Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2406.00092.
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 2026-08-07T14:44:34.321674Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T12:56:57.224899Z
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 bfe699db-0139-4b2d-8495-78866bd4dc75 · inbound
CapBencher: Give Your LLM Benchmark a Built-in Alarm for Test-Set Overfitting cites this paper.
CapBencher: Give Your LLM Benchmark a Built-in Alarm for Test-Set Overfitting How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:44:34.321674Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae67e2b6-d109-4b0c-9785-b8766395eea3 · inbound
B-score: Detecting biases in large language models using response history cites this paper.
B-score: Detecting biases in large language models using response history How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:33:48.892989Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d620471b-6b3e-4f56-8c79-5cc6f03caf19 · inbound
Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling cites this paper.
Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T09:27:14.828197Z
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 d269a2e2-3670-42ea-baac-e9fb0a5e34c5 · inbound
In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models cites this paper.
In Search of the Ingredients of Open-Endedness: Replicating Picbreeder with Large Vision-Language Models How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T15:09:20.426018Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f626a6c7-156d-43ee-b5d8-613f86a32f9a · inbound
FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences cites this paper.
FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
Reference 37
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T01:56:27.928520Z
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 2d40b2f6-998b-4f4f-9d17-3a6b723eeaf2 · inbound
UnpredictaBench: A Benchmark for Evaluating Distributional Randomness in LLMs cites this paper.
UnpredictaBench: A Benchmark for Evaluating Distributional Randomness in LLMs How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T12:56:57.226416Z
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 7e160766-a204-4e92-b88a-d49ea938f7e5 · inbound
One Token Is Enough: Fingerprinting and Verifying Large Language Models from Single-Token Output Distributions cites this paper.
One Token Is Enough: Fingerprinting and Verifying Large Language Models from Single-Token Output Distributions How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T13:10:47.045131Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.