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 2representative citing papers
Frozen multimodal embeddings with trait-specific late fusion cut personality prediction MSE by 19% relative to baseline in the 2026 AVI challenge, while cognitive results are attributed to validation shortcuts rather than content-based inference.
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.
-
Frozen Multimodal Embeddings for AI-Assisted Interview Assessment of Personality and Cognitive Ability
Frozen multimodal embeddings with trait-specific late fusion cut personality prediction MSE by 19% relative to baseline in the 2026 AVI challenge, while cognitive results are attributed to validation shortcuts rather than content-based inference.