Tootfinder

OSS-UAgent: An Agent-based Usability Evaluation Framework for Open Source Software
Lingkai Meng, Yu Shao, Long Yuan, Longbin Lai, Peng Cheng, Wenyuan Yu, Wenjie Zhang, Xuemin Lin, Jingren Zhou
https://arxiv.org/abs/2505.23239

OSS-UAgent: An Agent-based Usability Evaluation Framework for Open Source Software
Usability evaluation is critical to the impact and adoption of open source software (OSS), yet traditional methods relying on human evaluators suffer from high costs and limited scalability. To address these limitations, we introduce OSS-UAgent, an automated, configurable, and interactive agent-based usability evaluation framework specifically designed for open source software. Our framework employs intelligent agents powered by large language models (LLMs) to simulate developers performing pro…

I suspect it isn’t ideal from a usability point of view to have stations on the same metro line called both Vörösmarty tér and Vörösmarty utca.

Not quite a piece of CHERI-cake: Are new digital security by design architectures usable?
Maysara Alhindi, Joseph Hallett
https://arxiv.org/abs/2506.23682 …

Not quite a piece of CHERI-cake: Are new digital security by design architectures usable?
A digital security-by-design computer architecture, like CHERI, lets you program without fear of buffer overflows or other memory safety errors, but CHERI also rewrites some of the assumptions about how C works and how fundamental types (such as pointers) are implemented in hardware. We conducted a usability study to examine how developers react to the changes required by CHERI when porting software to run on it. We find that developers struggle with CHERI's display of warnings and errors and a…

Revisiting Graph Analytics Benchmark
Lingkai Meng, Yu Shao, Long Yuan, Longbin Lai, Peng Cheng, Xue Li, Wenyuan Yu, Wenjie Zhang, Xuemin Lin, Jingren Zhou
https://arxiv.org/abs/2506.21811

Revisiting Graph Analytics Benchmark
The rise of graph analytics platforms has led to the development of various benchmarks for evaluating and comparing platform performance. However, existing benchmarks often fall short of fully assessing performance due to limitations in core algorithm selection, data generation processes (and the corresponding synthetic datasets), as well as the neglect of API usability evaluation. To address these shortcomings, we propose a novel graph analytics benchmark. First, we select eight core algorithm…

The Distributed and Unified Numerics Environment (DUNE), Version 2.10
Markus Blatt, Samuel Burbulla, Ansgar Burchardt, Andreas Dedner, Christian Engwer, Carsten Gr\"aser, Christoph Gr\"uninger, Robert Kl\"ofkorn, Timo Koch, Santiago Ospina De Los R\'ios, Simon Praetorius, Oliver Sander
https://arxiv.org/abs/25…

The Distributed and Unified Numerics Environment (DUNE), Version 2.10
Version 2.10 of the Distributed and Unified Numerics Environment DUNE introduces a range of enhancements across its core and extension modules, with a continued emphasis on modern C++ integration and improved usability. This release extends support for C++20 features, particularly concepts, through comprehensive refinements in dune-common and dune-grid, enabling safer and more expressive generic programming paradigms. A notable advancement is the improved support for curved geometries, includin…

MindChat: Enhancing BCI Spelling with Large Language Models in Realistic Scenarios
JIaheng Wang, Yucun Zhong, Chengjie Huang, Lin Yao
https://arxiv.org/abs/2507.21435 https://…

MindChat: Enhancing BCI Spelling with Large Language Models in Realistic Scenarios
Brain-computer interface (BCI) spellers can render a new communication channel independent of peripheral nervous system, which are especially valuable for patients with severe motor disabilities. However, current BCI spellers often require users to type intended utterances letter-by-letter while spelling errors grow proportionally due to inaccurate electroencephalogram (EEG) decoding, largely impeding the efficiency and usability of BCIs in real-world communication. In this paper, we present Mi…

Apples neue iOS-26-UI: Usability-Probleme und Vista-Nostalgie
Liquid Glass, Apples neues Interface, ist auf dem iPhone eine größere Umstellung als gedacht. Die Beta hakt – und führt zu scherzhaften Microsoft-Vergleichen.

Not Here, Go There: Analyzing Redirection Patterns on the Web
Kritika Garg, Sawood Alam, Dietrich Ayala, Michele C. Weigle, Michael L. Nelson
https://arxiv.org/abs/2507.22019 ht…

Not Here, Go There: Analyzing Redirection Patterns on the Web
URI redirections are integral to web management, supporting structural changes, SEO optimization, and security. However, their complexities affect usability, SEO performance, and digital preservation. This study analyzed 11 million unique redirecting URIs, following redirections up to 10 hops per URI, to uncover patterns and implications of redirection practices. Our findings revealed that 50% of the URIs terminated successfully, while 50% resulted in errors, including 0.06% exceeding 10 hops. …

NerT-CA: Efficient Dynamic Reconstruction from Sparse-view X-ray Coronary Angiography
Kirsten W. H. Maas, Danny Ruijters, Nicola Pezzotti, Anna Vilanova
https://arxiv.org/abs/2507.19328

NerT-CA: Efficient Dynamic Reconstruction from Sparse-view X-ray Coronary Angiography
Three-dimensional (3D) and dynamic 3D+time (4D) reconstruction of coronary arteries from X-ray coronary angiography (CA) has the potential to improve clinical procedures. However, there are multiple challenges to be addressed, most notably, blood-vessel structure sparsity, poor background and blood vessel distinction, sparse-views, and intra-scan motion. State-of-the-art reconstruction approaches rely on time-consuming manual or error-prone automatic segmentations, limiting clinical usability. …

Local Type Inference for Context-Free Session Types
Bernardo Almeida (LASIGE, Faculty of Sciences, University of Lisbon, Portugal), Andreia Mordido (LASIGE, Faculty of Sciences, University of Lisbon, Portugal), Vasco T. Vasconcelos (LASIGE, Faculty of Sciences, University of Lisbon, Portugal)
https://arxiv.org/abs/2505.20855

Local Type Inference for Context-Free Session Types
We address the problem of local type inference for a language based on System F with context-free session types. We present an algorithm that leverages the bidirectional type checking approach to propagate type information, enabling first class polymorphism while addressing the intricacies brought about by the sequential composition operator and type equivalence. The algorithm improves the language's usability by eliminating the need for type annotations at type application sites.

Very excited about this! Code to access GRIN will help lots of Google Books partners, and the example might open other doors, as well as the obvious benefits of access to data!
'Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability' https://arxiv.org/abs/2506…

Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability
Large language models (LLMs) use data to learn about the world in order to produce meaningful correlations and predictions. As such, the nature, scale, quality, and diversity of the datasets used to train these models, or to support their work at inference time, have a direct impact on their quality. The rapid development and adoption of LLMs of varying quality has brought into focus the scarcity of publicly available, high-quality training data and revealed an urgent need to ground the steward…

Your priorities are all out of whack. Give me a private Unix system that's pretty unusable any day of the week.

Examination of Eye-Tracking, Head-Gaze, and Controller-Based Ray-casting in TMT-VR: Performance and Usability Across Adulthood
Panagiotis Kourtesis, Evgenia Giatzoglou, Panagiotis Vorias, Katerina Alkisti Gounari, Eleni Orfanidou, Chrysanthi Nega
https://arxiv.org/abs/2506.19519

Examination of Eye-Tracking, Head-Gaze, and Controller-Based Ray-casting in TMT-VR: Performance and Usability Across Adulthood
Virtual reality (VR) can enrich neuropsychological testing, yet the ergonomic trade-offs of its input modes remain under-examined. Seventy-seven healthy volunteers-young (19-29 y) and middle-aged (27-56 y)-completed a VR Trail-Making Test with three pointing methods: eye-tracking, head-gaze, and a six-degree-of-freedom hand controller. Completion time, spatial accuracy, and error counts for the simple (Trail A) and alternating (Trail B) sequences were analysed in 3 x 2 x 2 mixed-model ANOVAs; p…

Distilling On-device Language Models for Robot Planning with Minimal Human Intervention
Zachary Ravichandran, Ignacio Hounie, Fernando Cladera, Alejandro Ribeiro, George J. Pappas, Vijay Kumar
https://arxiv.org/abs/2506.17486

Distilling On-device Language Models for Robot Planning with Minimal Human Intervention
Large language models (LLMs) provide robots with powerful contextual reasoning abilities and a natural human interface. Yet, current LLM-enabled robots typically depend on cloud-hosted models, limiting their usability in environments with unreliable communication infrastructure, such as outdoor or industrial settings. We present PRISM, a framework for distilling small language model (SLM)-enabled robot planners that run on-device with minimal human supervision. Starting from an existing LLM-ena…

An Online A/B Testing Decision Support System for Web Usability Assessment Based on a Linguistic Decision-making Methodology: Case of Study a Virtual Learning Environment
Noe Zerme\~no, Cristina Zuheros, Lucas Daniel Del Rosso Calache, Francisco Herrera, Rosana Montes
https://arxiv.org/abs/2507.12118

An Online A/B Testing Decision Support System for Web Usability Assessment Based on a Linguistic Decision-making Methodology: Case of Study a Virtual Learning Environment
In recent years, attention has increasingly focused on enhancing user satisfaction with user interfaces, spanning both mobile applications and websites. One fundamental aspect of human-machine interaction is the concept of web usability. In order to assess web usability, the A/B testing technique enables the comparison of data between two designs. Expanding the scope of tests to include the designs being evaluated, in conjunction with the involvement of both real and fictional users, presents a…

Playing in the Sandbox: A Study on the Usability of Seccomp
Maysara Alhindi, Joseph Hallett
https://arxiv.org/abs/2506.10234 https://…

Playing in the Sandbox: A Study on the Usability of Seccomp
Sandboxing restricts what applications do, and prevents exploited processes being abused; yet relatively few applications get sandboxed: why? We report a usability trial with 7 experienced Seccomp developers exploring how they approached sandboxing an application and the difficulties they faced. The developers each approached sandboxing the application differently and each came to different solutions. We highlight many challenges of using Seccomp, the sandboxing designs by the participants, and…

LIVE programming workshop open call: https://liveprog.org/
Deadline 21st July
Get involved!

How Warm-Glow Alters the Usability of Technology
Antonios Saravanos (New York University)
https://arxiv.org/abs/2506.14720 https://ar…

How Warm-Glow Alters the Usability of Technology
As technology increasingly aligns with users' personal values, traditional models of usability, focused on functionality and specifically effectiveness, efficiency, and satisfaction, may not fully capture how people perceive and evaluate it. This study investigates how the warm-glow phenomenon, the positive feeling associated with doing good, shapes perceived usability. An experimental approach was taken in which participants evaluated a hypothetical technology under conditions designed to evok…

Label Unification for Cross-Dataset Generalization in Cybersecurity NER
Maciej Jalocha, Johan Hausted Schmidt, William Michelseen
https://arxiv.org/abs/2507.13870

Label Unification for Cross-Dataset Generalization in Cybersecurity NER
The field of cybersecurity NER lacks standardized labels, making it challenging to combine datasets. We investigate label unification across four cybersecurity datasets to increase data resource usability. We perform a coarse-grained label unification and conduct pairwise cross-dataset evaluations using BiLSTM models. Qualitative analysis of predictions reveals errors, limitations, and dataset differences. To address unification limitations, we propose alternative architectures including a mult…

Usability is like security: if you don't design around it from the very start, when you try to patch it on, unless you get lucky, you'll discover all kinds of architectural commitments that make it really hard, and you'll always play catch-up.

Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch
Lei Liu, Chao Song, Liangsheng He, Silin Wang, Xuan Feng, Cai Liu
https://arxiv.org/abs/2506.20513

Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch
This study proposes a high-performance dual-parameter full waveform inversion framework (FWI) for ground-penetrating radar (GPR), accelerated through the hybrid compilation of CUDA kernel functions and PyTorch. The method leverages the computational efficiency of GPU programming while preserving the flexibility and usability of Python-based deep learning frameworks. By integrating customized CUDA kernels into PyTorch's automatic differentiation mechanism, the framework enables accurate and effi…

#UX designer: Carousels are bad from a usability perspective
Web dev: We have recreated the carousel from the classic research paper "don't use carousels" entirely in #CSS

Carousels with CSS  |  Blog  |  Chrome for Developers
Support scroll experiences with navigation buttons and markers with just a few lines of CSS.

Biases in LLM-Generated Musical Taste Profiles for Recommendation
Bruno Sguerra, Elena V. Epure, Harin Lee, Manuel Moussallam
https://arxiv.org/abs/2507.16708

Biases in LLM-Generated Musical Taste Profiles for Recommendation
One particularly promising use case of Large Language Models (LLMs) for recommendation is the automatic generation of Natural Language (NL) user taste profiles from consumption data. These profiles offer interpretable and editable alternatives to opaque collaborative filtering representations, enabling greater transparency and user control. However, it remains unclear whether users consider these profiles to be an accurate representation of their taste, which is crucial for trust and usability.…

In iOS 26 beta 3, Apple dials back the degree of translucency in many UI elements, following user complaints about Liquid Glass (Sarah Perez/TechCrunch)
https://techcrunch.com/2025/07/07/ios-26-beta-3-dials-back-liquid-glass/

iOS 26 beta 3 dials back Liquid Glass | TechCrunch
The early version in the first developer beta of iOS 26 and the accompanying updates for Apple's other devices still left room for improvement in terms of usability, accessibility, and legibility.

Usability Evaluation of Cloud for HPC Applications
Vanessa Sochat, Daniel Milroy, Abhik Sarkar, Aniruddha Marathe
https://arxiv.org/abs/2506.02709 https://…

Usability Evaluation of Cloud for HPC Applications
The rise of AI and the economic dominance of cloud computing have created a new nexus of innovation for high performance computing (HPC), which has a long history of driving scientific discovery. In addition to performance needs, scientific workflows increasingly demand capabilities of cloud environments: portability, reproducibility, dynamism, and automation. As converged cloud environments emerge, there is growing need to study their fit for HPC use cases. Here we present a cross-platform usa…

Unveiling Usability Challenges in Web Privacy Controls
Rahat Masood, Sunday Oyinlola Ogundoyin, Muhammad Ikram, Alex Ye
https://arxiv.org/abs/2507.11908 ht…

Unveiling Usability Challenges in Web Privacy Controls
With the increasing concerns around privacy and the enforcement of data privacy laws, many websites now provide users with privacy controls. However, locating these controls can be challenging, as they are frequently hidden within multiple settings and layers. Moreover, the lack of standardization means these controls can vary widely across services. The technical or confusing terminology used to describe these controls further complicates users' ability to understand and use them effectively. …

Talking-to-Build: How LLM-Assisted Interface Shapes Player Performance and Experience in Minecraft
Xin Sun, Lei Wang, Yue Li, Jie Li, Massimo Poesio, Julian Frommel, Koen Hinriks, Jiahuan Pei
https://arxiv.org/abs/2507.20300

Talking-to-Build: How LLM-Assisted Interface Shapes Player Performance and Experience in Minecraft
With large language models (LLMs) on the rise, in-game interactions are shifting from rigid commands to natural conversations. However, the impacts of LLMs on player performance and game experience remain underexplored. This work explores LLM's role as a co-builder during gameplay, examining its impact on task performance, usability, and player experience. Using Minecraft as a sandbox, we present an LLM-assisted interface that engages players through natural language, aiming to facilitate creat…

Open-Path Methane Sensing via Backscattered Light in a Nonlinear Interferometer
Jinghan Dong, Weijie Nie, Arthur C. Cardoso, Haichen Zhou, Jingrui Zhang, John G. Rarity, Alex S. Clark
https://arxiv.org/abs/2506.17107

Open-Path Methane Sensing via Backscattered Light in a Nonlinear Interferometer
Nonlinear interferometry has widespread applications in sensing, spectroscopy, and imaging. However, most implementations require highly reflective mirrors and precise optical alignment, drastically reducing their versatility and usability in outdoor applications. This work is based on stimulated parametric down conversion (ST-PDC), demonstrating methane absorption spectroscopy in the mid-infrared (MIR) region by detecting near-infrared (NIR) photons using a silicon-based CMOS camera. The MIR l…

@… @… it’s definitely on the really nice cusp of still very much a hobbyist thing that isn’t heavily monetized yet but the usability of everything is still fairly approachable (imo)

Enhancing Physics Hand-on Lab through Online Educational Tools
Marina Babayeva
https://arxiv.org/abs/2506.16193 https://arxiv.org/pdf…

Enhancing Physics Hand-on Lab through Online Educational Tools
The increasing availability of digital tools for education offers significant opportunities to enhance teaching practices and student engagement. This study presents a structured categorization of online educational tools based on their core functionalities, including content creation, assessment, classroom management, and collaboration. A pilot implementation of selected tools was conducted in secondary-level science education, followed by a refinement phase to address usability and integratio…

Laptop Support and Usability (LSU): May 2025 report from the FreeBSD Foundation
<https://github.com/FreeBSDFoundation/proj-laptop/blob/main/monthly-updates/2025-05.md>
@…

Docmost: Open-source collaborative wiki and documentation software
https://docmost.com
Das klingt ernsthaft gut und würde einige Usability-Probleme des Mediawikis lösen. Unter anderem durch Markdown als Standard und Drag & Drop-Seitenhierarchie.
Realtime-Collaborative-Editing, schicke Ko…

An advanced AI driven database system
M. Tedeschi, S. Rizwan, C. Shringi, V. Devram Chandgir, S. Belich
https://arxiv.org/abs/2507.17778 https://arxiv.org/…

An advanced AI driven database system
Contemporary database systems, while effective, suffer severe issues related to complexity and usability, especially among individuals who lack technical expertise but are unfamiliar with query languages like Structured Query Language (SQL). This paper presents a new database system supported by Artificial Intelligence (AI), which is intended to improve the management of data using natural language processing (NLP) - based intuitive interfaces, and automatic creation of structured queries and s…

Metrology using atoms in an array of double-well potentials
Danish Ali Hamza, Jan Chwede\'nczuk
https://arxiv.org/abs/2507.11395 https://

Metrology using atoms in an array of double-well potentials
Quantum effects, such as entanglement, Einstein-Podolsky-Rosen steering, and Bell correlations, can enhance metrological sensitivity beyond the standard quantum limit. These correlations are typically generated through interactions between atoms or molecules, or during the passage of a laser pulse through a birefringent crystal. Here, we consider an alternative method of generating scalable, many-body entangled states, and demonstrate their usability for quantum-enhanced metrology. Our setup is…

Designing Effective LLM-Assisted Interfaces for Curriculum Development
Abdolali Faraji, Mohammadreza Tavakoli, Mohammad Moein, Mohammadreza Molavi, G\'abor Kismih\'ok
https://arxiv.org/abs/2506.11767

Designing Effective LLM-Assisted Interfaces for Curriculum Development
Large Language Models (LLMs) have the potential to transform the way a dynamic curriculum can be delivered. However, educators face significant challenges in interacting with these models, particularly due to complex prompt engineering and usability issues, which increase workload. Additionally, inaccuracies in LLM outputs can raise issues around output quality and ethical concerns in educational content delivery. Addressing these issues requires careful oversight, best achieved through coopera…

Can GPT-4o Evaluate Usability Like Human Experts? A Comparative Study on Issue Identification in Heuristic Evaluation
Guilherme Guerino, Luiz Rodrigues, Bruna Capeleti, Rafael Ferreira Mello, Andr\'e Freire, Luciana Zaina
https://arxiv.org/abs/2506.16345

Can GPT-4o Evaluate Usability Like Human Experts? A Comparative Study on Issue Identification in Heuristic Evaluation
Heuristic evaluation is a widely used method in Human-Computer Interaction (HCI) to inspect interfaces and identify issues based on heuristics. Recently, Large Language Models (LLMs), such as GPT-4o, have been applied in HCI to assist in persona creation, the ideation process, and the analysis of semi-structured interviews. However, considering the need to understand heuristics and the high degree of abstraction required to evaluate them, LLMs may have difficulty conducting heuristic evaluation…

Semantically Separating Nominal Wyvern for Usability and Decidability
Yu Xiang Zhu, Amos Robinson, Sophia Roshal, Timothy Mou, Julian Mackay, Jonathan Aldrich, Alex Potanin
https://arxiv.org/abs/2507.03867

Semantically Separating Nominal Wyvern for Usability and Decidability
The Dependent Object Types (DOT) calculus incorporates concepts from functional languages (e.g. modules) with traditional object-oriented features (e.g. objects, subtyping) to achieve greater expressivity (e.g. F-bounded polymorphism). However, this merger of paradigms comes at the cost of subtype decidability. Recent work on bringing decidability to DOT has either sacrificed expressiveness or ease of use. The unrestricted construction of recursive types and type bounds has made subtype decidab…

Room Impulse Response Generation Conditioned on Acoustic Parameters
Silvia Arellano, Chunghsin Yeh, Gautam Bhattacharya, Daniel Arteaga
https://arxiv.org/abs/2507.12136

Room Impulse Response Generation Conditioned on Acoustic Parameters
The generation of room impulse responses (RIRs) using deep neural networks has attracted growing research interest due to its applications in virtual and augmented reality, audio postproduction, and related fields. Most existing approaches condition generative models on physical descriptions of a room, such as its size, shape, and surface materials. However, this reliance on geometric information limits their usability in scenarios where the room layout is unknown or when perceptual realism (ho…

Personalized Socially Assistive Robots With End-to-End Speech-Language Models For Well-Being Support
Mengxue Fu, Zhonghao Shi, Minyu Huang, Siqi Liu, Mina Kian, Yirui Song, Maja J. Matari\'c
https://arxiv.org/abs/2507.14412

Personalized Socially Assistive Robots With End-to-End Speech-Language Models For Well-Being Support
Socially assistive robots (SARs) have shown great potential for supplementing well-being support. However, prior studies have found that existing dialogue pipelines for SARs remain limited in real-time latency, back-channeling, and personalized speech dialogue. Toward addressing these limitations, we propose using integrated end-to-end speech-language models (SLMs) with SARs. This work 1) evaluated the usability of an SLM-enabled SAR dialogue system through a small user study, and 2) identified…

The Making of a Community Dark Matter Dataset with the National Science Data Fabric
Amy Roberts, Jack Marquez, Kin Hong NG, Kitty Mickelson, Aashish Panta, Giorgio Scorzelli, Amy Gooch, Prisca Cushman, Matthew Fritts, Himangshu Neog, Valerio Pascucci, Michela Taufer
https://arxiv.org/abs/2507.13297…

The Making of a Community Dark Matter Dataset with the National Science Data Fabric
Dark matter is believed to constitute approximately 85 percent of the universes matter, yet its fundamental nature remains elusive. Direct detection experiments, though globally deployed, generate data that is often locked within custom formats and non-reproducible software stacks, limiting interdisciplinary analysis and innovation. This paper presents a collaboration between the National Science Data Fabric (NSDF) and dark matter researchers to improve accessibility, usability, and scientific …

Rattan: An Extensible and Scalable Modular Internet Path Emulator
Minhu Wang, Yixin Shen, Bo Wang, Haixuan Tong, Yutong Xie, Yixuan Gao, Yan Liu, Li Chen, Mingwei Xu, Jianping Wu
https://arxiv.org/abs/2507.08134

Rattan: An Extensible and Scalable Modular Internet Path Emulator
The rapid growth of Internet paths in heterogeneity, scale, and dynamics has made existing emulators increasingly insufficient in flexibility, scalability, and usability. To address these limitations, we present Rattan, an extensible and scalable software network path emulator for modern Internet conditions. Rattan's core innovation lies in its cell-based architecture: by splitting emulation functions into modular "cells" with well-documented asynchronous interfaces, users are allowed to easily…

This https://arxiv.org/abs/2503.00271 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Why Johnny Signs with Next-Generation Tools: A Usability Case Study of Sigstore
Software signing is the most robust method for ensuring the integrity and authenticity of components in a software supply chain. However, traditional signing tools place key management and signer identification burdens on practitioners, leading to both security vulnerabilities and usability challenges. Next-generation signing tools such as Sigstore have automated some of these concerns, but little is known about their usability and adoption dynamics. This knowledge gap hampers the integration o…

This https://arxiv.org/abs/2505.21907 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy
AI copilots, context-aware, AI-powered systems designed to assist users in tasks such as software development and content creation, are becoming integral to modern workflows. As these systems grow in capability and adoption, personalization has emerged as a cornerstone for ensuring usability, trust, and productivity. Central to this personalization is preference optimization: the ability of AI copilots to detect, interpret, and align with individual user preferences. While personalization techn…

Explainable Vulnerability Detection in C/C Using Edge-Aware Graph Attention Networks
Radowanul Haque, Aftab Ali, Sally McClean, Naveed Khan
https://arxiv.org/abs/2507.16540

Explainable Vulnerability Detection in C/C++ Using Edge-Aware Graph Attention Networks
Detecting security vulnerabilities in source code remains challenging, particularly due to class imbalance in real-world datasets where vulnerable functions are under-represented. Existing learning-based methods often optimise for recall, leading to high false positive rates and reduced usability in development workflows. Furthermore, many approaches lack explainability, limiting their integration into security workflows. This paper presents ExplainVulD, a graph-based framework for vulnerabilit…

EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes
LG AI Research, :, Kyunghoon Bae, Eunbi Choi, Kibong Choi, Stanley Jungkyu Choi, Yemuk Choi, Kyubeen Han, Seokhee Hong, Junwon Hwang, Taewan Hwang, Joonwon Jang, Hyojin Jeon, Kijeong Jeon, Gerrard Jeongwon Jo, Hyunjik Jo, Jiyeon Jung, Euisoon Kim, Hyosang Kim, Jihoon Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Yongil Kim, Youchul Kim, Edward Hwayoung Lee, Gwangho Lee, Ha…

EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes
This technical report introduces EXAONE 4.0, which integrates a Non-reasoning mode and a Reasoning mode to achieve both the excellent usability of EXAONE 3.5 and the advanced reasoning abilities of EXAONE Deep. To pave the way for the agentic AI era, EXAONE 4.0 incorporates essential features such as agentic tool use, and its multilingual capabilities are extended to support Spanish in addition to English and Korean. The EXAONE 4.0 model series consists of two sizes: a mid-size 32B model optimi…

Ten Essential Guidelines for Building High-Quality Research Software
Nasir U. Eisty, David E. Bernholdt, Alex Koufos, David J. Luet, Miranda Mundt
https://arxiv.org/abs/2507.16166

Ten Essential Guidelines for Building High-Quality Research Software
High-quality research software is a cornerstone of modern scientific progress, enabling researchers to analyze complex data, simulate phenomena, and share reproducible results. However, creating such software requires adherence to best practices that ensure robustness, usability, and sustainability. This paper presents ten guidelines for producing high-quality research software, covering every stage of the development lifecycle. These guidelines emphasize the importance of planning, writing cle…

Simulation Everywhere: An Evolutionary Expansion of Discrete-Event Modeling and Simulation research and practice
Ikpe Justice Akpan, Godwin E. Etti
https://arxiv.org/abs/2506.05698

This https://arxiv.org/abs/2506.02709 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Usability Evaluation of Cloud for HPC Applications
The rise of AI and the economic dominance of cloud computing have created a new nexus of innovation for high performance computing (HPC), which has a long history of driving scientific discovery. In addition to performance needs, scientific workflows increasingly demand capabilities of cloud environments: portability, reproducibility, dynamism, and automation. As converged cloud environments emerge, there is growing need to study their fit for HPC use cases. Here we present a cross-platform usa…

Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluation
Ruican Zhong, David W. McDonald, Gary Hsieh
https://arxiv.org/abs/2507.02306

Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluation
Usability evaluation is crucial in human-centered design but can be costly, requiring expert time and user compensation. In this work, we developed a method for synthetic heuristic evaluation using multimodal LLMs' ability to analyze images and provide design feedback. Comparing our synthetic evaluations to those by experienced UX practitioners across two apps, we found our evaluation identified 73% and 77% of usability issues, which exceeded the performance of 5 experienced human evaluators (5…

What is the Best Process Model Representation? A Comparative Analysis for Process Modeling with Large Language Models
Alexis Brissard, Fr\'ed\'eric Cuppens, Amal Zouaq
https://arxiv.org/abs/2507.11356

What is the Best Process Model Representation? A Comparative Analysis for Process Modeling with Large Language Models
Large Language Models (LLMs) are increasingly applied for Process Modeling (PMo) tasks such as Process Model Generation (PMG). To support these tasks, researchers have introduced a variety of Process Model Representations (PMRs) that serve as model abstractions or generation targets. However, these PMRs differ widely in structure, complexity, and usability, and have never been systematically compared. Moreover, recent PMG approaches rely on distinct evaluation strategies and generation techniqu…

This https://arxiv.org/abs/2406.13945 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks
As large language models (LLMs) continue to advance and gain widespread use, establishing systematic and reliable evaluation methodologies for LLMs and vision-language models (VLMs) has become essential to ensure their real-world effectiveness and reliability. There have been some early explorations about the usability of LLMs for limited urban tasks, but a systematic and scalable evaluation benchmark is still lacking. The challenge in constructing a systematic evaluation benchmark for urban re…

MD-ViSCo: A Unified Model for Multi-Directional Vital Sign Waveform Conversion
Franck Meyer, Kyunghoon Hur, Edward Choi
https://arxiv.org/abs/2506.08357 ht…

MD-ViSCo: A Unified Model for Multi-Directional Vital Sign Waveform Conversion
Despite the remarkable progress of deep-learning methods generating a target vital sign waveform from a source vital sign waveform, most existing models are designed exclusively for a specific source-to-target pair. This requires distinct model architectures, optimization procedures, and pre-processing pipelines, resulting in multiple models that hinder usability in clinical settings. To address this limitation, we propose the Multi-Directional Vital-Sign Converter (MD-ViSCo), a unified framewo…

Tady: A Neural Disassembler without Structural Constraint Violations
Siliang Qin, Fengrui Yang, Hao Wang, Bolun Zhang, Zeyu Gao, Chao Zhang, Kai Chen
https://arxiv.org/abs/2506.13323

Tady: A Neural Disassembler without Structural Constraint Violations
Disassembly is a crucial yet challenging step in binary analysis. While emerging neural disassemblers show promise for efficiency and accuracy, they frequently generate outputs violating fundamental structural constraints, which significantly compromise their practical usability. To address this critical problem, we regularize the disassembly solution space by formalizing and applying key structural constraints based on post-dominance relations. This approach systematically detects widespread e…

A Concurrent Multiscale Framework Coupling Direct Simulation Monte Carlo and Molecular Dynamics
Tim Linke, Dane Sterbentz, Niels Gr{\o}nbech-Jensen, Jean-Pierre Delplanque, Jonathan Belof
https://arxiv.org/abs/2506.01924

A Concurrent Multiscale Framework Coupling Direct Simulation Monte Carlo and Molecular Dynamics
We present a new method to couple the Direct Simulation Monte Carlo (DSMC) algorithm with molecular dynamics (MD). The coupling approach generalizes prior coupling methods using a cell-based decision. The approach is supported by a lifting and restricting operator, which translate length and time scales between DSMC and MD. We verify the framework on basic conservation laws, and demonstrate its usability on a hypersonic flow example. Its accuracy gain is discussed in light of conventional DSMC …

From Screen to Space: Evaluating Siemens' Cinematic Reality
Gijs Luijten, Lisle Faray de Paiva, Sebastian Krueger, Alexander Brost, Laura Mazilescu, Ana Sofia Ferreira Santos, Peter Hoyer, Jens Kleesiek, Sophia Marie-Therese Schmitz, Ulf Peter Neumann, Jan Egger
https://arxiv.org/abs/2506.04972…

From Screen to Space: Evaluating Siemens' Cinematic Reality
As one of the first research teams with full access to Siemens' Cinematic Reality, we evaluate its usability and clinical potential for cinematic volume rendering on the Apple Vision Pro. We visualized venous-phase liver computed tomography and magnetic resonance cholangiopancreatography scans from the CHAOS and MRCP\_DLRecon datasets. Fourteen medical experts assessed usability and anticipated clinical integration potential using the System Usability Scale, ISONORM 9242-110-S questionnaire, an…

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey
Ina K. Schieferdecker
https://arxiv.org/abs/2506.14640

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey
In industry, software testing is the primary method to verify and validate the functionality, performance, security, usability, and so on, of software-based systems. Test automation has gained increasing attention in industry over the last decade, following decades of intense research into test automation and model-based testing. However, designing, developing, maintaining and evolving test automation is a considerable effort. Meanwhile, AI's breakthroughs in many engineering fields are opening…

Learn Like Feynman: Developing and Testing an AI-Driven Feynman Bot
Akshaya Rajesh, Sumbul Khan
https://arxiv.org/abs/2506.09055 https://

Learn Like Feynman: Developing and Testing an AI-Driven Feynman Bot
The Feynman learning technique is an active learning strategy that helps learners simplify complex information through student-led teaching and discussion. In this paper, we present the development and usability testing of the Feynman Bot, which uses the Feynman technique to assist self-regulated learners who lack peer or instructor support. The Bot embodies the Feynman learning technique by encouraging learners to discuss their lecture material in a question-answer-driven discussion format. Th…

Mindfulness Meditation and Respiration: Accelerometer-Based Respiration Rate and Mindfulness Progress Estimation to Enhance App Engagement and Mindfulness Skills
Mohammad Nur Hossain Khan, David creswell, Jordan Albert, Patrick O'Connell, Shawn Fallon, Mathew Polowitz, Xuhai "orson" Xu, Bashima islam
https://arxiv.org/abs/250…

Mindfulness Meditation and Respiration: Accelerometer-Based Respiration Rate and Mindfulness Progress Estimation to Enhance App Engagement and Mindfulness Skills
Mindfulness training is widely recognized for its benefits in reducing depression, anxiety, and loneliness. With the rise of smartphone-based mindfulness apps, digital meditation has become more accessible, but sustaining long-term user engagement remains a challenge. This paper explores whether respiration biosignal feedback and mindfulness skill estimation enhance system usability and skill development. We develop a smartphone's accelerometer-based respiration tracking algorithm, eliminating …

Tady: A Neural Disassembler without Structural Constraint Violations
Siliang Qin, Fengrui Yang, Hao Wang, Bolun Zhang, Zeyu Gao, Chao Zhang, Kai Chen
https://arxiv.org/abs/2506.13323

Tady: A Neural Disassembler without Structural Constraint Violations
Disassembly is a crucial yet challenging step in binary analysis. While emerging neural disassemblers show promise for efficiency and accuracy, they frequently generate outputs violating fundamental structural constraints, which significantly compromise their practical usability. To address this critical problem, we regularize the disassembly solution space by formalizing and applying key structural constraints based on post-dominance relations. This approach systematically detects widespread e…

CueLearner: Bootstrapping and local policy adaptation from relative feedback
Giulio Schiavi, Andrei Cramariuc, Lionel Ott, Roland Siegwart
https://arxiv.org/abs/2507.04730

CueLearner: Bootstrapping and local policy adaptation from relative feedback
Human guidance has emerged as a powerful tool for enhancing reinforcement learning (RL). However, conventional forms of guidance such as demonstrations or binary scalar feedback can be challenging to collect or have low information content, motivating the exploration of other forms of human input. Among these, relative feedback (i.e., feedback on how to improve an action, such as "more to the left") offers a good balance between usability and information richness. Previous research has shown th…

Classification of Quality Characteristics in Online User Feedback using Linguistic Analysis, Crowdsourcing and LLMs
Eduard C. Groen, Fabiano Dalpiaz, Martijn van Vliet, Boris Winter, Joerg Doerr, Sjaak Brinkkemper
https://arxiv.org/abs/2506.11722

Classification of Quality Characteristics in Online User Feedback using Linguistic Analysis, Crowdsourcing and LLMs
Software qualities such as usability or reliability are among the strongest determinants of mobile app user satisfaction and constitute a significant portion of online user feedback on software products, making it a valuable source of quality-related feedback to guide the development process. The abundance of online user feedback warrants the automated identification of quality characteristics, but the online user feedback's heterogeneity and the lack of appropriate training corpora limit the a…

New preprint "Survey on the Evaluation of Generative Models in Music:" https://arxiv.org/abs/2506.05104
Despite the rapid progress in generative music models, evaluating these systems remains a major challenge. In this survey, we:
✅ Outline key evaluation targets
✅ Compare methodolog…

Survey on the Evaluation of Generative Models in Music
Research on generative systems in music has seen considerable attention and growth in recent years. A variety of attempts have been made to systematically evaluate such systems. We provide an interdisciplinary review of the common evaluation targets, methodologies, and metrics for the evaluation of both system output and model usability, covering subjective and objective approaches, qualitative and quantitative approaches, as well as empirical and computational methods. We discuss the advantage…

Designing at 1:1 Scale on Wall-Sized Displays Using Existing UI Design Tools
Lou Schwartz, Mohammad Ghoniem, Val\'erie Maquil, Adrien Coppens, Johannes Hermen
https://arxiv.org/abs/2507.15433

Designing at 1:1 Scale on Wall-Sized Displays Using Existing UI Design Tools
Wall-Sized Displays have spatial characteristics that are difficult to address during user interface design. The design at scale 1:1 could be part of the solution. In this paper, we present the results of two user studies and one technology review, exploring the usability of popular, desktop-optimized prototyping tools, for designing at scale on Wall-Sized Displays. We considered two wall-sized display setups, and three different interaction methods: touch, a keyboard equipped with a touchpad, …

Survey on the Evaluation of Generative Models in Music
Alexander Lerch, Claire Arthur, Nick Bryan-Kinns, Corey Ford, Qianyi Sun, Ashvala Vinay
https://arxiv.org/abs/2506.05104

Survey on the Evaluation of Generative Models in Music
Research on generative systems in music has seen considerable attention and growth in recent years. A variety of attempts have been made to systematically evaluate such systems. We provide an interdisciplinary review of the common evaluation targets, methodologies, and metrics for the evaluation of both system output and model usability, covering subjective and objective approaches, qualitative and quantitative approaches, as well as empirical and computational methods. We discuss the advantage…

Designing Deep Learning Frameworks for LLMs:Challenges, Expectations, and Opportunities
Yanzhou Mu, Rong Wang, Juan Zhai, Chunrong Fang, Xiang Chen, Jiacong Wu, An Guo, Jiawei Shen, Bingzhuo Li, Zhenyu Chen
https://arxiv.org/abs/2506.13114

Designing Deep Learning Frameworks for LLMs:Challenges, Expectations, and Opportunities
Large language models (LLMs) drive significant advancements in real industry applications. LLMs rely on DL frameworks for efficient model construction, distributed execution, and optimized deployment. Their large parameter scale and long execution cycles place extreme demands on DL frameworks in terms of scalability, stability, and efficiency. Therefore, poor usability, limited functionality, and subtle bugs in DL frameworks may hinder development efficiency and cause severe failures or resourc…

Template-Based Schema Matching of Multi-Layout Tenancy Schedules:A Comparative Study of a Template-Based Hybrid Matcher and the ALITE Full Disjunction Model
Tim Uilkema, Yao Ma, Seyed Sahand Mohammadi Ziabari, Joep van Vliet
https://arxiv.org/abs/2507.02020

Template-Based Schema Matching of Multi-Layout Tenancy Schedules:A Comparative Study of a Template-Based Hybrid Matcher and the ALITE Full Disjunction Model
The lack of standardized tabular formats for tenancy schedules across real estate firms creates significant inefficiencies in data integration. Existing automated integration methods, such as Full Disjunction (FD)-based models like ALITE, prioritize completeness but result in schema bloat, sparse attributes and limited business usability. We propose a novel hybrid, template-based schema matcher that aligns multi-layout tenancy schedules to a predefined target schema. The matcher combines schema…

This https://arxiv.org/abs/2503.16920 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Assessing AI Explainability: A Usability Study Using a Novel Framework Involving Clinicians
An AI design framework was developed based on three core principles, namely understandability, trust, and usability. The framework was conceptualized by synthesizing evidence from the literature and by consulting with experts. The initial version of the AI Explainability Framework was validated based on an in-depth expert engagement and review process. For evaluation purposes, an AI-anchored prototype, incorporating novel explainability features, was built and deployed online. The primary funct…

A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare
Ivania Donoso-Guzm\'an, Krist\'yna Sirka Kacaf\'irkov\'a, Maxwell Szymanski, An Jacobs, Denis Parra, Katrien Verbert
https://arxiv.org/abs/2506.13904

A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare
Despite promising developments in Explainable Artificial Intelligence, the practical value of XAI methods remains under-explored and insufficiently validated in real-world settings. Robust and context-aware evaluation is essential, not only to produce understandable explanations but also to ensure their trustworthiness and usability for intended users, but tends to be overlooked because of no clear guidelines on how to design an evaluation with users. This study addresses this gap with two ma…

Translating a VDM Model of a Medical Device into Kapture
Joe Hare, Leo Freitas, Ken Pierce
https://arxiv.org/abs/2506.09636 https://a…

Translating a VDM Model of a Medical Device into Kapture
As the complexity of safety-critical medical devices increases, so does the need for clear, verifiable, software requirements. This paper explores the use of Kapture, a formal modelling tool developed by D-RisQ, to translate an existing formal VDM model of a medical implant for treating focal epilepsy called CANDO. The work was undertaken without prior experience in formal methods. The paper assess Kapture's usability, the challenges of formal modelling, and the effectiveness of the translated …

Multimodal "Puppeteer": An Exploration of Robot Teleoperation Via Virtual Counterpart with LLM-Driven Voice and Gesture Interaction in Augmented Reality
Yuchong Zhang, Bastian Orthmann, Shichen Ji, Michael Welle, Jonne Van Haastregt, Danica Kragic
https://arxiv.org/abs/2506.13189…

Multimodal "Puppeteer": An Exploration of Robot Teleoperation Via Virtual Counterpart with LLM-Driven Voice and Gesture Interaction in Augmented Reality
The integration of robotics and augmented reality (AR) holds transformative potential for advancing human-robot interaction (HRI), offering enhancements in usability, intuitiveness, accessibility, and collaborative task performance. This paper introduces and evaluates a novel multimodal AR-based robot puppeteer framework that enables intuitive teleoperation via virtual counterpart through large language model (LLM)-driven voice commands and hand gesture interactions. Utilizing the Meta Quest 3,…

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Bao Zhang, Zihan Li, Zhenglei Liu, Huanchen Wang, Yuxin Ma
https://arxiv.org/abs/2506.10762

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Text animation, a foundational element in video creation, enables efficient and cost-effective communication, thriving in advertisements, journalism, and social media. However, traditional animation workflows present significant usability barriers for non-professionals, with intricate operational procedures severely hindering creative productivity. To address this, we propose a Large Language Model (LLM)-aided text animation editing system that enables real-time intent tracking and flexible edi…

Beyond the Desktop: XR-Driven Segmentation with Meta Quest 3 and MX Ink
Lisle Faray de Paiva, Gijs Luijten, Ana Sofia Ferreira Santos, Moon Kim, Behrus Puladi, Jens Kleesiek, Jan Egger
https://arxiv.org/abs/2506.04858

Beyond the Desktop: XR-Driven Segmentation with Meta Quest 3 and MX Ink
Medical imaging segmentation is essential in clinical settings for diagnosing diseases, planning surgeries, and other procedures. However, manual annotation is a cumbersome and effortful task. To mitigate these aspects, this study implements and evaluates the usability and clinical applicability of an extended reality (XR)-based segmentation tool for anatomical CT scans, using the Meta Quest 3 headset and Logitech MX Ink stylus. We develop an immersive interface enabling real-time interaction w…