# Livia: An Emotion-Aware AR Companion Powered by Modular AI Agents and Progressive Memory Compression

arXiv: https://arxiv.org/abs/2509.05298 · HTML: https://mlsanity.com/paper/2509.05298/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 13 references that are in the map.
- First posted on arXiv 12 Aug 2025.

## Builds on (most cited first, 4 of 4)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory](https://mlsanity.com/paper/1704.01074/) (2017)
- [Diversity and Inclusion in Artificial Intelligence](https://mlsanity.com/paper/2305.12728/) (2023)
- [Interpersonal Memory Matters: A New Task for Proactive Dialogue Utilizing Conversational History](https://mlsanity.com/paper/2503.05150/) (2025)

## Built on by (most cited first, 1 of 1)

- [Memory in the Age of AI Agents](https://mlsanity.com/paper/2512.13564/) (2025)

## Abstract (arXiv)

Loneliness and social isolation pose significant emotional and health challenges, prompting the development of technology-based solutions for companionship and emotional support. This paper introduces Livia, an emotion-aware augmented reality (AR) companion app designed to provide personalized emotional support by combining modular artificial intelligence (AI) agents, multimodal affective computing, progressive memory compression, and AR driven embodied interaction. Livia employs a modular AI architecture with specialized agents responsible for emotion analysis, dialogue generation, memory management, and behavioral orchestration, ensuring robust and adaptive interactions. Two novel algorithms-Temporal Binary Compression (TBC) and Dynamic Importance Memory Filter (DIMF)-effectively manage and prioritize long-term memory, significantly reducing storage requirements while retaining critical context. Our multimodal emotion detection approach achieves high accuracy, enhancing proactive and empathetic engagement. User evaluations demonstrated increased emotional bonds, improved satisfaction, and statistically significant reductions in loneliness. Users particularly valued Livia's adaptive personality evolution and realistic AR embodiment. Future research directions include expanding gesture and tactile interactions, supporting multi-user experiences, and exploring customized hardware implementations.