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Effective utilization of time series data is often constrained by the scarcity of data quantity that reflects complex dynamics, especially under the condition of distributional shifts. Existing datasets may not encompass the full range of…

Computational Engineering, Finance, and Science · Computer Science 2024-06-11 Haibei Zhu , Yousef El-Laham , Elizabeth Fons , Svitlana Vyetrenko

Large language models are being rapidly deployed across many fields such as healthcare, finance, transportation, and energy, where time-series data are fundamental components. The current works are still limited in their ability to perform…

Artificial Intelligence · Computer Science 2026-01-23 Paul Quinlan , Qingguo Li , Xiaodan Zhu

Understanding how large language models (LLMs) grasp the historical context of concepts and their semantic evolution is essential in advancing artificial intelligence and linguistic studies. This study aims to evaluate the capabilities of…

Computation and Language · Computer Science 2025-01-13 Mohamed Taher Alrefaie , Fatty Salem , Nour Eldin Morsy , Nada Samir , Mohamed Medhat Gaber

Time series forecasting plays a significant role in finance, energy, meteorology, and IoT applications. Recent studies have leveraged the generalization capabilities of large language models (LLMs) to adapt to time series forecasting,…

Machine Learning · Computer Science 2026-05-12 Hao Liu , Xiaoxing Zhang , Chun Yang , Xiaobin Zhu

Planning represents a fundamental capability of intelligent agents, requiring comprehensive environmental understanding, rigorous logical reasoning, and effective sequential decision-making. While Large Language Models (LLMs) have…

Artificial Intelligence · Computer Science 2025-05-27 Pengfei Cao , Tianyi Men , Wencan Liu , Jingwen Zhang , Xuzhao Li , Xixun Lin , Dianbo Sui , Yanan Cao , Kang Liu , Jun Zhao

Large Language Models (LLMs) have fundamentally transformed approaches to Natural Language Processing (NLP) tasks across diverse domains. In healthcare, accurate and cost-efficient text classification is crucial, whether for clinical notes…

Computation and Language · Computer Science 2026-02-16 Hajar Sakai , Sarah S. Lam

Time series anomaly detection is critical for supply chain management to take proactive operations, but faces challenges: classical unsupervised anomaly detection based on exploiting data patterns often yields results misaligned with…

Machine Learning · Computer Science 2026-01-28 Haoting Zhang , Shekhar Jain

In an era defined by the explosive growth of data and rapid technological advancements, Multimodal Large Language Models (MLLMs) stand at the forefront of artificial intelligence (AI) systems. Designed to seamlessly integrate diverse data…

Time series modeling holds significant importance in many real-world applications and has been extensively studied. While pre-trained foundation models have made impressive strides in the fields of natural language processing (NLP) and…

Computation and Language · Computer Science 2025-02-20 Juyuan Zhang , Wei Zhu , Jiechao Gao

The application of large language models (LLMs) in healthcare has gained significant attention due to their ability to process complex medical data and provide insights for clinical decision-making. These models have demonstrated…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Amna Khalid , Ayma Khalid , Umar Khalid

Large Language Models (LLMs) have recently demonstrated impressive capabilities in natural language processing due to their strong generalization and sequence modeling capabilities. However, their direct application to time series…

Computation and Language · Computer Science 2025-08-12 Yanru Sun , Emadeldeen Eldele , Zongxia Xie , Yucheng Wang , Wenzhe Niu , Qinghua Hu , Chee Keong Kwoh , Min Wu

This paper presents a comprehensive evaluation of the capabilities of Large Language Models (LLMs) in metaphor interpretation across multiple datasets, tasks, and prompt configurations. Although metaphor processing has gained significant…

Computation and Language · Computer Science 2025-07-22 Elisa Sanchez-Bayona , Rodrigo Agerri

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

Multilingual Large Language Models are capable of using powerful Large Language Models to handle and respond to queries in multiple languages, which achieves remarkable success in multilingual natural language processing tasks. Despite…

Computation and Language · Computer Science 2024-04-09 Libo Qin , Qiguang Chen , Yuhang Zhou , Zhi Chen , Yinghui Li , Lizi Liao , Min Li , Wanxiang Che , Philip S. Yu

Large Language Models (LLM), which have developed in recent years, enable credit risk assessment through the analysis of financial texts such as analyst reports and corporate disclosures. This paper presents the first systematic review and…

Risk Management · Quantitative Finance 2025-06-10 Muhammed Golec , Maha AlabdulJalil

In recent years, Large Language Models (LLMs) have emerged as transformative tools across numerous domains, impacting how professionals approach complex analytical tasks. This systematic mapping study comprehensively examines the…

Computers and Society · Computer Science 2025-08-19 Sai Sanjna Chintakunta , Nathalia Nascimento , Everton Guimaraes

Building effective machine learning (ML) workflows to address complex tasks is a primary focus of the Automatic ML (AutoML) community and a critical step toward achieving artificial general intelligence (AGI). Recently, the integration of…

Machine Learning · Computer Science 2024-12-30 Yang Gu , Hengyu You , Jian Cao , Muran Yu , Haoran Fan , Shiyou Qian

In the rapidly evolving domain of Natural Language Generation (NLG) evaluation, introducing Large Language Models (LLMs) has opened new avenues for assessing generated content quality, e.g., coherence, creativity, and context relevance.…

Computation and Language · Computer Science 2024-06-13 Zhen Li , Xiaohan Xu , Tao Shen , Can Xu , Jia-Chen Gu , Yuxuan Lai , Chongyang Tao , Shuai Ma

Recent advances in large language models (LLMs) have unlocked novel opportunities for machine learning applications in the financial domain. These models have demonstrated remarkable capabilities in understanding context, processing vast…

General Finance · Quantitative Finance 2024-06-19 Yuqi Nie , Yaxuan Kong , Xiaowen Dong , John M. Mulvey , H. Vincent Poor , Qingsong Wen , Stefan Zohren

Automatic disease diagnosis has become increasingly valuable in clinical practice. The advent of large language models (LLMs) has catalyzed a paradigm shift in artificial intelligence, with growing evidence supporting the efficacy of LLMs…

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