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Emotional Support Conversation (ESC) is a typical dialogue that can effectively assist the user in mitigating emotional pressures. However, owing to the inherent subjectivity involved in analyzing emotions, current non-artificial…

计算与语言 · 计算机科学 2024-08-05 Huaiwen Zhang , Yu Chen , Ming Wang , Shi Feng

This study investigates uncertainty quantification in large language models (LLMs) for medical applications, emphasizing both technical innovations and philosophical implications. As LLMs become integral to clinical decision-making,…

Online medical forums have long served as vital platforms where patients seek professional healthcare advice, generating vast amounts of valuable knowledge. However, the informal nature and linguistic complexity of forum interactions pose…

计算与语言 · 计算机科学 2025-10-22 Antonio Romano , Giuseppe Riccio , Mariano Barone , Marco Postiglione , Vincenzo Moscato

Large language models (LLMs) have shown considerable potential in supporting medical diagnosis. However, their effective integration into clinical workflows is hindered by physicians' difficulties in perceiving and trusting LLM…

人机交互 · 计算机科学 2026-01-28 Yuansong Xu , Yichao Zhu , Haokai Wang , Yuchen Wu , Yang Ouyang , Hanlu Li , Wenzhe Zhou , Xinyu Liu , Chang Jiang , Quan Li

Multimodal large language models (MLLMs) have broadened the scope of AI applications. Existing automatic evaluation methodologies for MLLMs are mainly limited in evaluating queries without considering user experiences, inadequately…

Critical appraisal of scientific literature is an essential skill in the biomedical field. While large language models (LLMs) can offer promising support in this task, their reliability remains limited, particularly for critical reasoning…

计算与语言 · 计算机科学 2026-03-05 Doria Bonzi , Alexandre Guiggi , Frédéric Béchet , Carlos Ramisch , Benoit Favre

Empowered by vast internal knowledge reservoir, the new generation of large language models (LLMs) demonstrate untapped potential to tackle medical tasks. However, there is insufficient effort made towards summoning up a synergic effect…

计算与语言 · 计算机科学 2025-05-23 Kexin Shang , Chia-Hsuan Chang , Christopher C. Yang

Accurate and reliable search on online healthcare platforms is critical for user safety and service efficacy. Traditional methods, however, often fail to comprehend complex and nuanced user queries, limiting their effectiveness. Large…

计算与语言 · 计算机科学 2025-12-04 Chuyue Wang , Jie Feng , Yuxi Wu , Hang Zhang , Zhiguo Fan , Bing Cheng , Wei Lin

The rising prevalence of eye diseases poses a growing public health burden. Large language models (LLMs) offer a promising path to reduce documentation workload and support clinical decision-making. However, few have been tailored for…

Recently, there has been a growing interest among large language model (LLM) developers in LLM-based document reading systems, which enable users to upload their own documents and pose questions related to the document contents, going…

计算与语言 · 计算机科学 2024-07-16 Anni Zou , Wenhao Yu , Hongming Zhang , Kaixin Ma , Deng Cai , Zhuosheng Zhang , Hai Zhao , Dong Yu

Competency modeling is widely used in human resource management to select, develop, and evaluate talent. However, traditional expert-driven approaches rely heavily on manual analysis of large volumes of interview transcripts, making them…

计算与语言 · 计算机科学 2026-02-16 Silin Du , Manqing Xin , Raymond Jia Wang

Large language models (LLMs) are increasingly used in the mental health domain, yet it remains unclear how well they capture related biomedical knowledge and how reliably they apply it to clinically salient structured judgments. Here, we…

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 effectiveness of these models in clinical settings remains…

人工智能 · 计算机科学 2024-08-22 Yining Hua , Hongbin Na , Zehan Li , Fenglin Liu , Xiao Fang , David Clifton , John Torous

Users typically engage with LLMs interactively, yet most existing benchmarks evaluate them in a static, single-turn format, posing reliability concerns in interactive scenarios. We identify a key obstacle towards reliability: LLMs are…

The recommendation of medication is a vital aspect of intelligent healthcare systems, as it involves prescribing the most suitable drugs based on a patient's specific health needs. Unfortunately, many sophisticated models currently in use…

信息检索 · 计算机科学 2025-01-28 Qidong Liu , Xian Wu , Xiangyu Zhao , Yuanshao Zhu , Zijian Zhang , Feng Tian , Yefeng Zheng

There is increasing interest in the application large language models (LLMs) to the medical field, in part because of their impressive performance on medical exam questions. While promising, exam questions do not reflect the complexity of…

The advancement of large language models (LLMs) has outpaced traditional evaluation methodologies. This progress presents novel challenges, such as measuring human-like psychological constructs, moving beyond static and task-specific…

计算与语言 · 计算机科学 2026-03-12 Haoran Ye , Jing Jin , Yuhang Xie , Xin Zhang , Guojie Song

In this paper, we investigate the potential of Large Language Models (LLMs) to improve English speaking skills. This is particularly relevant in countries like India, where English is crucial for academic, professional, and personal…

人机交互 · 计算机科学 2024-05-15 Manas Mhasakar , Shikhar Sharma , Apurv Mehra , Utkarsh Venaik , Ujjwal Singhal , Dhruv Kumar , Kashish Mittal

Large Language Models (LLMs) hold significant promise for improving clinical decision support and reducing physician burnout by synthesizing complex, longitudinal cancer Electronic Health Records (EHRs). However, their implementation in…

计算与语言 · 计算机科学 2026-01-12 Dongchen Li , Jitao Liang , Wei Li , Xiaoyu Wang , Longbing Cao , Kun Yu

Chart question answering (CQA) has become a critical multimodal task for evaluating the reasoning capabilities of vision-language models. While early approaches have shown promising performance by focusing on visual features or leveraging…

计算与语言 · 计算机科学 2025-05-30 Jingxuan Wei , Nan Xu , Junnan Zhu , Yanni Hao , Gaowei Wu , Bihui Yu , Lei Wang
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