Measuring Behavioural Signatures of Large Language Models through Psychometric Profiling
Quick summary
arXiv:2609.22934v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate human decisions and communication, yet their behavioural regularities remain difficult to characterize systematically. We develop a cross-linguistic psychometric profiling framework and evaluate nine LLMs using seven psychological instruments, with five repeated administrations per model and language in Chinese and English. Items unresolved after a prespecified retry procedure are retained as NA. Joint analysis of scored and NA responses captures response tendencies and boundaries of self-report
Key takeaways
- arXiv:2609.22934v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate human decisions and communication, yet their behavioural regularities remain difficult to characterize systematically.
- We develop a cross-linguistic psychometric profiling framework and evaluate nine LLMs using seven psychological instruments, with five repeated administrations per model and language in Chinese and English.
- Items unresolved after a prespecified retry procedure are retained as NA.
Why it matters
“Measuring Behavioural Signatures of Large Language Models through Psychometric Profiling” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.
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