Publications (15)
A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directions
Hongbin Na, Yining Hua, Zimu Wang +6
Mental health is increasingly critical in contemporary healthcare, with psychotherapy demanding dynamic, context-sensitive interactions that traditional NLP methods struggle to cap…
Lost in Pronunciation: Detecting Chinese Offensive Language Disguised by Phonetic Cloaking Replacement
Haotan Guo, Jianfei He, Jiayuan Ma +8
Phonetic Cloaking Replacement (PCR), defined as the deliberate use of homophonic or near-homophonic variants to hide toxic intent, has become a major obstacle to Chinese content mo…
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…
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…
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…
CARE-Bench: Benchmarking Patient-Facing LLM Triage
Yining Hua, Hongbin Na, Cyrus Ayubcha
Patient-facing medical LLMs and agents increasingly answer symptom questions before clinician contact, where the key safety question is what action the user should take next. We in…
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…
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…
Design and Report Benchmarks for Knowledge Work
Yining Hua, Hongbin Na, Cyrus Ayubcha +1
The development of LLM agents has led to a growing body of work on knowledge-work AI, including coding, research, and healthcare. However, current knowledge-work evaluation and ben…
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…
Overview of the PsyDefDetect Shared Task at BioNLP 2026: Detecting Levels of Psychological Defense Mechanisms in Supportive Conversations
Hongbin Na, Zimu Wang, Zhaoming Chen +8
We present an overview of PsyDefDetect, the shared task on detecting levels of psychological defense mechanisms in emotional support dialogues, co-located with BioNLP@ACL 2026. Gro…
You Never Know a Person, You Only Know Their Defenses: Detecting Levels of Psychological Defense Mechanisms in Supportive Conversations
Hongbin Na, Zimu Wang, Zhaoming Chen +9
Psychological defenses are strategies, often automatic, that people use to manage distress. Rigid or overuse of defenses is negatively linked to mental health and shapes what speak…
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…
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…
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…