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Paper Citation Record · LEDGER

Adaptive sample splitting for randomization tests

As of 19 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2504.21572.

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

pith.paper-citation-record.v1
2504.21572 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:11:27.421209Z

measured 17 of 17 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

17 of 17 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1e59bc0c-4e31-4aa7-99e1-b38e661eaedf · outbound

This paper cites Leta,b∈ Rm with bi > 0 for alli, and let B∈ (0,Pm i=1bi].

Adaptive sample splitting for randomization tests Leta,b∈ Rm with bi > 0 for alli, and let B∈ (0,Pm i=1bi]

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.353451Z

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.

source=pdf_text observed=2026-08-16T05:11:27.365374Z digest=sha256:0ec918ceb571d56ebf61addb0ccd426e097d03e1ec7de379ceb9dc977ad1f6a4

Observation dcb91e0c-8647-4f10-8e0f-ae74411342bf · outbound

This paper cites Taking an expectation of both sides of the model conditional onXi, µ(Xi) = E[Yi|Xi] =µ0(Xi) +e(Xi)τ(Xi).

Adaptive sample splitting for randomization tests Taking an expectation of both sides of the model conditional onXi, µ(Xi) = E[Yi|Xi] =µ0(Xi) +e(Xi)τ(Xi)

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.497900Z

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.

source=pdf_text observed=2026-08-16T05:11:27.302723Z digest=sha256:e52641e24641478ad2f9bb6f48b255dd4775d99b282e131b1ec821821851dd3e

Observation bca522a2-f2e4-4050-84e6-dc07a3cda2f8 · outbound

This paper cites Conditional onX[n],Y [n] and ZI, the remaining randomness in thep-value comes from the observed treatment assignmentsZJk in the summationAk defined above.

Adaptive sample splitting for randomization tests Conditional onX[n],Y [n] and ZI, the remaining randomness in thep-value comes from the observed treatment assignmentsZJk in the summationAk defined above

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.384643Z

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.

source=pdf_text observed=2026-08-16T05:11:27.321038Z digest=sha256:7ca4f57daef5234de0f2782639146dc88c2b873d1c94400f0463b8bdff5e4603

Observation a5735160-b0c6-40f7-be86-8b120ec15f6a · outbound

This paper cites an unresolved cited work.

Adaptive sample splitting for randomization tests Unresolved cited work

Reference 6

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unresolved
raw_fallback, observed 2026-08-16T05:11:28.683679Z

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.

source=pdf_text observed=2026-08-16T05:11:27.151471Z digest=sha256:5d9968a33875b94928d1632b9e104b0452350ef941fafa1dc3d99e17f5601b3c

Observation be9cc89c-b587-4c74-a773-8943580b5a00 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

Adaptive sample splitting for randomization tests Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 7

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unresolved
no resolver link, observed 2026-08-16T05:11:27.197666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:11:27.197666Z digest=sha256:8e78fcd3471840b69fa2c08e47b064e8c243f7c9d3e5e3a62e5b8792990e0a5e

Observation 25074a0d-8b9a-48e0-a4e7-84796e018d98 · outbound

This paper cites (22) Let Ui := E[Xiϵi|Xi,Bi].

Adaptive sample splitting for randomization tests (22) Let Ui := E[Xiϵi|Xi,Bi]

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.549320Z

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.

source=pdf_text observed=2026-08-16T05:11:27.292655Z digest=sha256:75dff4c46600f0d001304a0c6a5be404346f66c881c6ef7fadbb081a3f80ee88

Observation 9c782e1c-3e59-426f-b46f-509ef28fc9b9 · outbound

This paper cites [2010], we have sup t∈R P ˜ZJk n ˜V−1/2 k ˜Ak≤t o − Φ(t) ≤ C ˜V 3/2 k X j∈Jk ˆW 3 j E ˜Zj n | ˜Zj−e(Xj)|3 o =OP 1/ p |Jk|.

Adaptive sample splitting for randomization tests [2010], we have sup t∈R P ˜ZJk n ˜V−1/2 k ˜Ak≤t o − Φ(t) ≤ C ˜V 3/2 k X j∈Jk ˆW 3 j E ˜Zj n | ˜Zj−e(Xj)|3 o =OP 1/ p |Jk|

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.427721Z

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.

source=pdf_text observed=2026-08-16T05:11:27.311532Z digest=sha256:7c4fdfcee7ffb7a62613eb024021b80a3e1e818e352c209ad1ec02c3f1c18a91

Observation b49f6130-488b-4d28-9227-f9bd6b9abae9 · outbound

This paper cites an unresolved cited work.

Adaptive sample splitting for randomization tests Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:11:28.269639Z

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.

source=pdf_text observed=2026-08-16T05:11:27.384746Z digest=sha256:bfcfc5119fbd0061309fecf22751e7c108bcef4396d067ced5259238090e9e61

Observation f2df858d-1f70-430f-add5-b051117d7f93 · outbound

This paper cites B.8 Proof of Proposition 6 Proof.

Adaptive sample splitting for randomization tests B.8 Proof of Proposition 6 Proof

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.197625Z

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.

source=pdf_text observed=2026-08-16T05:11:27.412096Z digest=sha256:994b9327b281193ab2ffa989e367d178ab38cd25f6ff2d33ff7c799143bc43f4

Observation 933f15b2-e8bf-4f44-8612-b8d94b7fdc59 · outbound

This paper cites 43 C Additional simulations C.1 Details of Figure 3 To generate Figure 3, we simulate a sample ofn = 200 i.i.d.

Adaptive sample splitting for randomization tests 43 C Additional simulations C.1 Details of Figure 3 To generate Figure 3, we simulate a sample ofn = 200 i.i.d

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.148771Z

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.

source=pdf_text observed=2026-08-16T05:11:27.421209Z digest=sha256:c795d24b4ff6c174b30e2e7dfebce8e52fb49c0325189c298354f1f4ebf9fde7

Observation 8d77cb03-d418-4582-b93b-5be36b42f36f · outbound

This paper cites Prepivoted permutation tests.

Adaptive sample splitting for randomization tests Prepivoted permutation tests

Reference 1935

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unresolved
no resolver link, observed 2026-08-16T05:11:27.091578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:11:27.091578Z digest=sha256:7fccf32eb89f70e86eb9464f3d8a1849149ef574e5511f689888c2e26746c4d9

Observation 5d30d005-99f0-45fb-8cf4-268c7371b80e · outbound

This paper cites Submodularity in data subset selection and active learning.

Adaptive sample splitting for randomization tests Submodularity in data subset selection and active learning

Reference 1964

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:11:28.607004Z

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.

source=pdf_text observed=2026-08-16T05:11:27.279354Z digest=sha256:cc8a97c2411655c0f06976615a690d660c26b3fb6249fbd90bf0c7b3dcf8932b

Observation f35b4477-605a-453f-bbf7-24dd70d63c2c · outbound

This paper cites Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning.

Adaptive sample splitting for randomization tests Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning

Reference 2006

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unresolved
no resolver link, observed 2026-08-16T05:11:27.127487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:11:27.127487Z digest=sha256:81bf7e8e5352536811f5f0cf1a93999bf6ef2aacc5558bee342521e0710dea6e

Observation 1481f70b-79f3-4298-8b7d-86666fbd8518 · outbound

This paper cites Enhanced inference for distributions and quantiles of individual treatment effects in various experiments.arXiv preprint arXiv:2407.13261,.

Adaptive sample splitting for randomization tests Enhanced inference for distributions and quantiles of individual treatment effects in various experiments.arXiv preprint arXiv:2407.13261,

Reference 2016

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no resolver link, observed 2026-08-16T05:11:27.072550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:11:27.072550Z digest=sha256:6008dd3e3362add7d0d2fc51ebf0c4cc64c149b720d9142b2b6eeeabedc396d0

Observation 30f2b480-ebaf-4a76-a56c-f3d08eebe012 · outbound

This paper cites an unresolved cited work.

Adaptive sample splitting for randomization tests Unresolved cited work

Reference 2018

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:11:28.238932Z

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.

source=pdf_text observed=2026-08-16T05:11:27.405976Z digest=sha256:cb299a850c3bb08a995d45b2c1b33b52b9e25ae418e38821a0f6216720fd9551

Observation 773aa0d6-9cfa-416d-abf9-3e6b14f47984 · outbound

This paper cites Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.

Adaptive sample splitting for randomization tests Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Reference 2021

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no resolver link, observed 2026-08-16T05:11:27.044683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:11:27.044683Z digest=sha256:202ddeae3b7d4f8f6d5d1f742946a5f6fc3b7487f7be41162c6ddbfc54772141

Observation 0c43b16d-c201-4b98-b7fa-de924ab70770 · outbound

This paper cites ML-assisted Randomization Tests for Detecting Treatment Effects in A/B Experiments.

Adaptive sample splitting for randomization tests ML-assisted Randomization Tests for Detecting Treatment Effects in A/B Experiments

Reference 2023

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no resolver link, observed 2026-08-16T05:11:27.099807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:11:27.099807Z digest=sha256:2055071ecef797d5a66eebf148714c84d05e255d83492a479a705c707a4b5d66

Pith citing papers

No inbound Pith citation observations are available.