Medium personality expression in LLM agents yields the most positive user perceptions in goal-oriented tasks, further improved by trait alignment.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.HC 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
Motion-based user identification works reliably inside one XR application but generalizes poorly across different applications.
citing papers explorer
-
Vibe Check: Understanding the Effects of LLM-Based Conversational Agents' Personality and Alignment on User Perceptions in Goal-Oriented Tasks
Medium personality expression in LLM agents yields the most positive user perceptions in goal-oriented tasks, further improved by trait alignment.
-
Motion-Based User Identification across XR and Metaverse Applications by Deep Classification and Similarity Learning
Motion-based user identification works reliably inside one XR application but generalizes poorly across different applications.