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The breakthrough of generative large language models (LLMs) that can solve different tasks through chat interaction has led to a significant increase in the use of general benchmarks to assess the quality or performance of these models…

In recent years, the integration of large language models (LLMs) has revolutionized the field of robotics, enabling robots to communicate, understand, and reason with human-like proficiency. This paper explores the multifaceted impact of…

This paper presents insights from evaluating 16 frontier large language models (LLMs) on the WebApp1K benchmark, a test suite designed to assess the ability of LLMs to generate web application code. The results reveal that while all models…

This volume consists of the proceedings of the 5th Workshop on Formal Languages and Analysis of Contract-Oriented Software (FLACOS'11). The FLACOS Workshops serve as annual meeting places to bring together researchers and practitioners…

The aim of the FESCA workshop is to bring together junior researchers from formal methods, software engineering, and industry interested in the development and application of formal modelling approaches as well as associated analysis and…

Modern day system developers have some serious problems to contend with. The systems they develop are becoming increasingly complex as customers demand richer functionality delivered in ever shorter timescales. They have to manage a huge…

Model Transformations in Practice (MTiP) 2005 was a workshop which provided a forum for the model transformation community to discuss practical model transformation issues. Although many different model transformation approaches have been…

Small Language Models (SLMs) have gained substantial attention due to their ability to execute diverse language tasks successfully while using fewer computer resources. These models are particularly ideal for deployment in limited…

With the growing deployment of Vision-Language Models (VLMs), pre-trained on large image-text and video-text datasets, it is critical to equip users with the tools to discern when to trust these systems. However, examining how user trust in…

The recent advances in neural language models have also been successfully applied to the field of chemistry, offering generative solutions for classical problems in molecular design and synthesis planning. These new methods have the…

Agile software development principles and values have been widely adopted across various industries, influencing products and services globally. Despite its increasing popularity, a significant gap remains between research and practical…

Recent advancements in large language models (LLMs) have spurred interest in expanding their application beyond text-based tasks. A large number of studies have explored integrating other modalities with LLMs, notably speech modality, which…

This volume contains the proceedings of the (first) Graphs as Models (GaM) 2015 workshop, held on 10-11 April 2015 in London, U.K., as a satellite workshop of ETAPS 2015, the European Joint Conferences on Theory and Practice of Software.…

Multi-robot systems have been widely deployed in real-world applications, providing significant improvements in efficiency and reductions in labor costs. However, most existing multi-robot collaboration methods rely on extensive…

Foundation models, including Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Image Generative Models (i.e, Text-to-Image Models and Image-Editing Models), and Video Generative Models, have become essential tools with…

This volume contains the proceedings of the Seventh Workshop on Model-Based Testing (MBT 2012), which was held on 25 March, 2012 in Tallinn, Estonia, as a satellite event of the European Joint Conferences on Theory and Practice of Software,…

We propose a half-day workshop at IEEE VIS 2023 on the topic of communication and collaboration around data. Specifically, we aim to gather researchers interested on multimodal, synchronous, and remote or hybrid forms of communication and…

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

Large Language Models (LLMs) have demonstrated remarkable language understanding and generation capabilities. However, training, deploying, and accessing these models pose notable challenges, including resource-intensive demands, extended…

Recently, there has been growing interest in leveraging large language models (LLMs) to generate symbolic world models from textual descriptions. Although LLMs have been extensively explored in the context of world modeling, prior studies…