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20242026
most citedLarge Language Models in Mental Health Care: a Scoping Review

37 citations · 52 across the 17 of their papers we have counts for

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Showing 2024 · cs.CLShow all

6 papers · 2 filters

cs.CL2024

Detecting Conversational Mental Manipulation with Intent-Aware Prompting

Jiayuan Ma, Hongbin Na, Zimu Wang +4

Mental manipulation severely undermines mental wellness by covertly and negatively distorting decision-making. While there is an increasing interest in mental health care within th…

cs.CL2024

Guardians of Discourse: Evaluating LLMs on Multilingual Offensive Language Detection

Jianfei He, Lilin Wang, Jiaying Wang +5

Identifying offensive language is essential for maintaining safety and sustainability in the social media era. Though large language models (LLMs) have demonstrated encouraging pot…

cs.CL2024

Multi-Session Client-Centered Treatment Outcome Evaluation in Psychotherapy

Hongbin Na, Tao Shen, Shumao Yu +1

In psychotherapy, therapeutic outcome assessment, or treatment outcome evaluation, is essential to mental health care by systematically evaluating therapeutic processes and outcome…

cs.CL2024★ 6 cited

CBT-LLM: A Chinese Large Language Model for Cognitive Behavioral Therapy-based Mental Health Question Answering

Hongbin Na

The recent advancements in artificial intelligence highlight the potential of language models in psychological health support. While models trained on data from mental health servi…

cs.CL2024

Thinker-DDM: Modeling Deliberation for Machine Translation with a Drift-Diffusion Process

Hongbin Na, Zimu Wang, Mieradilijiang Maimaiti +4

Large language models (LLMs) have demonstrated promising potential in various downstream tasks, including machine translation. However, prior work on LLM-based machine translation…

cs.CL2024★ 37 cited

Large Language Models in Mental Health Care: a Scoping Review

Yining Hua, Fenglin Liu, Kailai Yang +9

Objectieve:This review aims to deliver a comprehensive analysis of Large Language Models (LLMs) utilization in mental health care, evaluating their effectiveness, identifying chall…