Co-design of LLM-based preference agents: participation may drive overtrust
arXiv 2607.21757•d324b8ae2cbf3d05bc6c410251094389de6aea106671652af569aec52699b04d
accessibilityagentic-systemsai-governanceartificial-intelligencecopyright-compliancedeployment-configurationeu-ai-acthuman-ai-interactionlarge-language-modelsllm-safetymodel-reliabilityopaque-updatesovertrustprompt-sensitivitypsychological-dependencyregulatory-compliancerequirements-engineeringtime-pressure
Paper metadata
- arXiv ID
- 2607.21757
- Version
- Not specified by this published record
- Category
- Computer Science — Computers and Society (cs.CY)
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Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- d324b8ae2cbf3d05bc6c410251094389de6aea106671652af569aec52699b04d
- Enrichment time
- 2026-07-27T07:23:45Z
- AI-assisted enrichment
- Yes
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