Reasoning Is Not All You Need: Examining LLMs for Multi-Turn Mental Health Conversations

Jul 1, 2026·
Mohit Chandra
,
Siddharth Sriraman
,
Harneet Singh Khanuja
Yiqiao Jin
Yiqiao Jin
,
Munmun De Choudhury
· 1 min read
Abstract
Mental health support over multi-turn conversations stresses LLM reasoning, empathy, and safety in distinct ways. We systematically examine the limits of reasoning-focused LLMs in multi-turn mental health conversations, isolating failure modes that pure reasoning cannot address, and discuss design implications for responsible deployment. ACL 2026 acceptance rate: 19.0%.
Type
Publication
Annual Meeting of the Association for Computational Linguistics (ACL) 2026, Main Conference

Abstract

Mental health support over multi-turn conversations stresses LLM reasoning, empathy, and safety in distinct ways. We systematically examine the limits of reasoning-focused LLMs in multi-turn mental health conversations, isolating failure modes that pure reasoning cannot address.

Yiqiao Jin
Authors
Final-year Ph.D. Candidate in Computer Science
My research sits at the intersection of multimodal foundation models, intelligent agents, and spatial/physical intelligence. I build general-purpose models that perceive, reason, learn, and act in interactive virtual and physical environments.