Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2502.00678.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:35:11.856700Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T20:57:23.351502Z
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 5730a9c4-46ad-4ad3-b5e8-92b0d06bd75d · inbound
Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks cites this paper.
Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:35:11.856700Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de39f1bc-94b6-4e53-b903-ba3bd58af580 · inbound
The Economics of AI Training Data: A Research Agenda cites this paper.
The Economics of AI Training Data: A Research Agenda How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T07:40:11.897460Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8d26c43a-aedc-4344-8d11-af3667d41ce5 · inbound
When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors cites this paper.
When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:16:18.222490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a86d04d6-a9a5-46c5-93c1-0cab8b5a3bee · inbound
Beyond Goodhart's Law: A Dynamic Benchmark for Evaluating Compliance in Multi-Agent Systems cites this paper.
Beyond Goodhart's Law: A Dynamic Benchmark for Evaluating Compliance in Multi-Agent Systems How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T17:47:17.785130Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 115f0cf7-4813-46ac-9c84-79ba0c1a5787 · inbound
MC-PDD: Masked Corpus-Level Pretraining Data Detection for Black-Box Large Language Models cites this paper.
MC-PDD: Masked Corpus-Level Pretraining Data Detection for Black-Box Large Language Models How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T20:57:23.353100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.