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Paper Citation Record · LEDGER

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models

As of 14 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2606.05169.

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

pith.paper-citation-record.v1
2606.05169 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T20:43:46.574417Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation ca734e5e-95fe-4088-9208-0f7be6def4b5 · outbound

This paper cites Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices

Reference 1

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Observation 25f8a8a0-a9d6-4e7f-a5a3-97c3b1e48f81 · outbound

This paper cites Atomic vibrations in vitreous silica.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Atomic vibrations in vitreous silica

Reference 2

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Observation c4274874-8f9c-4433-b026-49199e774cdc · outbound

This paper cites On a short-coming of saaty's method of analytic hierarchies.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models On a short-coming of saaty's method of analytic hierarchies

Reference 3

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Observation 92482c6d-513c-4612-bdb5-abc48569bebc · outbound

This paper cites Revealing the structure of language model capabilities.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Revealing the structure of language model capabilities

Reference 4

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Observation 552f4880-0463-4327-8b9b-b2f5e65eb06a · outbound

This paper cites Approximation Theory and Harmonic Analysis on Spheres and Balls.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Approximation Theory and Harmonic Analysis on Spheres and Balls

Reference 5

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Observation 7c2ad284-af8e-4196-8608-8b1c6e04d5dc · outbound

This paper cites Submodular meets spectral: greedy algorithms for subset selection, sparse approximation and dictionary selection.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Submodular meets spectral: greedy algorithms for subset selection, sparse approximation and dictionary selection

Reference 6

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Observation 4bf2214d-0948-4684-8444-c5bb1e5297d7 · outbound

This paper cites Moduli of Smoothness.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Moduli of Smoothness

Reference 7

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Observation 8db03edc-9ade-410c-994d-72e6f94108a6 · outbound

This paper cites Remarks on the analytic hierarchy process.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Remarks on the analytic hierarchy process

Reference 8

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Observation b332224d-3af8-4782-951d-0b8ca36e5de2 · outbound

This paper cites A positive answer to the busemann-petty problem in three dimensions.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models A positive answer to the busemann-petty problem in three dimensions

Reference 9

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Observation 3798dce5-3aa0-4e0f-aa79-52ef3f9d77b7 · outbound

This paper cites Geometric Tomography.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Geometric Tomography

Reference 10

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Observation e3bcb6ff-1be0-4432-abc9-97779f1328dc · outbound

This paper cites Geometric Tomography (Second Edition).

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Geometric Tomography (Second Edition)

Reference 11

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Observation a1f41c01-f065-4ad6-b307-9507bc013353 · outbound

This paper cites Optimal rates of convergence for convex set estimation from support functions.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Optimal rates of convergence for convex set estimation from support functions

Reference 12

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Observation c12ec4f6-adb9-4c1f-a46a-997882c335f7 · outbound

This paper cites The theory of ratio scale estimation: Saaty's analytic hierarchy process.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models The theory of ratio scale estimation: Saaty's analytic hierarchy process

Reference 13

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Observation 20753677-634f-4b7b-9a4f-3b2e266f5410 · outbound

This paper cites A rationale and test for the number of factors in factor analysis.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models A rationale and test for the number of factors in factor analysis

Reference 14

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Observation eb9a7002-0021-43a2-8da4-62d179dd6db0 · outbound

This paper cites HypoSpace : underdetermination in enumerable hypothesis spaces, 2025.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models HypoSpace : underdetermination in enumerable hypothesis spaces, 2025

Reference 15

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Observation 29f1a536-e03e-4ef7-aa30-d59a12ea823c · outbound

This paper cites Dynabench : Rethinking benchmarking in NLP.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Dynabench : Rethinking benchmarking in NLP

Reference 16

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Observation 782e4d07-20dd-4b73-bebf-b703a3862bc6 · outbound

This paper cites metabench: A sparse benchmark to measure general ability in large language models.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models metabench: A sparse benchmark to measure general ability in large language models

Reference 17

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Observation f6fd100e-9b3e-40da-a0e6-dea35a5f5b88 · outbound

This paper cites Intersection bodies, positive definite distributions, and the busemann--petty problem.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Intersection bodies, positive definite distributions, and the busemann--petty problem

Reference 18

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Observation e6dbfa72-4153-4d26-9304-a3b16e5bee60 · outbound

This paper cites Near-optimal sensor placements in G aussian processes: theory, efficient algorithms and empirical studies.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Near-optimal sensor placements in G aussian processes: theory, efficient algorithms and empirical studies

Reference 19

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Observation bd97a9df-2182-471f-8c68-0e5458c69535 · outbound

This paper cites Active evaluation acquisition for efficient llm benchmarking.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Active evaluation acquisition for efficient llm benchmarking

Reference 20

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Observation 791161d4-a3ff-4368-9a67-a3adc27c7643 · outbound

This paper cites Intersection bodies and dual mixed volumes.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Intersection bodies and dual mixed volumes

Reference 21

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Observation 79ef9017-2dcf-4494-b98b-fae699af46d6 · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Diameters of compact sets in linear metric spaces

Reference 22

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Observation f9d36f3d-a679-4b8e-b5d0-a52cbc2ac5b2 · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Optimal recovery of operators and multidimensional carlson type inequalities

Reference 23

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Observation cff30fdd-cb51-49dd-9511-1ba967b4b14b · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Distribution of eigenvalues for some sets of random matrices

Reference 24

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Observation 22c045db-90ff-4f29-bbaf-5ff379a0e9c5 · outbound

This paper cites The Random Matrix Theory of the Classical Compact Groups.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models The Random Matrix Theory of the Classical Compact Groups

Reference 25

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Observation fe7cacab-1ffa-4895-9129-681d2d35f00a · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models A survey of optimal recovery

Reference 26

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Observation b8fb6902-c12d-4f4a-9ac7-69f81471bc9a · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models An analysis of approximations for maximizing submodular set functions—i

Reference 27

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Observation 1dae0248-a0a5-4ff0-bcb7-ca1ca5aa97dc · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Efficient multi-prompt evaluation of llms

Reference 28

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Observation f977f1ff-9831-4249-8598-5612b8653b72 · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Projection bodies

Reference 29

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Observation c3cf31a0-8016-4422-af44-3e37c08605f1 · outbound

This paper cites tinybenchmarks: evaluating llms with fewer examples.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models tinybenchmarks: evaluating llms with fewer examples

Reference 30

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Polynomial approximation on compact manifolds and homogeneous spaces

Reference 31

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Observation b78e5120-5ae4-4617-a12e-ee8a87625c50 · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Covering a sphere with spheres

Reference 32

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Inconsistency and rank preservation

Reference 33

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models u ber die projektionen konvexer k \

Reference 34

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Observation f79143ea-ba2b-440c-9ef2-bf1d04780b90 · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models BenchScope : dimensionality and reliability of LLM benchmark suites

Reference 35

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Observation b2fc03f8-9826-462c-af30-de31a633126f · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Information-Based Complexity

Reference 36

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Observation 714792d9-90fe-45b7-b0a0-d149407e179d · outbound

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The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models Inverse participation ratio in 2+ dimensions

Reference 37

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Observation d240ba93-beb0-44c2-826c-893e64bec394 · outbound

This paper cites A positive solution to the busemann-petty problem in R ^4.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models A positive solution to the busemann-petty problem in R ^4

Reference 38

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source=arxiv_source observed=2026-07-12T20:43:46.574417Z digest=sha256:06745640be91a85ebbb82c006e786f409a184a8b1070a7b92960364701598ade

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This paper cites General scales unlock ai evaluation.

The Evaluation Blind Spot: A Stereological Theory of Benchmark Coverage for Large Language Models General scales unlock ai evaluation

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