Paper Citation Record · LEDGER

Accounting for Variance in Machine Learning Benchmarks

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2103.03098.

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

pith.paper-citation-record.v1
2103.03098 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T02:42:55.488694Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:39:58.508622Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fc3391f6-c76f-4669-ac5b-9f77a4a832b5 · inbound

QuickScope: Certifying Hard Questions in Dynamic LLM Benchmarks cites this paper.

QuickScope: Certifying Hard Questions in Dynamic LLM Benchmarks Accounting for Variance in Machine Learning Benchmarks

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:56:29.644687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 125fbc8a-b8eb-47b1-a456-c1f0ed959364 · inbound

SafetyRepro: Configuration-Conditional Rank Instability on Alignment Benchmarks cites this paper.

SafetyRepro: Configuration-Conditional Rank Instability on Alignment Benchmarks Accounting for Variance in Machine Learning Benchmarks

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T22:54:01.011913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 62093066-090e-4af8-ae41-0f36bc1f6d6d · inbound

A Pre-Registered Causal Partition of Self-Consistency Elicitation and Reward Design in RLVR cites this paper.

A Pre-Registered Causal Partition of Self-Consistency Elicitation and Reward Design in RLVR Accounting for Variance in Machine Learning Benchmarks

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:06:59.087174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 182831b8-0846-464d-b9d8-3d90703284e6 · inbound

From Forecasting Leaderboards to Deployment Decisions: A Fail-Closed Certification Protocol cites this paper.

From Forecasting Leaderboards to Deployment Decisions: A Fail-Closed Certification Protocol Accounting for Variance in Machine Learning Benchmarks

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:39:58.510193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4642e8ac-6ba4-4372-8407-365155d4dbfc · inbound

Grokking Is Conditional and Fragile: A Fully-Tractable, Multi-Seed Study at 12K Parameters cites this paper.

Grokking Is Conditional and Fragile: A Fully-Tractable, Multi-Seed Study at 12K Parameters Accounting for Variance in Machine Learning Benchmarks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-11T08:46:29.099447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c1ddb2a-92ad-48d5-b45e-f03794fd0fb0 · inbound

SketchMamba: A Lightweight State-Space Model for Joint Progressive Sketch Classification and Stroke Auto-Completion cites this paper.

SketchMamba: A Lightweight State-Space Model for Joint Progressive Sketch Classification and Stroke Auto-Completion Accounting for Variance in Machine Learning Benchmarks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-30T18:22:25.866849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e517e830-bdc9-496e-96ce-a89bcbc70208 · inbound

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines cites this paper.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Accounting for Variance in Machine Learning Benchmarks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.488694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.