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Related papers: A Closer Look at System Prompt Robustness

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The widespread adoption of large language models (LLMs) such as ChatGPT, Gemini, and DeepSeek has significantly changed how people approach tasks in education, professional work, and creative domains. This paper investigates how the…

Human-Computer Interaction · Computer Science 2025-08-29 Rizal Khoirul Anam

Language models are increasingly used for social robot navigation, yet existing benchmarks largely overlook principled prompt design for socially compliant behavior. This limitation is particularly relevant in practice, as many systems rely…

Robotics · Computer Science 2026-01-22 Ling Xiao , Toshihiko Yamasaki

Prompt engineering has emerged as an indispensable technique for extending the capabilities of large language models (LLMs) and vision-language models (VLMs). This approach leverages task-specific instructions, known as prompts, to enhance…

Artificial Intelligence · Computer Science 2025-03-18 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Vinija Jain , Samrat Mondal , Aman Chadha

In recent years, Large Language Models (LLMs) have demonstrated remarkable proficiency in comprehending and generating natural language, with a growing prevalence in the domain of recommendation systems. However, LLMs still face a…

Information Retrieval · Computer Science 2024-12-13 Xinyu Li , Chuang Zhao , Hongke Zhao , Likang Wu , Ming HE

Effective prompt engineering is critical to realizing the promised productivity gains of large language models (LLMs) in knowledge-intensive tasks. Yet, many users struggle to craft prompts that yield high-quality outputs, limiting the…

Human-Computer Interaction · Computer Science 2025-10-02 Niklas Gutheil , Valentin Mayer , Leopold Müller , Jörg Rommelt , Niklas Kühl

The field of prompt engineering is becoming an essential phenomenon in artificial intelligence. It is altering how data scientists interact with large language models (LLMs) for analytics applications. This research paper shares empirical…

Digital Libraries · Computer Science 2026-02-03 Snehasish Paul , Rohit Kumar , Laxman Das

Large Language Models (LLMs) changed the way we design and interact with software systems. Their ability to process and extract information from text has drastically improved productivity in a number of routine tasks. Developers that want…

Machine Learning · Computer Science 2025-08-26 Federico Errica , Giuseppe Siracusano , Davide Sanvito , Roberto Bifulco

The recent explosion in the capabilities of large language models has led to a wave of interest in how best to prompt a model to perform a given task. While it may be tempting to simply choose a prompt based on average performance on a…

Machine Learning · Computer Science 2024-03-29 Thomas P. Zollo , Todd Morrill , Zhun Deng , Jake C. Snell , Toniann Pitassi , Richard Zemel

As large language models (LLMs) advance, ensuring AI safety and alignment is paramount. One popular approach is prompt guards, lightweight mechanisms designed to filter malicious queries while being easy to implement and update. In this…

Machine Learning · Computer Science 2025-10-08 Jaiden Fairoze , Sanjam Garg , Keewoo Lee , Mingyuan Wang

Large Language Models (LLMs) are vulnerable to adversarial prompt based injects. These injects could jailbreak or exploit vulnerabilities within these models with explicit prompt requests leading to undesired responses. In the context of…

Cryptography and Security · Computer Science 2025-02-18 Jonathan Pan , Swee Liang Wong , Yidi Yuan , Xin Wei Chia

Deploying large language model (LLM)-driven conversational agents in enterprise settings requires prompts that are simultaneously correct at launch and resilient to the non-deterministic behavioral drift that characterizes production LLM…

Artificial Intelligence · Computer Science 2026-05-18 Keshava Chaitanya , Jahnavi Gundakaram

System prompts in Large Language Models (LLMs) are predefined directives that guide model behaviour, taking precedence over user inputs in text processing and generation. LLM deployers increasingly use them to ensure consistent responses…

Computers and Society · Computer Science 2025-06-24 Anna Neumann , Elisabeth Kirsten , Muhammad Bilal Zafar , Jatinder Singh

The ability of large language models (LLMs) to $``$learn in context$"$ based on the provided prompt has led to an explosive growth in their use, culminating in the proliferation of AI assistants such as ChatGPT, Claude, and Bard. These AI…

Computation and Language · Computer Science 2024-05-30 Namrata Shivagunde , Vladislav Lialin , Sherin Muckatira , Anna Rumshisky

Instruction fine-tuning has recently emerged as a promising approach for improving the zero-shot capabilities of Large Language Models (LLMs) on new tasks. This technique has shown particular strength in improving the performance of…

Computation and Language · Computer Science 2023-07-13 Jiuding Sun , Chantal Shaib , Byron C. Wallace

The growing integration of AI tools in software development, particularly Large Language Models (LLMs) such as ChatGPT, has revolutionized how developers approach coding tasks. However, achieving high-quality code often requires iterative…

Software Engineering · Computer Science 2025-06-03 Sophia DiCuffa , Amanda Zambrana , Priyanshi Yadav , Sashidhar Madiraju , Khushi Suman , Eman Abdullah AlOmar

The drastic increase of large language models' (LLMs) parameters has led to a new research direction of fine-tuning-free downstream customization by prompts, i.e., task descriptions. While these prompt-based services (e.g. OpenAI's GPTs)…

Computation and Language · Computer Science 2025-02-13 Zi Liang , Haibo Hu , Qingqing Ye , Yaxin Xiao , Haoyang Li

Large language models are increasingly used for vulnerability detection, yet their reliability under different prompt formulations remains uncharacterized. We present PromptAudit, a controlled evaluation framework that isolates prompt…

Machine Learning · Computer Science 2026-05-26 Steffen J. Camarato , Yahya Hmaiti , Mandana Ghadamian , David Mohaisen

The use of large language model (LLM)-powered chatbots, such as ChatGPT, has become popular across various domains, supporting a range of tasks and processes. However, due to the intrinsic complexity of LLMs, effective prompting is more…

This study investigates whether repeating questions within prompts influences the performance of large language models (LLMs). We hypothesize that reiterating a question within a single prompt might enhance the model's focus on key elements…

Computation and Language · Computer Science 2025-03-13 Sagi Shaier , Mario Sanz-Guerrero , Katharina von der Wense

System prompts are critical for guiding the behavior of Large Language Models (LLMs), yet they often contain proprietary logic or sensitive information, making them a prime target for extraction attacks. Adversarial queries can successfully…

Cryptography and Security · Computer Science 2026-02-03 Huseein Jawad , Nicolas Brunel