Conversational Agents

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37 papers in the last four weeks, up 32% on the four weeks before. 0.2% of all new papers.

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Tell Me: An LLM-powered Mental Well-being Assistant with RAG, Synthetic Dialogue Generation, and Agentic Planning
Nov 18, 2025Trishala Jayesh AhalparaMental Health Counseling Mental Health
Fujitsu Research of America Santa Clara, USA
Generative AI Purpose-built for Social and Mental Health: A Real-World Pilot
Nov 12, 2025Thomas D. Hull, Lizhe Zhang, Caitlin A. Stamatis +2Healthcare Mental Health
Slingshot AI · CREATIV Lab, Department of Psychiatry and Behavioral Sciences, University of Washington · Department of Psychiatry, NYU School of Medicine +1
Thinking While Speaking: Inference-Time Knowledge Transfer for Responsive and Intelligent Conversational Voice Agents
Nov 10, 2025Vidya Srinivas, Zachary Englhardt, Vikram Iyer +1Conversational Agents Efficient Language Model Inference
Paul G. Allen School of Computer Science & Engineering
When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue
Oct 22, 2025Tanya Shourya, Yingfan Wang, Zhaoyi Joey Hou +3Tool-Use Evaluation AI Agent Benchmarks
AWS AI Labs · University of Pittsburgh
WaLLM -- Understanding Use and Engagement with a General-Purpose LLM on WhatsApp
May 13, 2025Hiba Eltigani, Rukhshan Haroon, Asli Kocak +3Human-AI Interaction Conversational Agents
Tufts University, USA, Medford
Therapy as an NLP Task: Comparing LLMs and Human Peers Behaviors in CBT Sessions
Sep 3, 2024Zainab Iftikhar, Sean Ransom, Amy Xiao +2Mental Health Counseling Conversational Agents
Brown University, USA · Department of Psychiatry, Louisiana State University Health Sciences, USA · Alpert Medical School of Brown University, Brown University, USA
A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog
Jul 26, 2022Stefan Larson, Kevin LeachIntent Classification Conversational Agents
Department of Computer Science, Vanderbilt University, 1400 18th St. S, Nashville, 37212, TN, USA
Tinker Tales: A Tangible Dialogue System for Child-AI Co-Creative Storytelling
Date pendingNayoung Choi, Jiseung Hong, Peace Cyebukayire +2Interactive Storytelling Conversational Agents
Department of Computer Science, Emory University · Department of Computer Science, Carnegie Mellon University · School of Nursing, Emory University
Some hypotheses on how chatbots work in problem-solution-driven conversations: Large Language Models as confirmation of the Innovation Illusion
Date pendingS. F. M. van Vlijmen, H. D. Lethe jrCognitive Modeling Conversational Agents

Nov 18, 2025J/K move · Enter open · S save

Tell Me: An LLM-powered Mental Well-being Assistant with RAG, Synthetic Dialogue Generation, and Agentic Planning

Trishala Jayesh Ahalpara

Fujitsu Research of America Santa Clara, USA

Mental Health Counseling Mental Health Conversational Agents Text Generation

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We present Tell Me, a mental well-being system that leverages advances in large language models to provide accessible, context-aware support for users and researchers. The system integrates three components: (i) a retrieval-augmented generation (RAG) assistant for personalized, knowledge-grounded dialogue; (ii) a synthetic client-therapist dialogue generator conditioned on client profiles to facilitate research on therapeutic language and data augmentation; and (iii) a Well-being AI crew, implemented with CrewAI, that produces weekly self-care plans and guided meditation audio. The system is designed as a reflective space for emotional processing rather than a substitute for professional therapy. It illustrates how conversational assistants can lower barriers to support, complement existing care, and broaden access to mental health resources. To address the shortage of confidential therapeutic data, we introduce synthetic client-therapist dialogue generation conditioned on client profiles. Finally, the planner demonstrates an innovative agentic workflow for dynamically adaptive, personalized self-care, bridging the limitations of static well-being tools. We describe the architecture, demonstrate its functionalities, and report evaluation of the RAG assistant in curated well-being scenarios using both automatic LLM-based judgments and a human-user study. This work highlights opportunities for interdisciplinary collaboration between NLP researchers and mental health professionals to advance responsible innovation in human-AI interaction for well-being.