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Traditional manufacturing faces challenges adapting to dynamic environments and quickly responding to manufacturing changes. The use of multi-agent systems has improved adaptability and coordination but requires further advancements in…

Multiagent Systems · Computer Science 2024-06-24 Jonghan Lim , Birgit Vogel-Heuser , Ilya Kovalenko

Controlling the text generated by language models and customizing the content has been a long-standing challenge. Existing prompting techniques proposed in pursuit of providing control are task-specific and lack generality; this provides…

Computation and Language · Computer Science 2023-06-14 Swaroop Mishra , Elnaz Nouri

Prompt learning is a new paradigm for utilizing pre-trained language models and has achieved great success in many tasks. To adopt prompt learning in the NER task, two kinds of methods have been explored from a pair of symmetric…

Computation and Language · Computer Science 2023-05-29 Yongliang Shen , Zeqi Tan , Shuhui Wu , Wenqi Zhang , Rongsheng Zhang , Yadong Xi , Weiming Lu , Yueting Zhuang

Deep generative modeling of natural languages has achieved many successes, such as producing fluent sentences and translating from one language into another. However, the development of generative modeling techniques for paraphrase…

Computation and Language · Computer Science 2023-11-28 Haotian Luo , Yixin Liu , Peidong Liu , Xianggen Liu

Prompt engineering is a challenging and important task due to the high sensitivity of Large Language Models (LLMs) to the given prompt and the inherent ambiguity of a textual task instruction. Automatic prompt engineering is essential to…

Computation and Language · Computer Science 2024-02-06 Elad Levi , Eli Brosh , Matan Friedmann

Prompt engineering has emerged as a useful way studying the algorithmic tendencies and biases of large language models. Meanwhile creatives and academics have leveraged LLMs to develop creative works and explore the boundaries of their…

Computation and Language · Computer Science 2025-12-08 P. D. Edgar , Alia Hall

Prompt engineering has emerged as a powerful technique for optimizing large language models (LLMs) for specific applications, enabling faster prototyping and improved performance, and giving rise to the interest of the community in…

Artificial Intelligence · Computer Science 2025-02-17 Roman Levin , Valeriia Cherepanova , Abhimanyu Hans , Avi Schwarzschild , Tom Goldstein

Chatbots have long been explored as tools to support learning, and recent advances in large language models have significantly expanded the availability of platforms for educators to author AI tutoring chatbots. Yet effective authorship…

Human-Computer Interaction · Computer Science 2026-05-19 Miina Koyama , Ruiwei Xiao , John Stamper

Large language models can perform various reasoning tasks by using chain-of-thought prompting, which guides them to find answers through step-by-step demonstrations. However, the quality of the prompts depends on the demonstrations given to…

Computation and Language · Computer Science 2023-02-02 Zhihong Shao , Yeyun Gong , Yelong Shen , Minlie Huang , Nan Duan , Weizhu Chen

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation. However, despite their impressive capabilities, they still possess limitations,…

Computation and Language · Computer Science 2023-10-17 Yang Deng , Lizi Liao , Liang Chen , Hongru Wang , Wenqiang Lei , Tat-Seng Chua

Generative Pre-trained Transformer (GPT) is a state-of-the-art machine learning model capable of generating human-like text through natural language processing (NLP). GPT is trained on massive amounts of text data and uses deep learning…

We propose cognitive prompting as a novel approach to guide problem-solving in large language models (LLMs) through structured, human-like cognitive operations, such as goal clarification, decomposition, filtering, abstraction, and pattern…

Computation and Language · Computer Science 2024-12-03 Oliver Kramer , Jill Baumann

This comprehensive review delves into the pivotal role of prompt engineering in unleashing the capabilities of Large Language Models (LLMs). The development of Artificial Intelligence (AI), from its inception in the 1950s to the emergence…

Computation and Language · Computer Science 2025-06-18 Banghao Chen , Zhaofeng Zhang , Nicolas Langrené , Shengxin Zhu

Pre-trained language models (LLMs) such as GPT-3 can carry fluent, multi-turn conversations out-of-the-box, making them attractive materials for chatbot design. Further, designers can improve LLM chatbot utterances by prepending textual…

Human-Computer Interaction · Computer Science 2023-02-08 J. D. Zamfirescu-Pereira , Bjoern Hartmann , Qian Yang

Large language models (LLMs) can be used as accessible and intelligent chatbots by constructing natural language queries and directly inputting the prompt into the large language model. However, different prompt' constructions often lead to…

Computation and Language · Computer Science 2023-12-14 Jinta Weng , Jiarui Zhang , Yue Hu , Daidong Fa , Xiaofeng Xuand , Heyan Huang

The use of generative AI (GenAI) tools has fundamentally transformed software development. Central to this shift is prompt engineering, the practice of crafting textual prompts to guide GenAI tools in generating useful content. Although…

Software Engineering · Computer Science 2026-01-26 Daniel Otten , Trevor Stalnaker , Nathan Wintersgill , Oscar Chaparro , Denys Poshyvanyk

Schema matching is the process of identifying correspondences between the elements of two given schemata, essential for database management systems, data integration, and data warehousing. For datasets across different scenarios, the…

Databases · Computer Science 2025-03-07 Longyu Feng , Huahang Li , Chen Jason Zhang

Learning to use feature-rich software is a persistent challenge, but generative AI tools promise to lower this barrier by replacing complex navigation with natural language prompts. We investigated how people approach prompt-based tools for…

Human-Computer Interaction · Computer Science 2026-04-01 Kanak Gautam , Poorvi Bhatia , Parmit K. Chilana

Recent works have shown promising results of prompt tuning in stimulating pre-trained language models (PLMs) for natural language processing (NLP) tasks. However, to the best of our knowledge, existing works focus on prompt-tuning…

Computation and Language · Computer Science 2022-05-24 Yuan Yao , Bowen Dong , Ao Zhang , Zhengyan Zhang , Ruobing Xie , Zhiyuan Liu , Leyu Lin , Maosong Sun , Jianyong Wang

Recent advancements in speech synthesis have enabled large language model (LLM)-based systems to perform zero-shot generation with controllable content, timbre, speaker identity, and emotion through input prompts. As a result, these models…