66 citations · 107 across the 7 of their papers we have counts for
7 papers
"ChatGPT, Don't Tell Me What to Do": Designing AI for Context Analysis in Humanitarian Frontline Negotiations
ZIlin Ma, Yiyang Mei, Claude Bruderlein +2
Frontline humanitarian negotiators are increasingly exploring ways to use AI tools in their workflows. However, current AI-tools in negotiation primarily focus on outcomes, neglect…
Learning Interpretable Fair Representations
Tianhao Wang, Zana Buçinca, Zilin Ma
Numerous approaches have been recently proposed for learning fair representations that mitigate unfair outcomes in prediction tasks. A key motivation for these methods is that the…
Using Large Language Models for Humanitarian Frontline Negotiation: Opportunities and Considerations
Zilin Ma, Susannah, Su +14
Humanitarian negotiations in conflict zones, called \emph{frontline negotiation}, are often highly adversarial, complex, and high-risk. Several best-practices have emerged over the…
AffirmativeAI: Towards LGBTQ+ Friendly Audit Frameworks for Large Language Models
Yinru Long, Zilin Ma, Yiyang Mei +1
LGBTQ+ community face disproportionate mental health challenges, including higher rates of depression, anxiety, and suicidal ideation. Research has shown that LGBTQ+ people have be…
Speech as Interactive Design Material (SIDM): How to design and evaluate task-tailored synthetic voices?
Mateusz Dubiel, Matthew Aylett, Anuschka Schmitt +3
The aim of this workshop is two-fold. First, it aims to establish a research community focused on design and evaluation of synthetic speech (TTS) interfaces that are tailored not o…
Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support
Zilin Ma, Yiyang Mei, Yinru Long +2
LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether the…
Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Support
Zilin Ma, Yiyang Mei, Zhaoyuan Su
Conversational agents powered by large language models (LLM) have increasingly been utilized in the realm of mental well-being support. However, the implications and outcomes assoc…