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This volume contains the proceedings of the First Workshop on Logics and Model-checking for self-* systems (MOD* 2014). The worshop took place in Bertinoro, Italy, on 12th of September 2014, and was a satellite event of iFM 2014 (the 11th…

Logic in Computer Science · Computer Science 2014-11-14 Marcello Maria Bersani , Davide Bresolin , Luca Ferrucci , Manuel Mazzara

Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific…

This proceedings contains abstracts and position papers for the work presented at the third Logic and Practice of Programming (LPOP) Workshop. The workshop was held online, using zoom, at stonybrook.zoom.us, on December 13, 2022. The…

Programming Languages · Computer Science 2024-10-01 David S. Warren , Yanhong A. Liu

In this article, we explore various parallel and distributed computing topics from a user-centric software engineering perspective. Specifically, in the context of mobile application development, we study the basic building blocks of…

Software Engineering · Computer Science 2017-05-09 Konstantin Läufer , George K. Thiruvathukal

The demand for quality in mobile applications has increased greatly given users' high reliance on them for daily tasks. Developers work tirelessly to ensure that their applications are both functional and user-friendly. In pursuit of this,…

Software Engineering · Computer Science 2025-05-16 Safwat Ali Khan

The great diversity of end-user tasks ranging from manufacturing environments to personal homes makes pre-programming robots for general purpose applications extremely challenging. In fact, teaching robots new actions from scratch that can…

Robotics · Computer Science 2021-12-09 Ying Siu Liang , Damien Pellier , Humbert Fiorino , Sylvie Pesty

The increasingly concurrent and parallel landscape of hardware and software infrastructures demands the exploration and understanding of a wide variety of foundational and practical ideas. The International Workshop on Programming Language…

Programming Languages · Computer Science 2022-03-24 Marco Carbone , Rumyana Neykova

Large language models (LLMs) have demonstrated increasingly sophisticated performance in medical and other fields of knowledge. Traditional methods of creating specialist LLMs require extensive fine-tuning and training of models on large…

Computation and Language · Computer Science 2025-02-25 Sean Wu , Michael Koo , Fabien Scalzo , Ira Kurtz

These are the proceedings of the 10th International Workshop on Formal Engineering approaches to Software Components and Architectures (FESCA). The workshop was held on March 23, 2013 in Rome (Italy) as a satellite event to the European…

Software Engineering · Computer Science 2013-02-21 Barbora Buhnova , Lucia Happe , Jan Kofroň

Programming robots is a complicated and time-consuming task. A robot is essentially a real-time, distributed embedded system. Often, control and communication paths within the system are tightly coupled to the actual physical configuration…

Robotics · Computer Science 2014-01-08 Thomas Buchmann , Johannes Baumgartl , Dominik Henrich , Bernhard Westfechtel

The advent of increasingly powerful language models has raised expectations for language-based interactions. However, controlling these models is a challenge, emphasizing the need to be able to investigate the feasibility and value of their…

These are the revised versions of the papers presented at CICLOPS 2011, a workshop colocated with ICLP 2011.

Programming Languages · Computer Science 2011-12-22 Salvador Abreu , Vitor Santos Costa

These reports present the results of the 2013 Community Summer Study of the APS Division of Particles and Fields ("Snowmass 2013") on the future program of particle physics in the U.S. Chapter 9, on Computing, discusses the computing…

A collection of the accepted Findings papers that were presented at the 3rd Machine Learning for Health symposium (ML4H 2023), which was held on December 10, 2023, in New Orleans, Louisiana, USA. ML4H 2023 invited high-quality submissions…

Large Language Models (LLMs) are nowadays extensively used for various types of software engineering tasks, primarily code generation. Previous research has shown how suitable prompt engineering could help developers in improving their code…

The rise of large language models (LLMs) has given rise to a class of prompt-based interactive systems where users primarily express their input in natural language. However, composing a prompt as a linear text string becomes unwieldy when…

Human-Computer Interaction · Computer Science 2026-04-22 Tengyou Xu , Detao Ma , Xiang 'Anthony' Chen

Large Language Models (LLMs) have gained popularity in task planning for long-horizon manipulation tasks. To enhance the validity of LLM-generated plans, visual demonstrations and online videos have been widely employed to guide the…

Robotics · Computer Science 2025-03-12 Kejia Chen , Zheng Shen , Yue Zhang , Lingyun Chen , Fan Wu , Zhenshan Bing , Sami Haddadin , Alois Knoll

Large language models (LLMs) have taken the world by storm by making many previously difficult uses of AI feasible. LLMs are controlled via highly expressive textual prompts and return textual answers. Unfortunately, this unstructured text…

Artificial Intelligence · Computer Science 2024-10-28 Mandana Vaziri , Louis Mandel , Claudio Spiess , Martin Hirzel

Prompt engineering has made significant contributions to the era of large language models, yet its effectiveness depends on the skills of a prompt author. This paper introduces $\textit{iPrOp}$, a novel interactive prompt optimization…

Computation and Language · Computer Science 2025-06-30 Jiahui Li , Roman Klinger

Large Language Models, particularly decoder-only generative models such as GPT, are increasingly used to automate Software Engineering tasks. These models are primarily guided through natural language prompts, making prompt engineering a…

Software Engineering · Computer Science 2026-01-06 Alexander Korn , Lea Zaruchas , Chetan Arora , Andreas Metzger , Sven Smolka , Fanyu Wang , Andreas Vogelsang
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