Stark: Social Long-Term Multi-Modal Conversation with Persona
  Commonsense Knowledge
Authors: name: Young-Jun Lee, name: Dokyong Lee, name: Junyoung Youn, name: Kyeongjin Oh, name: Byungsoo Ko, name: Jonghwan Hyeon, name: Ho-Jin Choi

Humans share a wide variety of images related to their personal experiences
within conversations via instant messaging tools. However, existing works focus
on (1) image-sharing behavior in singular sessions, leading to limited
long-term social interaction, and (2) a lack of personalized image-sharing
behavior. In this work, we introduce Stark, a large-scale long-term multi-modal
conversation dataset that covers a wide range of social personas in a
multi-modality format, time intervals, and images. To construct Stark
automatically, we propose a novel multi-modal contextualization framework, Mcu,
that generates long-term multi-modal dialogue distilled from ChatGPT and our
proposed Plan-and-Execute image aligner. Using our Stark, we train a
multi-modal conversation model, Ultron 7B, which demonstrates impressive visual
imagination ability. Furthermore, we demonstrate the effectiveness of our
dataset in human evaluation. We make our source code and dataset publicly
available.