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Recent advancements in generative Large Language Models(LLMs) have been remarkable, however, the quality of the text generated by these models often reveals persistent issues. Evaluating the quality of text generated by these models,…

Computation and Language · Computer Science 2024-04-16 Yu Li , Shenyu Zhang , Rui Wu , Xiutian Huang , Yongrui Chen , Wenhao Xu , Guilin Qi , Dehai Min

Large language models (LLMs) have demonstrated impressive impact in the field of natural language processing, but they still struggle with several issues regarding, such as completeness, timeliness, faithfulness and adaptability. While…

Computation and Language · Computer Science 2023-08-24 Xintao Wang , Qianwen Yang , Yongting Qiu , Jiaqing Liang , Qianyu He , Zhouhong Gu , Yanghua Xiao , Wei Wang

Large Language Models (LLMs) have demonstrated remarkable adaptability, showcasing their capacity to excel in tasks for which they were not explicitly trained. However, despite their impressive natural language processing (NLP)…

Computation and Language · Computer Science 2023-09-08 Supun Manathunga , Isuru Hettigoda

Large language models (LLMs) can generate fluent dialogue, but prior works lack situational grounding, dynamic strategy control, and evaluation aligned with clinical standards in motivational interviewing (MI). We introduce StoryMI, a…

Computation and Language · Computer Science 2026-05-28 Qingyu Meng , Min Chen , Dingming Liu , Yifan Mo , Yue Su , Xin Sun , Koen Hindriks , Jiahuan Pei

Autonomous agents utilizing Large Language Models (LLMs) have demonstrated remarkable capabilities in isolated medical tasks like diagnosis and image analysis, but struggle with integrated clinical workflows that connect diagnostic…

Artificial Intelligence · Computer Science 2025-10-14 Hongjie Zheng , Zesheng Shi , Ping Yi

In healthcare intelligence, the ability to fuse heterogeneous, multi-intent information from diverse clinical sources is fundamental to building reliable decision-making systems. Large Language Model (LLM)-driven information interaction…

Computation and Language · Computer Science 2025-07-04 Dingkang Yang , Jinjie Wei , Mingcheng Li , Jiyao Liu , Lihao Liu , Ming Hu , Junjun He , Yakun Ju , Wei Zhou , Yang Liu , Lihua Zhang

Large Language Models (LLMs), prominently highlighted by the recent evolution in the Generative Pre-trained Transformers (GPT) series, have displayed significant prowess across various domains, such as aiding in healthcare diagnostics and…

Portfolio Management · Quantitative Finance 2023-09-08 Yang Li , Yangyang Yu , Haohang Li , Zhi Chen , Khaldoun Khashanah

Traditional AI-based healthcare systems often rely on single-modal data, limiting diagnostic accuracy due to incomplete information. However, recent advancements in foundation models show promising potential for enhancing diagnosis…

Artificial Intelligence · Computer Science 2025-03-24 Sihan Wang , Suiyang Jiang , Yibo Gao , Boming Wang , Shangqi Gao , Xiahai Zhuang

Since the release of ChatGPT and GPT-4, large language models (LLMs) and multimodal large language models (MLLMs) have attracted widespread attention for their exceptional capabilities in understanding, reasoning, and generation,…

Computation and Language · Computer Science 2024-12-31 Hanguang Xiao , Feizhong Zhou , Xingyue Liu , Tianqi Liu , Zhipeng Li , Xin Liu , Xiaoxuan Huang

Knowledge augmentation has significantly enhanced the performance of Large Language Models (LLMs) in knowledge-intensive tasks. However, existing methods typically operate on the simplistic premise that model performance equates with…

Computation and Language · Computer Science 2026-02-16 Hao Chen , Ye He , Yuchun Fan , Yukun Yan , Zhenghao Liu , Qingfu Zhu , Maosong Sun , Wanxiang Che

Large Language Models (LLMs) still face challenges when dealing with complex reasoning tasks, often resulting in hallucinations, which limit the practical application of LLMs. To alleviate this issue, this paper proposes a new method that…

Artificial Intelligence · Computer Science 2024-11-26 Zhihua Duan , Jialin Wang

Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-world clinical settings. However, clinical decision-making is inherently safety-critical,…

Computation and Language · Computer Science 2026-04-13 Xiaohan Ren , Chenxiao Fan , Wenyin Ma , Hongliang He , Chongming Gao , Xiaoyan Zhao , Fuli Feng

Large language models (LLMs) and LLM-based agents are increasingly deployed as assistants in planning and decision making, yet most existing systems are implicitly optimized for a single-principal interaction paradigm, in which the model is…

Computation and Language · Computer Science 2026-04-29 Shu Yang , Shenzhe Zhu , Hao Zhu , José Ramón Enríquez , Di Wang , Alex Pentland , Michiel A. Bakker , Jiaxin Pei

With appropriate data selection and training techniques, Large Language Models (LLMs) have demonstrated exceptional success in various medical examinations and multiple-choice questions. However, the application of LLMs in medical dialogue…

Computation and Language · Computer Science 2024-03-12 Jiageng Wu , Xian Wu , Yefeng Zheng , Jie Yang

Recent developments in Large Language Model (LLM)-based agents have shown impressive capabilities spanning multiple domains, exemplified by deep research systems that demonstrate superior performance on complex information-seeking and…

Computation and Language · Computer Science 2025-09-03 Ailing Yu , Lan Yao , Jingnan Liu , Zhe Chen , Jiajun Yin , Yuan Wang , Xinhao Liao , Zhiling Ye , Ji Li , Yun Yue , Hansong Xiao , Hualei Zhou , Chunxiao Guo , Peng Wei , Junwei Liu , Jinjie Gu

Large Language Model (LLM) agents significantly extend the capabilities of standalone LLMs, empowering them to interact with external tools (e.g., APIs, functions) and complete various tasks in a self-directed fashion. The challenge of tool…

Artificial Intelligence · Computer Science 2024-02-19 Weizhou Shen , Chenliang Li , Hongzhan Chen , Ming Yan , Xiaojun Quan , Hehong Chen , Ji Zhang , Fei Huang

Bridging the significant gap between large language model's English and non-English performance presents a great challenge. While some previous studies attempt to mitigate this gap with translated training data, the recently proposed…

Computation and Language · Computer Science 2024-11-07 Wenhao Zhu , Shujian Huang , Fei Yuan , Cheng Chen , Jiajun Chen , Alexandra Birch

Generative Large Language Models (LLMs) hold significant promise in healthcare, demonstrating capabilities such as passing medical licensing exams and providing clinical knowledge. However, their current use as information retrieval tools…

Large language models (LLMs), such as ChatGPT, have received substantial attention due to their capabilities for understanding and generating human language. While there has been a burgeoning trend in research focusing on the employment of…

Large Language Models (LLMs) have demonstrated significant capabilities in understanding and generating human language, contributing to more natural interactions with complex systems. However, they face challenges such as ambiguity in user…

Computation and Language · Computer Science 2025-07-17 Ana Davila , Jacinto Colan , Yasuhisa Hasegawa