6 papers
Measuring What Matters!! Assessing Therapeutic Principles in Mental-Health Conversation
Abdullah Mazhar, Het Riteshkumar Shah, Aseem Srivastava +2
The increasing use of large language models in mental health applications calls for principled evaluation frameworks that assess alignment with psychotherapeutic best practices bey…
Redefining Experts: Interpretable Decomposition of Language Models for Toxicity Mitigation
Zuhair Hasan Shaik, Abdullah Mazhar, Aseem Srivastava +1
Large Language Models have demonstrated impressive fluency across diverse tasks, yet their tendency to produce toxic content remains a critical challenge for AI safety and public t…
Assess and Prompt: A Generative RL Framework for Improving Engagement in Online Mental Health Communities
Bhagesh Gaur, Karan Gupta, Aseem Srivastava +2
Online Mental Health Communities (OMHCs) provide crucial peer and expert support, yet many posts remain unanswered due to missing support attributes that signal the need for help.…
Figurative-cum-Commonsense Knowledge Infusion for Multimodal Mental Health Meme Classification
Abdullah Mazhar, Zuhair hasan shaik, Aseem Srivastava +5
The expression of mental health symptoms through non-traditional means, such as memes, has gained remarkable attention over the past few years, with users often highlighting their…
Sentiment-guided Commonsense-aware Response Generation for Mental Health Counseling
Aseem Srivastava, Gauri Naik, Alison Cerezo +2
The crisis of mental health issues is escalating. Effective counseling serves as a critical lifeline for individuals suffering from conditions like PTSD, stress, etc. Therapists fo…
Trust Modeling in Counseling Conversations: A Benchmark Study
Aseem Srivastava, Zuhair Hasan Shaik, Tanmoy Chakraborty +1
In mental health counseling, a variety of earlier studies have focused on dialogue modeling. However, most of these studies give limited to no emphasis on the quality of interactio…