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Large language models (LLMs) have received considerable attention recently due to their outstanding comprehension and reasoning capabilities, leading to great progress in many fields. The advancement of LLM techniques also offers promising…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Hao Zhou , Chengming Hu , Ye Yuan , Yufei Cui , Yili Jin , Can Chen , Haolun Wu , Dun Yuan , Li Jiang , Di Wu , Xue Liu , Charlie Zhang , Xianbin Wang , Jiangchuan Liu

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

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

We show that large language models (LLMs) are remarkably good at working with interpretable models that decompose complex outcomes into univariate graph-represented components. By adopting a hierarchical approach to reasoning, LLMs can…

Large Language Models (LLMs) have shown the potential to be valuable teaching tools, with the potential of giving every student a personalized tutor. However, one challenge with using LLMs to learn new concepts is that when learning a topic…

Human-Computer Interaction · Computer Science 2024-11-19 Steve Oney , Yue Shen , Fei Wu , Young Suh Hong , Ziang Wang , Yamini Khajekar , Jiacheng Zhang , April Yi Wang

Large language models (LLMs) process and predict sequences containing text to answer questions, and address tasks including document summarization, providing recommendations, writing software and solving quantitative problems. We provide a…

Numerical Analysis · Mathematics 2026-02-02 Ricardo Baptista , Andrew Stuart , Son Tran

Large language models (LLMs) have not only revolutionized natural language processing but also extended their prowess to various domains, marking a significant stride towards artificial general intelligence. The interplay between LLMs and…

Neural and Evolutionary Computing · Computer Science 2024-05-30 Xingyu Wu , Sheng-hao Wu , Jibin Wu , Liang Feng , Kay Chen Tan

Large Language Models (LLMs) represent a landmark achievement in Artificial Intelligence (AI), demonstrating unprecedented proficiency in procedural tasks such as text generation, code completion, and conversational coherence. These…

Artificial Intelligence · Computer Science 2025-05-07 Schaun Wheeler , Olivier Jeunen

In Business Process Management (BPM), effectively comprehending process models is crucial yet poses significant challenges, particularly as organizations scale and processes become more complex. This paper introduces a novel framework…

This survey and application guide to multimodal large language models(MLLMs) explores the rapidly developing field of MLLMs, examining their architectures, applications, and impact on AI and Generative Models. Starting with foundational…

Artificial Intelligence · Computer Science 2025-12-02 Chia Xin Liang , Pu Tian , Caitlyn Heqi Yin , Yao Yua , Wei An-Hou , Li Ming , Xinyuan Song , Tianyang Wang , Ziqian Bi , Ming Liu

Predictive analysis is a cornerstone of modern decision-making, with applications in various domains. Large Language Models (LLMs) have emerged as powerful tools in enabling nuanced, knowledge-intensive conversations, thus aiding in complex…

Computation and Language · Computer Science 2025-05-26 Qin Chen , Yuanyi Ren , Xiaojun Ma , Yuyang Shi

This paper presents novel systems and methodologies for the development of efficient large language models (LLMs). It explores the trade-offs between model size, performance, and computational resources, with the aim of maximizing the…

Computation and Language · Computer Science 2023-09-14 Sia Gholami , Marwan Omar

Multilingual Large Language Models (MLLMs) represent a pivotal advancement in democratizing artificial intelligence across linguistic boundaries. While theoretical foundations are well-established, practical implementation guidelines remain…

Computation and Language · Computer Science 2024-10-24 Junhua Liu , Bin Fu

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

Computation and Language · Computer Science 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Large Language Models (LLMs) have garnered significant attention due to their remarkable ability to process information across various languages. Despite their capabilities, they exhibit inconsistencies in handling identical queries in…

Computation and Language · Computer Science 2024-06-24 Yue Huang , Chenrui Fan , Yuan Li , Siyuan Wu , Tianyi Zhou , Xiangliang Zhang , Lichao Sun

As Large Language Models (LLMs) rise in popularity, it is necessary to assess their capability in critically relevant domains. We present a comprehensive evaluation framework, grounded in science communication research, to assess LLM…

Artificial intelligence (AI) has a profound impact on traditional education. In recent years, large language models (LLMs) have been increasingly used in various applications such as natural language processing, computer vision, speech…

Computation and Language · Computer Science 2024-05-24 Hanyi Xu , Wensheng Gan , Zhenlian Qi , Jiayang Wu , Philip S. Yu

Artificial intelligence (AI), machine learning, and deep learning have become transformative forces in big data analytics and management, enabling groundbreaking advancements across diverse industries. This article delves into the…

The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with large language models (LLMs) and computer vision (CV) systems driving advancements in natural language understanding and visual processing,…

Computation and Language · Computer Science 2024-12-04 Yunkai Dang , Kaichen Huang , Jiahao Huo , Yibo Yan , Sirui Huang , Dongrui Liu , Mengxi Gao , Jie Zhang , Chen Qian , Kun Wang , Yong Liu , Jing Shao , Hui Xiong , Xuming Hu

Topic modelling, as a well-established unsupervised technique, has found extensive use in automatically detecting significant topics within a corpus of documents. However, classic topic modelling approaches (e.g., LDA) have certain…

Computation and Language · Computer Science 2024-03-27 Yida Mu , Chun Dong , Kalina Bontcheva , Xingyi Song