7 papers
Evaluating Document-Tuned Transformer Representations for Person-level Mental Health Assessment
Aaron Marker, Oscar Kjell, Vasudha Varadarajan +1
Person-level psychological assessment requires aggregating meaning across many messages from the same individual, a task that document-level training objectives were not explicitly…
MAQuA: Adaptive Question-Asking for Multidimensional Mental Health Screening using Item Response Theory
Vasudha Varadarajan, Hui Xu, Rebecca Astrid Boehme +3
Recent advances in large language models (LLMs) offer new opportunities for scalable, interactive mental health assessment, but excessive querying by LLMs burdens users and is inef…
Explaining GPTs' Schema of Depression: A Machine Behavior Analysis
Adithya V Ganesan, Vasudha Varadarajan, Yash Kumar Lal +9
Use of large language models such as ChatGPT (GPT-4/GPT-5) for mental health support has grown rapidly, emerging as a promising route to assess and help people with mood disorders…
Unifying the Extremes: Developing a Unified Model for Detecting and Predicting Extremist Traits and Radicalization
Allison Lahnala, Vasudha Varadarajan, Lucie Flek +2
The proliferation of ideological movements into extremist factions via social media has become a global concern. While radicalization has been studied extensively within the contex…
WhiSPA: Semantically and Psychologically Aligned Whisper with Self-Supervised Contrastive and Student-Teacher Learning
Rajath Rao, Adithya Ganesan, Oscar Kjell +10
Current speech encoding pipelines often rely on an additional text-based LM to get robust representations of human communication, even though SotA speech-to-text models often have…
Capturing Human Cognitive Styles with Language: Towards an Experimental Evaluation Paradigm
Vasudha Varadarajan, Syeda Mahwish, Xiaoran Liu +4
While NLP models often seek to capture cognitive states via language, the validity of predicted states is determined by comparing them to annotations created without access the cog…