SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations
<|reference_start|>SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations: In today's globalized world, bridging the cultural divide is more critical than ever for forging meaningful connections. The Socially-Aware Dialogue Assistant System (SADAS) is our answer to this global challenge, and it's designed to ensure that conversations between individuals from diverse cultural backgrounds unfold with respect and understanding. Our system's novel architecture includes: (1) identifying the categories of norms present in the dialogue, (2) detecting potential norm violations, (3) evaluating the severity of these violations, (4) implementing targeted remedies to rectify the breaches, and (5) articulates the rationale behind these corrective actions. We employ a series of State-Of-The-Art (SOTA) techniques to build different modules, and conduct numerous experiments to select the most suitable backbone model for each of the modules. We also design a human preference experiment to validate the overall performance of the system. We will open-source our system (including source code, tools and applications), hoping to advance future research. A demo video of our system can be found at:~\url{https://youtu.be/JqetWkfsejk}. We have released our code and software at:~\url{https://github.com/AnonymousEACLDemo/SADAS}.<|reference_end|>
@article{hua2024sadas:,
    title={SADAS: A Dialogue Assistant System Towards Remediating Norm Violations
  in Bilingual Socio-Cultural Conversations},
    author={Yuncheng Hua, Zhuang Li, Linhao Luo, Kadek Ananta Satriadi, Tao Feng,
  Haolan Zhan, Lizhen Qu, Suraj Sharma, Ingrid Zukerman, Zhaleh Semnani-Azad
  and Gholamreza Haffari},
    journal={arXiv preprint arXiv:2402.01736},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.01736},
    primaryClass={cs.CL cs.AI}
}