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In recent years, large language models have had a very impressive performance, which largely contributed to the development and application of artificial intelligence, and the parameters and performance of the models are still growing…

Machine Learning · Computer Science 2025-01-10 Xuran Zheng , Chang D. Yoo

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…

Computation and Language · Computer Science 2025-05-23 Kexin Shang , Chia-Hsuan Chang , Christopher C. Yang

In this paper, we describe the capabilities and constraints of Large Language Models (LLMs) within disparate academic disciplines, aiming to delineate their strengths and limitations with precision. We examine how LLMs augment scientific…

Pre-trained large language models (LLM) have emerged as a powerful tool for simulating various scenarios and generating output given specific instructions and multimodal input. In this work, we analyze the specific use of LLM to enhance a…

Machine Learning · Computer Science 2024-05-10 Yuhang Wu , Yingfei Wang , Chu Wang , Zeyu Zheng

Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have made significant advancements in reasoning capabilities. However, they still face challenges such as high computational demands and privacy concerns. This paper…

Large Language Models (LLMs) have emerged as powerful tools for automating complex reasoning and decision-making tasks. In telecommunications, they hold the potential to transform network optimization, automate troubleshooting, enhance…

Large Language Models (LLMs) have shown promising results on machine translation for high resource language pairs and domains. However, in specialised domains (e.g. medical) LLMs have shown lower performance compared to standard neural…

Computation and Language · Computer Science 2025-07-31 Miguel Rios

Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them…

Recently, Large Language Models (LLM) have demonstrated impressive capability to solve a wide range of tasks. However, despite their success across various tasks, no prior work has investigated their capability in the biomedical domain yet.…

Computation and Language · Computer Science 2024-02-21 Israt Jahan , Md Tahmid Rahman Laskar , Chun Peng , Jimmy Huang

Although large language models (LLMs) are impressive in solving various tasks, they can quickly be outdated after deployment. Maintaining their up-to-date status is a pressing concern in the current era. This paper provides a comprehensive…

Computation and Language · Computer Science 2023-10-12 Zihan Zhang , Meng Fang , Ling Chen , Mohammad-Reza Namazi-Rad , Jun Wang

By integrating the perception capabilities of multimodal encoders with the generative power of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), exemplified by GPT-4V, have achieved great success in various multimodal…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Wenbin An , Jiahao Nie , Yaqiang Wu , Feng Tian , Shijian Lu , Qinghua Zheng

Reinforcement learning (RL) has shown impressive results in sequential decision-making tasks. Meanwhile, Large Language Models (LLMs) and Vision-Language Models (VLMs) have emerged, exhibiting impressive capabilities in multimodal…

Large Language Models (LLMs) have delivered impressive results in language understanding, generation, reasoning, and pushes the ability boundary of multimodal models. Transformer models, as the foundation of modern LLMs, offer a strong…

Computation and Language · Computer Science 2025-08-14 Weigao Sun , Jiaxi Hu , Yucheng Zhou , Jusen Du , Disen Lan , Kexin Wang , Tong Zhu , Xiaoye Qu , Yu Zhang , Xiaoyu Mo , Daizong Liu , Yuxuan Liang , Wenliang Chen , Guoqi Li , Yu Cheng

Multilingual Language Models (\MLLMs) such as mBERT, XLM, XLM-R, \textit{etc.} have emerged as a viable option for bringing the power of pretraining to a large number of languages. Given their success in zero-shot transfer learning, there…

Computation and Language · Computer Science 2021-12-24 Sumanth Doddapaneni , Gowtham Ramesh , Mitesh M. Khapra , Anoop Kunchukuttan , Pratyush Kumar

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the…

Computation and Language · Computer Science 2024-04-12 Linyi Yang , Shuibai Zhang , Zhuohao Yu , Guangsheng Bao , Yidong Wang , Jindong Wang , Ruochen Xu , Wei Ye , Xing Xie , Weizhu Chen , Yue Zhang

Large Language Models (LLMs) excel in generating personalized content and facilitating interactive dialogues, showcasing their remarkable aptitude for a myriad of applications. However, their capabilities in reasoning and providing…

Computation and Language · Computer Science 2024-02-16 Min Zhang , Sato Takumi , Jack Zhang , Jun Wang

Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table…

Large language models (LLMs) have not only revolutionized the field of natural language processing (NLP) but also have the potential to bring a paradigm shift in many other fields due to their remarkable abilities of language understanding,…

Information Retrieval · Computer Science 2024-10-29 Qi Wang , Jindong Li , Shiqi Wang , Qianli Xing , Runliang Niu , He Kong , Rui Li , Guodong Long , Yi Chang , Chengqi Zhang

Large Language Models (LLMs) have been employed in financial decision making, enhancing analytical capabilities for investment strategies. Traditional investment strategies often utilize quantitative models, fundamental analysis, and…

General Finance · Quantitative Finance 2025-07-04 Sedigheh Mahdavi , Jiating , Chen , Pradeep Kumar Joshi , Lina Huertas Guativa , Upmanyu Singh

There have been rapid advancements in the capabilities of large language models (LLMs) in recent years, greatly revolutionizing the field of natural language processing (NLP) and artificial intelligence (AI) to understand and interact with…

Computation and Language · Computer Science 2024-09-26 Zeyneb N. Kaya , Souvick Ghosh