7 papers
Graph2Counsel: Clinically Grounded Synthetic Counseling Dialogue Generation from Client Psychological Graphs
Aishik Mandal, Hiba Arnaout, Clarissa W. Ong +5
Rising demand for mental health support has increased interest in using Large Language Models (LLMs) for counseling. However, adapting LLMs to this high-risk safety-critical domain…
MAGneT: Coordinated Multi-Agent Generation of Synthetic Multi-Turn Mental Health Counseling Sessions
Aishik Mandal, Tanmoy Chakraborty, Iryna Gurevych
The growing demand for scalable psychological counseling highlights the need for high-quality, privacy-compliant data, yet such data remains scarce. Here we introduce MAGneT, a nov…
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
Towards Privacy-aware Mental Health AI Models: Advances, Challenges, and Opportunities
Aishik Mandal, Tanmoy Chakraborty, Iryna Gurevych
Mental health disorders create profound personal and societal burdens, yet conventional diagnostics are resource-intensive and limit accessibility. Advances in artificial intellige…
A Comprehensive Review of Datasets for Clinical Mental Health AI Systems
Aishik Mandal, Prottay Kumar Adhikary, Hiba Arnaout +2
Mental health disorders are rising worldwide. However, the availability of trained clinicians has not scaled proportionally, leaving many people without adequate or timely support.…
Enhancing Depression Detection via Question-wise Modality Fusion
Aishik Mandal, Dana Atzil-Slonim, Thamar Solorio +1
Depression is a highly prevalent and disabling condition that incurs substantial personal and societal costs. Current depression diagnosis involves determining the depression sever…