arXiv Artificial Intelligence

Competence-Preserving Resume Perturbations Expose Presentation Sensitivity in LLM Screening

1 hour ago 16.09.2026 07:00 👁 1 views
Competence-Preserving Resume Perturbations Expose Presentation Sensitivity in LLM Screening

Quick summary

arXiv:2609.16517v1 Announce Type: cross Abstract: Resume screeners must infer job-relevant competence from resumes whose presentation can vary substantially in wording, structure, stylistic polish, and document extraction quality. Ideally, such surface variation should not change decisions when the underlying qualification evidence is unchanged. We introduce a controlled audit of this property, constructing occupation-grounded candidate profiles at controlled competence levels and rendering each profile into multiple resume presentations. A deterministic validation gate excludes variants that

Key takeaways

  • arXiv:2609.16517v1 Announce Type: cross Abstract: Resume screeners must infer job-relevant competence from resumes whose presentation can vary substantially in wording, structure, stylistic polish, and document extraction quality.
  • Ideally, such surface variation should not change decisions when the underlying qualification evidence is unchanged.
  • We introduce a controlled audit of this property, constructing occupation-grounded candidate profiles at controlled competence levels and rendering each profile into multiple resume presentations.

Why it matters

“Competence-Preserving Resume Perturbations Expose Presentation Sensitivity in LLM Screening” illustrates how changes in the AI ecosystem can affect products, workflows and user expectations together. Its lasting significance depends on measurable adoption, cost and safety outcomes.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗