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Bringing generative AI into the architecture, engineering and construction (AEC) field requires systems that can translate natural language instructions into actions on standardized data models. We present MCP4IFC, a comprehensive…

Large language models have demonstrated the ability to perform \textit{in-context learning} (ICL), whereby the model performs predictions by directly mapping the query and a few examples from the given task to the output variable. In this…

Signal Processing · Electrical Eng. & Systems 2025-12-02 Meng Hua , Wenjing Zhang , Chenghong Bian , Deniz Gunduz

How to identify the comprehensive comparable performance of various Intrusion Detection (ID) algorithms which are based on the Model Checking (MC) techniques? To address this open issue, we conduct some tests for the model-checking-based…

Cryptography and Security · Computer Science 2018-06-26 Weijun Zhu

In-context learning (ICL) enables large language models (LLMs) to perform downstream tasks through advanced prompting and high-quality demonstrations. However, traditional ICL paradigms encounter significant limitations in complex reasoning…

Computation and Language · Computer Science 2025-06-03 Jinyang Wu , Mingkuan Feng , Shuai Zhang , Feihu Che , Zengqi Wen , Chonghua Liao , Jianhua Tao

In this paper, by treating in-context learning (ICL) as a meta-optimization process, we explain why LLMs are sensitive to the order of ICL examples. This understanding leads us to the development of Batch-ICL, an effective, efficient, and…

Machine Learning · Computer Science 2024-06-06 Kaiyi Zhang , Ang Lv , Yuhan Chen , Hansen Ha , Tao Xu , Rui Yan

The application of Machine Learning (ML) techniques to the well-known intrusion detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks through an effective and efficient detection process. In the…

Since the introduction of Large Language Models (LLMs), they have been widely adopted for various tasks such as text summarization, question answering, speech-to-text translation, and more. In recent times, the use of LLMs for code…

Software Engineering · Computer Science 2026-01-22 Krishna Vamshi Bodla , Haizhao Yang

xMLC is the second book of this `Machine Learning Tools in Fluid Mechanics' Series and focuses on Machine Learning Control (MLC). The objectives of this book are two-fold: First, provide an introduction to MLC for students, researchers, and…

Fluid Dynamics · Physics 2022-08-30 Guy Y. Cornejo Maceda , François Lusseyran , Bernd R. Noack

Proper Production Planning and Control (PPC) is capital to have an edge over competitors, reduce costs and respect delivery dates. With regard to PPC, Machine Learning (ML) provides new opportunities to make intelligent decisions based on…

Machine Learning · Computer Science 2021-06-25 Juan Pablo Usuga Cadavid , Samir Lamouri , Bernard Grabot , Arnaud Fortin

The rapid advancement of large language models (LLMs) has accelerated the emergence of in-context learning (ICL) as a cutting-edge approach in the natural language processing domain. Recently, ICL has been employed in visual understanding…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Dianmo Sheng , Dongdong Chen , Zhentao Tan , Qiankun Liu , Qi Chu , Jianmin Bao , Tao Gong , Bin Liu , Shengwei Xu , Nenghai Yu

Context: Software vulnerability assessment (SVA) is critical for identifying, evaluating, and prioritizing security weaknesses in software applications. Objective: Despite the increasing application of large language models (LLMs) in…

Software Engineering · Computer Science 2025-05-29 Chaoyang Gao , Xiang Chen , Guangbei Zhang

Industrial control systems (ICS) depend on highly heterogeneous environments where Linux, proprietary real-time operating systems, and Windows coexist. Although the IEC 62443-3-3 standard provides a comprehensive framework for securing such…

Cryptography and Security · Computer Science 2026-02-17 Miguel Bicudo , Estevão Rabello , Daniel Menasché , Paulo Segal , Claudio Segal , Anton Kocheturov , Priyanjan Sharma

Language models that can learn a task at inference time, called in-context learning (ICL), show increasing promise in natural language inference tasks. In ICL, a model user constructs a prompt to describe a task with a natural language…

Software Engineering · Computer Science 2024-04-22 Sarah Santos , Travis Breaux , Thomas Norton , Sara Haghighi , Sepideh Ghanavati

In-context learning (ICL) has demonstrated remarkable success in large language models (LLMs) due to its adaptability and parameter-free nature. However, it also introduces a critical vulnerability to backdoor attacks, where adversaries can…

Machine Learning · Computer Science 2025-07-03 Zhiyao Ren , Siyuan Liang , Aishan Liu , Dacheng Tao

Software is prone to security vulnerabilities. Program analysis tools to detect them have limited effectiveness in practice due to their reliance on human labeled specifications. Large language models (or LLMs) have shown impressive code…

Cryptography and Security · Computer Science 2025-04-08 Ziyang Li , Saikat Dutta , Mayur Naik

Programmable Logic Controllers (PLCs) are a core component of an Industrial Control System (ICS). However, if a PLC is compromised or the commands sent across a network from the PLCs are spoofed, consequences could be catastrophic. In this…

Cryptography and Security · Computer Science 2021-02-19 Chuadhry Mujeeb Ahmed , Martin Ochoa , Jianying Zhou , Aditya Mathur

Log analysis is a relevant research field in cybersecurity as they can provide a source of information for the detection of threats to networks and systems. This paper presents a pipeline to use fine-tuned Large Language Models (LLMs) for…

Cryptography and Security · Computer Science 2025-07-04 Jorge J. Tejero-Fernández , Alfonso Sánchez-Macián

In industrial control systems, devices such as Programmable Logic Controllers (PLCs) are commonly used to directly interact with sensors and actuators, and perform local automatic control. PLCs run software on two different layers: a)…

Cryptography and Security · Computer Science 2017-02-20 Naman Govil , Anand Agrawal , Nils Ole Tippenhauer

Lithography, transferring chip design masks to the silicon wafer, is the most important phase in modern semiconductor manufacturing flow. Due to the limitations of lithography systems, Extensive design optimizations are required to tackle…

Machine Learning · Computer Science 2024-05-07 Haoyu Yang , Haoxing Ren