Poster: Phase-Based Latency Mitigation in LLM-Driven VR Agents

Response latency in Large Language Model (LLM)–driven Embodied Conversational Agents (ECAs) can disrupt conversational flow. We investigated whether phase-specific multimodal feedback can mitigate perceived waiting time without modifying the underlying dialogue pipeline. In a within-subjects study (n = 35), participants experienced feedback during user speech (USP), the response-waiting phase (RWP), both phases, or neither phase. Results showed that RWP feedback consistently reduced perceived latency, whereas USP-only feedback showed weaker and partly distracting effects, while perceived social qualities remained unaffected in all conditions. This highlights the importance of temporally aligned feedback for improving perceived responsiveness.