARF Random forest missing data algorithms

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.487779Z

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 75719cca-0336-45b3-91d6-b3be9d978889 · outbound

This paper cites On the consistency of supervised learning with missing values.

Missing value imputation with adversarial random forests -- MissARF On the consistency of supervised learning with missing values

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.473554Z

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 215d195d-aec2-40be-9ff3-4e0ebc04e635 · outbound

This paper cites A fair comparison of tree-based and parametric methods in multiple impu- tation by chained equations.

Missing value imputation with adversarial random forests -- MissARF A fair comparison of tree-based and parametric methods in multiple impu- tation by chained equations

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.458481Z

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 e8025e9c-6fdf-496f-aa38-4207397ee6f2 · outbound

This paper cites Review and evaluation of imputation methods for multivariate longitudinal data with mixed-type incomplete variables.

Missing value imputation with adversarial random forests -- MissARF Review and evaluation of imputation methods for multivariate longitudinal data with mixed-type incomplete variables

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.444185Z

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 4ed49625-2b95-4996-8f14-9984beb4f595 · outbound

This paper cites Identify the most appropriate imputation method for handling missing values in clinical structured datasets: a systematic review.BMC Medical Research Method- ology, 24(1):188, 2024.

Missing value imputation with adversarial random forests -- MissARF Identify the most appropriate imputation method for handling missing values in clinical structured datasets: a systematic review.BMC Medical Research Method- ology, 24(1):188, 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.408784Z

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 68ba773f-5df9-4434-8b52-a31a79aeb5a1 · outbound

This paper cites Does imputation matter? benchmark for real-life classification problems.

Missing value imputation with adversarial random forests -- MissARF Does imputation matter? benchmark for real-life classification problems

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.379886Z

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 9fd2346f-e296-400c-a6c2-7e69af3ee151 · outbound

This paper cites an unresolved cited work.

Missing value imputation with adversarial random forests -- MissARF Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:32:11.365785Z

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 e4c04b92-823f-4adc-b004-6698bb77012c · outbound

This paper cites Little and D.B.

Missing value imputation with adversarial random forests -- MissARF Little and D.B

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.352272Z

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 f4328fe1-2960-408b-a222-08ab6ee725ec · outbound

This paper cites Multiple imputation using chained equations: issues and guidance for practice.

Missing value imputation with adversarial random forests -- MissARF Multiple imputation using chained equations: issues and guidance for practice

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.338604Z

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 cf4ce027-3618-4a5e-bcc4-5c32f93d38b1 · outbound

This paper cites Missforest—non-parametric missing value imputation for mixed-type data.

Missing value imputation with adversarial random forests -- MissARF Missforest—non-parametric missing value imputation for mixed-type data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.324929Z

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 fb6aef18-bc5d-4e4d-9228-d2667fef52c4 · outbound

This paper cites Random forests.

Missing value imputation with adversarial random forests -- MissARF Random forests

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.310157Z

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 dae923b1-0dc4-4751-93d2-35ad1b965ff1 · outbound

This paper cites Multiple imputation after 18+ years.

Missing value imputation with adversarial random forests -- MissARF Multiple imputation after 18+ years

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.295817Z

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 dd52c3a4-3c9f-4c58-afe0-026e1a0ff706 · outbound

This paper cites Multiple imputation of discrete and continuous data by fully conditional specification.

Missing value imputation with adversarial random forests -- MissARF Multiple imputation of discrete and continuous data by fully conditional specification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.282155Z

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 f0f28ef0-966b-4430-b590-4fbe69d517d7 · outbound

This paper cites mice: Multivariate imputation by chained equations in r.

Missing value imputation with adversarial random forests -- MissARF mice: Multivariate imputation by chained equations in r

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.267161Z

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 fc08cc01-587a-4fb0-bd4e-1f249e97e07a · outbound

This paper cites missranger: Fast imputation of missing values.

Missing value imputation with adversarial random forests -- MissARF missranger: Fast imputation of missing values

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.252595Z

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 b5613a5a-1ab4-44b9-8629-38df96a7cb5c · outbound

This paper cites GPT-4 Technical Report.

Missing value imputation with adversarial random forests -- MissARF GPT-4 Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T15:32:10.576787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d4d9ac8-2107-44e6-9b65-7ee53cc6b7f3 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Missing value imputation with adversarial random forests -- MissARF Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T15:32:10.581395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7daf565-853c-43b6-8a43-61d5e7ab5aad · outbound

This paper cites Gain: Missing data imputation using generative adversarial nets.

Missing value imputation with adversarial random forests -- MissARF Gain: Missing data imputation using generative adversarial nets

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.236343Z

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 d2117b6b-ab1a-4476-b743-412d015fbe2b · outbound

This paper cites Learning from incomplete data with generative adver- sarial networks.

Missing value imputation with adversarial random forests -- MissARF Learning from incomplete data with generative adver- sarial networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.217038Z

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 5391b0b0-4fe0-467a-a5c7-7c9632b83564 · outbound

This paper cites Natural generative noise diffusion model imputation.

Missing value imputation with adversarial random forests -- MissARF Natural generative noise diffusion model imputation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.193872Z

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 f05bd993-b4d7-4e3b-b3d4-62d17f8fa3dc · outbound

This paper cites A systematic review of generative adversarial imputation network in missing data imputation.

Missing value imputation with adversarial random forests -- MissARF A systematic review of generative adversarial imputation network in missing data imputation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.175381Z

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 ef941405-33f5-4c50-b188-f63b32db578e · outbound

This paper cites Generative adversarial networks assist missing data imputation: A compre- hensive survey and evaluation.

Missing value imputation with adversarial random forests -- MissARF Generative adversarial networks assist missing data imputation: A compre- hensive survey and evaluation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.157281Z

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 ac786298-293d-4db8-bee1-b1846f0900be · outbound

This paper cites Why do tree-based models still outperform deep learning on typical tabular data? In S.

Missing value imputation with adversarial random forests -- MissARF Why do tree-based models still outperform deep learning on typical tabular data? In S

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.139652Z

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 4bb4c20d-e7ab-4937-baca-e2d92c6d0a4e · outbound

This paper cites Tabular data: Deep learning is not all you need.

Missing value imputation with adversarial random forests -- MissARF Tabular data: Deep learning is not all you need

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T15:32:10.613632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8df00d7-99bb-4c9f-8b6e-bcbcdfea03ea · outbound

This paper cites Adversarial random forests for density estimation and generative modeling.

Missing value imputation with adversarial random forests -- MissARF Adversarial random forests for density estimation and generative modeling

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.107242Z

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 bed97569-ac5f-460b-9138-d5b5883e9845 · outbound

This paper cites Synthcity: a benchmark framework for diverse use cases of tabular synthetic data.

Missing value imputation with adversarial random forests -- MissARF Synthcity: a benchmark framework for diverse use cases of tabular synthetic data

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.088811Z

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 333ad9f3-af30-4a86-be98-b30b02e005d0 · outbound

This paper cites Unsupervised learning with random forest predictors.

Missing value imputation with adversarial random forests -- MissARF Unsupervised learning with random forest predictors

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.072407Z

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 7bccfc24-fae9-4601-82d3-8c1a80397fdc · outbound

This paper cites Generative adversarial nets.

Missing value imputation with adversarial random forests -- MissARF Generative adversarial nets

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.057122Z

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 3812f98d-684d-4ea7-bce8-5317615e4e80 · outbound

This paper cites Countarfactuals–generating plausible model-agnostic counterfactual explanations with adversarial ran- dom forests.

Missing value imputation with adversarial random forests -- MissARF Countarfactuals–generating plausible model-agnostic counterfactual explanations with adversarial ran- dom forests

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.041944Z

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 dd0217d6-6a9c-46e8-9a94-0eecb8e8368c · outbound

This paper cites Good methods for coping with missing data in decision trees.

Missing value imputation with adversarial random forests -- MissARF Good methods for coping with missing data in decision trees

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.026046Z

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 66e687d6-e7ec-4206-be82-7afcd1f87d6d · outbound

This paper cites Ensemble missing data techniques for software effort prediction.

Missing value imputation with adversarial random forests -- MissARF Ensemble missing data techniques for software effort prediction

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:11.009363Z

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 7cf3cb8e-af8b-49ec-80ba-d43137d15041 · outbound

This paper cites Wright and Andreas Ziegler.

Missing value imputation with adversarial random forests -- MissARF Wright and Andreas Ziegler

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.992573Z

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 c8a096fa-33df-428a-8d6e-783642dd22df · outbound

This paper cites Wright, David S.

Missing value imputation with adversarial random forests -- MissARF Wright, David S

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.978195Z

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 d6a293fa-f310-4ed9-b4f1-a3edf734b177 · outbound

This paper cites simstudy: Illuminating research methods through data generation.

Missing value imputation with adversarial random forests -- MissARF simstudy: Illuminating research methods through data generation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.962213Z

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 f20f9095-4031-44dd-b6c4-16d71f93c2b5 · outbound

This paper cites simstudy: Simulation of study data.

Missing value imputation with adversarial random forests -- MissARF simstudy: Simulation of study data

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.943310Z

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 9f1e1c17-3554-4074-b898-6526e598a2ff · outbound

This paper cites missmethods: Methods for missing data.

Missing value imputation with adversarial random forests -- MissARF missmethods: Methods for missing data

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.925976Z

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 c0418a2b-cf31-4fa3-9ee4-96ce02f60cf1 · outbound

This paper cites Verification of forecasts expressed in terms of probability.

Missing value imputation with adversarial random forests -- MissARF Verification of forecasts expressed in terms of probability

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.909893Z

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 98d504e2-c686-48e9-87e5-602fdf154464 · outbound

This paper cites Diabetes health indicators dataset.

Missing value imputation with adversarial random forests -- MissARF Diabetes health indicators dataset

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.895324Z

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 a3e9dfca-67d9-4deb-a0fc-8793c965134c · outbound

This paper cites Recursive partitioning for missing data imputation in the presence of interaction effects.

Missing value imputation with adversarial random forests -- MissARF Recursive partitioning for missing data imputation in the presence of interaction effects

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:32:10.880007Z

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 7e239103-b5c9-435e-95d9-f7e080834ddb · outbound

This paper cites Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests.

Missing value imputation with adversarial random forests -- MissARF Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:32:10.829207Z

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 c537f2d0-bc99-4ae1-8cad-73654470c10e · outbound

This paper cites at least equal to the percentage of incomplete cases.

Missing value imputation with adversarial random forests -- MissARF at least equal to the percentage of incomplete cases

Reference 47

Resolution: verified exact; raw_fallback, observed 2026-08-06T15:32:10.806089Z

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

Observation 76b5236e-dbac-4358-ac88-a978da1aa266 · inbound

Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests cites this paper.

Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests Missing value imputation with adversarial random forests -- MissARF

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:22:51.631224Z

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 0777e0a4-f7a0-4171-82c4-fc643ed77da0 · inbound

Testing independence in the presence of missing data: high-dimensional case cites this paper.

Testing independence in the presence of missing data: high-dimensional case Missing value imputation with adversarial random forests -- MissARF

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:51:09.948254Z

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.