Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive Principles
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.12644.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:59:55.734120Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T05:57:41.350120Z
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 ca7ff6da-26b8-4be8-b4bd-6873e3b2a77b · inbound
Pedestrian Intention Prediction via Vision-Language Foundation Models cites this paper.
Pedestrian Intention Prediction via Vision-Language Foundation Models Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive Principles
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:59:55.734120Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ea3dbb9-4922-485d-9e12-17949d2cad4a · inbound
Mechanistic Interpretability of Cognitive Complexity in LLMs via Linear Probing using Bloom's Taxonomy cites this paper.
Mechanistic Interpretability of Cognitive Complexity in LLMs via Linear Probing using Bloom's Taxonomy Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive Principles
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T22:20:51.929555Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b52fefc-4380-4474-86b1-ad9e3c1d7608 · inbound
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes cites this paper.
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive Principles
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:57:41.351677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.