37 citations · 52 across the 17 of their papers we have counts for
9 papers · 1 filter
MineAgent: Towards Remote-Sensing Mineral Exploration with Multimodal Large Language Models
Beibei Yu, Tao Shen, Hongbin Na +2
Remote-sensing mineral exploration is critical for identifying economically viable mineral deposits, yet it poses significant challenges for multimodal large language models (MLLMs…
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…
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…
Hazards in Daily Life? Enabling Robots to Proactively Detect and Resolve Anomalies
Zirui Song, Guangxian Ouyang, Meng Fang +9
Existing household robots have made significant progress in performing routine tasks, such as cleaning floors or delivering objects. However, a key limitation of these robots is th…
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…
Applying and Evaluating Large Language Models in Mental Health Care: A Scoping Review of Human-Assessed Generative Tasks
Yining Hua, Hongbin Na, Zehan Li +4
Large language models (LLMs) are emerging as promising tools for mental health care, offering scalable support through their ability to generate human-like responses. However, the…
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…
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…
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…