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The critical field of psychology necessitates a comprehensive benchmark to enhance the evaluation and development of domain-specific Large Language Models (LLMs). Existing MMLU-type benchmarks, such as C-EVAL and CMMLU, include…

Computation and Language · Computer Science 2024-06-18 Junlei Zhang , Hongliang He , Nirui Song , Zhanchao Zhou , Shuyuan He , Shuai Zhang , Huachuan Qiu , Anqi Li , Yong Dai , Lizhi Ma , Zhenzhong Lan

Using large language models (LLMs) to assist psychological counseling is a significant but challenging task at present. Attempts have been made on improving empathetic conversations or acting as effective assistants in the treatment with…

Computation and Language · Computer Science 2024-06-11 Chenhao Zhang , Renhao Li , Minghuan Tan , Min Yang , Jingwei Zhu , Di Yang , Jiahao Zhao , Guancheng Ye , Chengming Li , Xiping Hu

Mental health has attracted substantial attention in recent years and LLM can be an effective technology for alleviating this problem owing to its capability in text understanding and dialogue. However, existing research in this domain…

Computation and Language · Computer Science 2024-12-09 Jinpeng Hu , Tengteng Dong , Luo Gang , Hui Ma , Peng Zou , Xiao Sun , Dan Guo , Xun Yang , Meng Wang

As the capabilities of large language models (LLMs) continue to advance, evaluating their performance becomes increasingly crucial and challenging. This paper aims to bridge this gap by introducing CMMLU, a comprehensive Chinese benchmark…

Computation and Language · Computer Science 2024-01-19 Haonan Li , Yixuan Zhang , Fajri Koto , Yifei Yang , Hai Zhao , Yeyun Gong , Nan Duan , Timothy Baldwin

With the rapid development of large language models (LLMs), assessing their performance on health-related inquiries has become increasingly essential. The use of these models in real-world contexts-where misinformation can lead to serious…

Computation and Language · Computer Science 2025-02-24 Chenlu Guo , Nuo Xu , Yi Chang , Yuan Wu

Large Language Models (LLMs) have demonstrated significant potential and effectiveness across multiple application domains. To assess the performance of mainstream LLMs in public security tasks, this study aims to construct a specialized…

Artificial Intelligence · Computer Science 2024-03-22 Xin Tong , Bo Jin , Zhi Lin , Binjun Wang , Ting Yu , Qiang Cheng

Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address…

Computation and Language · Computer Science 2023-10-24 Junling Liu , Peilin Zhou , Yining Hua , Dading Chong , Zhongyu Tian , Andrew Liu , Helin Wang , Chenyu You , Zhenhua Guo , Lei Zhu , Michael Lingzhi Li

Large language models (LLMs) offer significant potential in enhancing psychiatric practice, from improving diagnostic accuracy to streamlining clinical documentation and therapeutic support. However, existing evaluation resources heavily…

Computation and Language · Computer Science 2025-11-25 Aya E. Fouda , Abdelrahamn A. Hassan , Radwa J. Hanafy , Mohammed E. Fouda

With the proliferation of Large Language Models (LLMs) in diverse domains, there is a particular need for unified evaluation standards in clinical medical scenarios, where models need to be examined very thoroughly. We present CliMedBench,…

Computation and Language · Computer Science 2024-10-07 Zetian Ouyang , Yishuai Qiu , Linlin Wang , Gerard de Melo , Ya Zhang , Yanfeng Wang , Liang He

Online education platforms have significantly transformed the dissemination of educational resources by providing a dynamic and digital infrastructure. With the further enhancement of this transformation, the advent of Large Language Models…

Artificial Intelligence · Computer Science 2024-09-26 Qian-Wen Zhang , Haochen Wang , Fang Li , Siyu An , Lingfeng Qiao , Liangcai Gao , Di Yin , Xing Sun

The emergence of various medical large language models (LLMs) in the medical domain has highlighted the need for unified evaluation standards, as manual evaluation of LLMs proves to be time-consuming and labor-intensive. To address this…

Computation and Language · Computer Science 2023-12-21 Yan Cai , Linlin Wang , Ye Wang , Gerard de Melo , Ya Zhang , Yanfeng Wang , Liang He

In light of recent breakthroughs in large language models (LLMs) that have revolutionized natural language processing (NLP), there is an urgent need for new benchmarks to keep pace with the fast development of LLMs. In this paper, we…

Computation and Language · Computer Science 2024-05-20 Jie Zhu , Junhui Li , Yalong Wen , Lifan Guo

Amidst a shortage of qualified mental health professionals, the integration of large language models (LLMs) into psychological applications offers a promising way to alleviate the growing burden of mental health disorders. Recent…

Computation and Language · Computer Science 2025-08-25 Chongyuan Dai , Jinpeng Hu , Hongchang Shi , Zhuo Li , Xun Yang , Meng Wang

Large language models (LLMs) have made significant progress in natural language processing tasks and demonstrate considerable potential in the legal domain. However, legal applications demand high standards of accuracy, reliability, and…

Computation and Language · Computer Science 2024-11-27 Haitao Li , You Chen , Qingyao Ai , Yueyue Wu , Ruizhe Zhang , Yiqun Liu

Evaluating the safety alignment of LLM responses in high-risk mental health dialogues is particularly difficult due to missing gold-standard answers and the ethically sensitive nature of these interactions. To address this challenge, we…

Computation and Language · Computer Science 2026-02-16 Yunna Cai , Fan Wang , Haowei Wang , Kun Wang , Kailai Yang , Sophia Ananiadou , Moyan Li , Mingming Fan

New NLP benchmarks are urgently needed to align with the rapid development of large language models (LLMs). We present C-Eval, the first comprehensive Chinese evaluation suite designed to assess advanced knowledge and reasoning abilities of…

Computation and Language · Computer Science 2023-11-07 Yuzhen Huang , Yuzhuo Bai , Zhihao Zhu , Junlei Zhang , Jinghan Zhang , Tangjun Su , Junteng Liu , Chuancheng Lv , Yikai Zhang , Jiayi Lei , Yao Fu , Maosong Sun , Junxian He

The rapid development of Chinese large language models (LLMs) poses big challenges for efficient LLM evaluation. While current initiatives have introduced new benchmarks or evaluation platforms for assessing Chinese LLMs, many of these…

Computation and Language · Computer Science 2024-03-20 Chuang Liu , Linhao Yu , Jiaxuan Li , Renren Jin , Yufei Huang , Ling Shi , Junhui Zhang , Xinmeng Ji , Tingting Cui , Tao Liu , Jinwang Song , Hongying Zan , Sun Li , Deyi Xiong

Chinese essay writing and its evaluation are critical in educational contexts, yet the capabilities of Large Language Models (LLMs) in this domain remain largely underexplored. Existing benchmarks often rely on coarse-grained text quality…

Computation and Language · Computer Science 2025-06-04 Fan Gao , Dongyuan Li , Ding Xia , Fei Mi , Yasheng Wang , Lifeng Shang , Baojun Wang

With the rapid development of Large Language Models (LLMs), it is crucial to have benchmarks which can evaluate the ability of LLMs on different domains. One common use of LLMs is performing tasks on scientific topics, such as writing…

The advent of Large Language Models (LLMs) offers potential solutions to address problems such as shortage of medical resources and low diagnostic consistency in psychiatric clinical practice. Despite this potential, a robust and…

Computation and Language · Computer Science 2025-06-19 Shuyu Liu , Ruoxi Wang , Ling Zhang , Xuequan Zhu , Rui Yang , Xinzhu Zhou , Fei Wu , Zhi Yang , Cheng Jin , Gang Wang
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