Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Evaluating General-Purpose AI with Psychometrics
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.16379.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:12:55.204761Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z
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 fba9a1d0-413e-4320-abf7-c05e07483ebd · inbound
Evaluating Generative AI Systems is a Social Science Measurement Challenge cites this paper.
Evaluating Generative AI Systems is a Social Science Measurement Challenge Evaluating General-Purpose AI with Psychometrics
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:12:55.204761Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 98797b12-7942-4d4c-bfed-81d607f38ec6 · inbound
Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge cites this paper.
Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge Evaluating General-Purpose AI with Psychometrics
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T18:37:35.029933Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1d38910-3952-4dfd-84dc-462de215e527 · inbound
Designing Psychometric Bias Measures for ChatBots: An Application to Racial Bias Measurement cites this paper.
Designing Psychometric Bias Measures for ChatBots: An Application to Racial Bias Measurement Evaluating General-Purpose AI with Psychometrics
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T22:12:51.786287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 515af0c0-b732-4be7-96a5-eec0cab864cf · inbound
Position: AI Evaluations Should be Grounded on a Theory of Capability cites this paper.
Position: AI Evaluations Should be Grounded on a Theory of Capability Evaluating General-Purpose AI with Psychometrics
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T22:00:41.493712Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 093ce730-eafa-4d22-899e-7b1cfae8c464 · inbound
FairTree: Subgroup Fairness Auditing of Machine Learning Models with Bias-Variance Decomposition cites this paper.
FairTree: Subgroup Fairness Auditing of Machine Learning Models with Bias-Variance Decomposition Evaluating General-Purpose AI with Psychometrics
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:31:03.890165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cb9f0246-af48-4666-8530-fa961aa366e1 · inbound
An Interpretable and Scalable Framework for Evaluating Large Language Models cites this paper.
An Interpretable and Scalable Framework for Evaluating Large Language Models Evaluating General-Purpose AI with Psychometrics
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T04:41:01.552357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2798aa96-e4a3-4980-876b-b9eedfcf66b7 · inbound
Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts cites this paper.
Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts Evaluating General-Purpose AI with Psychometrics
Reference 79
- Resolution
- verified exact
- arxiv_id, observed 2026-06-26T12:29:28.245534Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.