Persona-Guided LLM Agents for Task-Oriented Dialogue
Balancing personality and performance in task-oriented LLM dialogue agents.
Prior work has shown that large language models (LLMs) can express diverse personality traits in open-ended text generation. However, it remains unclear whether they can do so in a goal-directed dialogue without compromising task completion, and whether adapting to the user's per...
ArXiv CS.CL
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This research reveals that LLMs can balance distinct personality expressions with operational efficiency in task-oriented roles without requiring expensive fine-tuning. It highlights a critical tension between user-centric personalization and factual grounding, suggesting that cue-based inference is the most robust path forward for naturalistic AI interactions.
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