Paper Citation Record · LEDGER

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity

As of 10 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2605.27526.

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

pith.paper-citation-record.v1
2605.27526 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T15:34:24.619176Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

24 of 24 outbound references displayed

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unresolved15
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malformed identifier1
metadata mismatch2

External citation measurements

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Outbound references

Observation 66c6a8cb-8a05-4a61-bbe5-ad3ea48b01fa · outbound

This paper cites Sinkhorn Treatment Effects: A Causal Optimal Transport Measure.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Sinkhorn Treatment Effects: A Causal Optimal Transport Measure

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-06-29T15:43:32.835975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 14df26ea-d54f-4345-b635-fc228c4589c6 · outbound

This paper cites A simpler condition for consistency of a kernel independence test.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity A simpler condition for consistency of a kernel independence test

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-29T15:43:32.830351Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bfe446dd-9d64-4a87-a9bf-db156c566d20 · outbound

This paper cites On the hardness of conditional independence testing in practice.arXiv preprint arXiv:2512.14000,.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity On the hardness of conditional independence testing in practice.arXiv preprint arXiv:2512.14000,

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-29T15:43:32.833163Z

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Observation 02eca165-19c2-4cc2-9c1a-48dc9d77eefa · outbound

This paper cites month = mar, year =.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity month = mar, year =

Reference 4

Resolution: metadata mismatch; doi, observed 2026-06-29T15:43:32.487518Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 40288edc-baa0-4a38-92a3-8450855edb8c · outbound

This paper cites URLhttps://par.nsf.gov/biblio/10649160.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity URLhttps://par.nsf.gov/biblio/10649160

Reference 5

Resolution: verified exact; doi, observed 2026-06-29T15:43:32.491447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8f506cf2-f4e3-4b05-aabd-f5363ecb0d8b · outbound

This paper cites URLhttps: //doi.org/10.1214/24-AOS2403.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity URLhttps: //doi.org/10.1214/24-AOS2403

Reference 6

Resolution: verified exact; doi, observed 2026-06-29T15:43:32.493444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8f40bd8a-6de8-4b30-a1f2-b4cc2b82d898 · outbound

This paper cites Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-06-29T15:43:32.838778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6ec4d381-f52d-422d-8754-bc44febf92db · outbound

This paper cites Roman Pogodin, Antonin Schrab, Yazhe Li, Danica J Sutherland, and Arthur Gretton.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Roman Pogodin, Antonin Schrab, Yazhe Li, Danica J Sutherland, and Arthur Gretton

Reference 8

Resolution: verified exact; doi, observed 2026-06-29T15:43:32.489418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e6198f51-6b37-4865-bc42-7e9e9a98aee0 · outbound

This paper cites an unresolved cited work.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 50e9b6e4-89b8-4536-b78a-4fcb69bd9336 · outbound

This paper cites In Section 13, we construct the data-adaptive diagnostic for the trustworthiness of the delta method introduced in Section 3.2.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity In Section 13, we construct the data-adaptive diagnostic for the trustworthiness of the delta method introduced in Section 3.2

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 15b4bc94-c71d-4a7d-aa96-98abad3d4381 · outbound

This paper cites We have EP h eϕX,P (X)⊗eφξ,P (W, Y) i =E P [(φk(X)−E P [φk(X ′)])⊗(φ ξ,P (W, Y)−E P [φξ,P (W ′, Y ′)])] =E P [φk(X)⊗φ ξ,P (W, Y)]−E P [φk(X)]⊗E P [φξ,P (W, Y)].

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity We have EP h eϕX,P (X)⊗eφξ,P (W, Y) i =E P [(φk(X)−E P [φk(X ′)])⊗(φ ξ,P (W, Y)−E P [φξ,P (W ′, Y ′)])] =E P [φk(X)⊗φ ξ,P (W, Y)]−E P [φk(X)]⊗E P [φξ,P (W, Y)]

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation bc8e1782-18dc-4100-869a-fc941b441de8 · outbound

This paper cites an unresolved cited work.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 0a855cbb-7242-4598-98ad-a6b983700c31 · outbound

This paper cites an unresolved cited work.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Unresolved cited work

Reference 13

Resolution: malformed identifier; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 43c98238-c217-4c3a-8475-9e0090a0e3db · outbound

This paper cites an unresolved cited work.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 9ad61349-a866-42f7-98f2-91f371e62f1b · outbound

This paper cites bQV, bQU V-statistic and U-statistic center∥ˇΨn∥2 Hkl and its diagonal-term-free analogue.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity bQV, bQU V-statistic and U-statistic center∥ˇΨn∥2 Hkl and its diagonal-term-free analogue

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation efc8a585-a3ed-4ced-a3c8-d6efbfbba191 · outbound

This paper cites ForΩ n = IdHkl, the confidence set is Cn(ζ) = h∈ H kl :∥ ˇΨn −h∥ 2 Hkl ≤ ζ n.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity ForΩ n = IdHkl, the confidence set is Cn(ζ) = h∈ H kl :∥ ˇΨn −h∥ 2 Hkl ≤ ζ n

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 3b7fd3f6-3a4a-4a88-8892-8e5666a17fb0 · outbound

This paper cites The functional delta method therefore gives √n ∥ ˇΨn∥2 Hkl − ∥Ψ0∥2 Hkl ⇝2⟨Ψ 0,H⟩ Hkl.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity The functional delta method therefore gives √n ∥ ˇΨn∥2 Hkl − ∥Ψ0∥2 Hkl ⇝2⟨Ψ 0,H⟩ Hkl

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 7132eba3-655f-46d4-b455-bd69df8dbec3 · outbound

This paper cites an unresolved cited work.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation d457152a-1fea-42b8-a552-f7e7d4afa439 · outbound

This paper cites Improvements to the underlying raw independence test, such as Schrab et al.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Improvements to the underlying raw independence test, such as Schrab et al

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Unavailable: canonical work link unavailable.

Observation 515843b9-2cb5-4606-9bc9-df4a59e557f5 · outbound

This paper cites (EVD) (measures capacity ofHq) pS|W,σ,RConditional law of the labelSand constants in Eq.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity (EVD) (measures capacity ofHq) pS|W,σ,RConditional law of the labelSand constants in Eq

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Unavailable: canonical work link unavailable.

Observation 9cefd11e-a947-475f-866c-0d6b94c0642c · outbound

This paper cites We first define the embeddingIw : Hq →L 2(PW,0), mapping a functionf∈ H q to its PW,0-equivalence class[ f].

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity We first define the embeddingIw : Hq →L 2(PW,0), mapping a functionf∈ H q to its PW,0-equivalence class[ f]

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation 31f4c18d-5ba0-49dd-bd1a-ba1d0fbfd75e · outbound

This paper cites The α-interpolationspacedefinesaHilbertspace.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity The α-interpolationspacedefinesaHilbertspace

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Observation cf5831f7-aaa3-4432-8547-588484ff0c27 · outbound

This paper cites an unresolved cited work.

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d00fcbd-9b5f-4c45-b9df-e8428d1987ac · outbound

This paper cites The space[G] α is a Hilbert space equipped with the inner product ⟨F, G⟩α :=⟨C, L⟩ S2([Hq]α,Hl) (F, G∈[G] α), whereC=I −1(F), L=I −1(G).

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity The space[G] α is a Hilbert space equipped with the inner product ⟨F, G⟩α :=⟨C, L⟩ S2([Hq]α,Hl) (F, G∈[G] α), whereC=I −1(F), L=I −1(G)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-29T15:34:24.619176Z

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Unavailable: canonical work link unavailable.

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