Egocentric Memory Enhanced Mixed-Session Conversation Agent (EMMA)

Introduction

EMMA is a new conversation model designed for mixed-session conversations, incorporating Egocentric Memory trained on the MiSC dataset. This model focuses on handling dynamic interactions across sessions, where a main speaker engages with different partners.

🚨 This repository is for the adapter of EMMA's dialogue module, which is based on FLAN-T5-Large.

Model Description

• Paper: Mixed-Session Conversation with Egocentric Memory
• Dataset: MiSC
• Code: GitHub

Citation Information

If you use EMMA in your research, please cite the following paper:

@article{jang2024mixed,
  title={Mixed-Session Conversation with Egocentric Memory},
  author={Jang, Jihyoung and Kim, Taeyoung and Kim, Hyounghun},
  journal={arXiv preprint arXiv:2410.02503},
  year={2024}
}