Tootfinder

Scale AI launches SEAL Showdown, a public AI benchmarking system that relies on votes from contributors in 100 countries to gauge everyday usability of models (Agnee Ghosh/Bloomberg)
https://www.bloomberg.com/news/articles/20…

BEFT: Bias-Efficient Fine-Tuning of Language Models
Baichuan Huang, Ananth Balashankar, Amir Aminifar
https://arxiv.org/abs/2509.15974 https://arxiv.org/pd…

BEFT: Bias-Efficient Fine-Tuning of Language Models
Fine-tuning all-bias-terms stands out among various parameter-efficient fine-tuning (PEFT) techniques, owing to its out-of-the-box usability and competitive performance, especially in low-data regimes. Bias-only fine-tuning has the potential for unprecedented parameter efficiency. However, the link between fine-tuning different bias terms (i.e., bias terms in the query, key, or value projections) and downstream performance remains unclear. The existing approaches, e.g., based on the magnitude o…

PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments
Bernd Hofmann, Albert Scheck, Joerg Franke, Patrick Bruendl
https://arxiv.org/abs/2508.14504

PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments
The detection of anomalies in manufacturing processes is crucial to ensure product quality and identify process deviations. Statistical and data-driven approaches remain the standard in industrial anomaly detection, yet their adaptability and usability are constrained by the dependence on extensive annotated datasets and limited flexibility under dynamic production conditions. Recent advances in the perception capabilities of foundation models provide promising opportunities for their adaptatio…

You Don't Know Until You Click:Automated GUI Testing for Production-Ready Software Evaluation
Yutong Bian, Xianhao Lin, Yupeng Xie, Tianyang Liu, Mingchen Zhuge, Siyuan Lu, Haoming Tang, Jinlin Wang, Jiayi Zhang, Jiaqi Chen, Xiangru Tang, Yongxin Ni, Sirui Hong, Chenglin Wu
https://arxiv.org/abs/2508.14104

You Don't Know Until You Click:Automated GUI Testing for Production-Ready Software Evaluation
Large Language Models (LLMs) and code agents in software development are rapidly evolving from generating isolated code snippets to producing full-fledged software applications with graphical interfaces, interactive logic, and dynamic behaviors. However, current benchmarks fall short in evaluating such production-ready software, as they often rely on static checks or binary pass/fail scripts, failing to capture the interactive behaviors and runtime dynamics that define real-world usability - qu…

Evaluating an Immersive Analytics Application at an Enterprise Business Intelligence Customer Conference
Matthew Brehmer, Ginger Gloystein, Bailiang Zhou, Abby Gray, Sruthi Pillai, Ben Medina, Vidya Setlur
https://arxiv.org/abs/2508.15152

Evaluating an Immersive Analytics Application at an Enterprise Business Intelligence Customer Conference
We reflect on an evaluation of an immersive analytics application (Tableau for visionOS) conducted at a large enterprise business intelligence (BI) conference. Conducting a study in such a context offered an opportunistic setting to gather diverse feedback. However, this setting also highlighted the challenge of evaluating usability while also assessing potential utility, as feedback straddled between the novelty of the experience and the practicality of the application in participants' analyti…

Systematic FAIRness Assessment of Open Voice Biomarker Datasets for Mental Health and Neurodegenerative Diseases
Ishaan Mahapatra, Nihar R. Mahapatra
https://arxiv.org/abs/2508.14089

Systematic FAIRness Assessment of Open Voice Biomarker Datasets for Mental Health and Neurodegenerative Diseases
Voice biomarkers--human-generated acoustic signals such as speech, coughing, and breathing--are promising tools for scalable, non-invasive detection and monitoring of mental health and neurodegenerative diseases. Yet, their clinical adoption remains constrained by inconsistent quality and limited usability of publicly available datasets. To address this gap, we present the first systematic FAIR (Findable, Accessible, Interoperable, Reusable) evaluation of 27 publicly available voice biomarker d…

Usability vs. Cost. https://social.heise.de/@heiseautos/115055162848701309

Theorem Provers: One Size Fits All?
Harrison Oates, Hyeonggeun Yun, Nikhila Gurusinghe
https://arxiv.org/abs/2509.15015 https://arxiv.org/pdf/2509.15015

Theorem Provers: One Size Fits All?
Theorem provers are important tools for people working in formal verification. There are a myriad of interactive systems available today, with varying features and approaches motivating their development. These design choices impact their usability, alongside the problem domain in which they are employed. We test-drive two such provers, Coq and Idris2, by proving the correctness of insertion sort, before providing a qualitative evaluation of their performance. We then compare their community an…

VerilogLAVD: LLM-Aided Rule Generation for Vulnerability Detection in Verilog
Xiang Long, Yingjie Xia, Xiyuan Chen, Li Kuang
https://arxiv.org/abs/2508.13092 https://

VerilogLAVD: LLM-Aided Rule Generation for Vulnerability Detection in Verilog
Timely detection of hardware vulnerabilities during the early design stage is critical for reducing remediation costs. Existing early detection techniques often require specialized security expertise, limiting their usability. Recent efforts have explored the use of large language models (LLMs) for Verilog vulnerability detection. However, LLMs struggle to capture the structure in Verilog code, resulting in inconsistent detection results. To this end, we propose VerilogLAVD, the first LLM-aided…

Been busy updating the #Trajectools archival records over at #SDSL2025

The Anatomy of Alignment: Decomposing Preference Optimization by Steering Sparse Features
Jeremias Ferrao, Matthijs van der Lende, Ilija Lichkovski, Clement Neo
https://arxiv.org/abs/2509.12934

The Anatomy of Alignment: Decomposing Preference Optimization by Steering Sparse Features
Aligning large language models is critical for their usability and safety. However, the prevailing approach of Reinforcement Learning from Human Feedback (RLHF) induces diffuse, opaque parameter changes, making it difficult to discern what the model has internalized. Hence, we introduce Feature Steering with Reinforcement Learning (FSRL), a transparent alignment framework that trains a lightweight adapter to steer behavior by modulating interpretable features from a Sparse Autoencoder (SAE). Fi…

Vision Pro: In dieser Nische verkauft sie sich gut
4000 Euro Mindestpreis, dazu Usability-Nachteile: Die Vision Pro gilt nicht als Hit. Doch bestimmte Firmengeschäfte laufen gut, so ein Bericht.
https://www.

Design-Space Exploration of Distributed Neural Networks in Low-Power Wearable Nodes
Meghna Roy Chowdhury, Ming-che Li, Archisman Ghosh, Md Faizul Bari, Shreyas Sen
https://arxiv.org/abs/2509.14540

Design-Space Exploration of Distributed Neural Networks in Low-Power Wearable Nodes
Wearable devices are revolutionizing personal technology, but their usability is often hindered by frequent charging due to high power consumption. This paper introduces Distributed Neural Networks (DistNN), a framework that distributes neural network computations between resource-constrained wearable nodes and resource-rich hubs to reduce energy at the node without sacrificing performance. We define a Figure of Merit (FoM) to select the optimal split point that minimizes node-side energy. A cu…

CosmicWatch: The Desktop Muon Detector(v3X)
Spencer Axani, Masooma Sarfraz, Miles Garcia, Collin Owens, Katarzyna Frankiewicz, Janet M. Conrad
https://arxiv.org/abs/2508.12111 h…

CosmicWatch: The Desktop Muon Detector(v3X)
The CosmicWatch Desktop Muon Detector (v3X) is a compact, low-cost, and portable device designed for detecting ionizing radiation, including cosmic-ray muons. Building on previous iterations, the v3X introduces significant hardware and firmware improvements that enhance sensitivity, usability, and data acquisition capabilities. The detector integrates a plastic scintillator and silicon photomultiplier (SiPM), custom designed electronics for signal processing, onboard data storage, OLED display,…

@… some German cities built very expensive bike storage
Of course they built them in shitty locations and with bad usability
And then are confused why nobody uses them

Millionengräber: Fahrrad-Parkhäuser in Bonn und Leverkusen bleiben leer
In der Theorie klingt es super: Das Fahrrad für wenig Geld sicher abstellen. Nur wird das Angebot nicht genutzt.

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security
Yanrui Du, Fenglei Fan, Sendong Zhao, Jiawei Cao, Ting Liu, Bing Qin
https://arxiv.org/abs/2509.06807

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security
As Large Language Models (LLMs) increasingly permeate human life, their security has emerged as a critical concern, particularly their ability to maintain harmless responses to malicious instructions. Although extensive methods have improved LLMs' security, they often lead to conservative, rejection-oriented responses that compromise practical usability. This presents a key challenge: how to advance the Pareto frontier between LLMs' usability and security, rather than necessitate a trade-off be…

macOS 26 Tahoe review: Liquid Glass has small regressions in usability and accessibility but the upgrade has enough iterative changes like automated Shortcuts (Andrew Cunningham/Ars Technica)
https://arstechnica.com/gadgets/2025/09/macos-26-tahoe-the-ars-techn…

macOS 26 Tahoe: The Ars Technica Review
Liquid Glass brings translucent sheen to the typical batch of iterative changes.

I wonder how it comes that people do not "contribute" to open source, but mutilate it. From version 4.9 to version 5.2 the contributors managed to destroy usability and consistency checking in kmymoney. Maybe this is done deliberately by those offering commercial options? (Conspiracy vs just human stupidity). I'm not amused, because it is then hard to keep it out of the updates.

Choosing the Right Engine in the Virtual Reality Landscape
Santiago Berrezueta-Guzman, Stefan Wagner
https://arxiv.org/abs/2508.13116 https://arxiv.org/pdf…

Choosing the Right Engine in the Virtual Reality Landscape
Virtual reality (VR) development relies on game engines to provide real-time rendering, physics simulation, and interaction systems. Among the most widely used game engines, Unreal Engine and Unity dominate the industry, offering distinct advantages in graphics rendering, performance optimization, usability, resource requirements, and scalability. This study presents a comprehensive comparative analysis of both engines, evaluating their capabilities and trade-offs through empirical assessments …

FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification
Prajit Sengupta, Islem Rekik
https://arxiv.org/abs/2509.10510

FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification
Medical image classification requires not only high predictive performance but also interpretability to ensure clinical trust and adoption. Graph Neural Networks (GNNs) offer a powerful framework for modeling relational structures within datasets; however, standard GNNs often operate as black boxes, limiting transparency and usability, particularly in clinical settings. In this work, we present an interpretable graph-based learning framework named FireGNN that integrates trainable fuzzy rules i…

One of my most useful tools these days are things that take screenshots. Greenshot, a Windows tool with excellent usability. And Powertools Text Extractor which lets me OCR bits of text on the screen. Usability is important here: press one button and stuff is copied to clipboard.

Would you let a humanoid play storytelling with your child? A usability study on LLM-powered narrative Humanoid-Robot Interaction
Maria Lombardi, Carmela Calabrese, Davide Ghiglino, Caterina Foglino, Davide De Tommaso, Giulia Da Lisca, Lorenzo Natale, Agnieszka Wykowska
https://arxiv.org/abs/2508.02505…

Would you let a humanoid play storytelling with your child? A usability study on LLM-powered narrative Humanoid-Robot Interaction
A key challenge in human-robot interaction research lies in developing robotic systems that can effectively perceive and interpret social cues, facilitating natural and adaptive interactions. In this work, we present a novel framework for enhancing the attention of the iCub humanoid robot by integrating advanced perceptual abilities to recognise social cues, understand surroundings through generative models, such as ChatGPT, and respond with contextually appropriate social behaviour. Specifical…

Laptop Support and Usability (LSU): August 2025 report from the FreeBSD Foundation
https://github.com/FreeBSDFoundation/proj-laptop/blob/main/monthly-updates/2025-08.md
@…

Was mich bis heute seit dem Umstieg auf Mint nervt, ist, dass es keine keine einheitlich Pfadwahl gibt.
Bei manchen Tools muss ich erst CTRL . oder CTRL L (keine Ahnung wann welches) wählen, bevor ich einen Pfad im Dialog (entpacken, speichern, öffnen) einfügen kann. Unter Windows funktioniert in 99% der Fälle einfach CTRL V und enter
Ist so eine Usability-Kleinigkeit, aber eine, die immer wieder auffällt.

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal
Haonan Zhang, Dongxia Wang, Yi Liu, Kexin Chen, Jiashui Wang, Xinlei Ying, Long Liu, Wenhai Wang
https://arxiv.org/abs/2508.11222

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal
Large Language Models (LLMs) increasingly exhibit over-refusal - erroneously rejecting benign queries due to overly conservative safety measures - a critical functional flaw that undermines their reliability and usability. Current methods for testing this behavior are demonstrably inadequate, suffering from flawed benchmarks and limited test generation capabilities, as highlighted by our empirical user study. To the best of our knowledge, this paper introduces the first evolutionary testing fra…

Maestro: Self-Improving Text-to-Image Generation via Agent Orchestration
Xingchen Wan, Han Zhou, Ruoxi Sun, Hootan Nakhost, Ke Jiang, Rajarishi Sinha, Sercan \"O. Ar{\i}k
https://arxiv.org/abs/2509.10704

Maestro: Self-Improving Text-to-Image Generation via Agent Orchestration
Text-to-image (T2I) models, while offering immense creative potential, are highly reliant on human intervention, posing significant usability challenges that often necessitate manual, iterative prompt engineering over often underspecified prompts. This paper introduces Maestro, a novel self-evolving image generation system that enables T2I models to autonomously self-improve generated images through iterative evolution of prompts, using only an initial prompt. Maestro incorporates two key innov…

Targeted Sequential Pattern Mining with High Average Utility
Kai Cao, Yucong Duan, Wensheng Gan
https://arxiv.org/abs/2510.10115 https://arxiv.org/pdf/2510…

Targeted Sequential Pattern Mining with High Average Utility
Incorporating utility into targeted pattern mining can address the practical limitations of traditional frequency-based approaches. However, utility-based methods often suffer from generating a large number of long and complicated sequences. To improve pattern relevance and interpretability, average utility provides a more balanced metric by considering both utility and sequence length. Moreover, incorporating user-defined query targets into the mining process enhances usability and interactivi…

Towards Experience-Centered AI: A Framework for Integrating Lived Experience in Design and Development
Sanjana Gautam, Mohit Chandra, Ankolika De, Tatiana Chakravorti, Girik Malik, Munmun De Choudhury
https://arxiv.org/abs/2508.06849

Towards Experience-Centered AI: A Framework for Integrating Lived Experience in Design and Development
Lived experiences fundamentally shape how individuals interact with AI systems, influencing perceptions of safety, trust, and usability. While prior research has focused on developing techniques to emulate human preferences, and proposed taxonomies to categorize risks (such as psychological harms and algorithmic biases), these efforts have provided limited systematic understanding of lived human experiences or actionable strategies for embedding them meaningfully into the AI development lifecyc…

The Cost of Simplicity: How Reducing EEG Electrodes Affects Source Localization and BCI Accuracy
Eva Guttmann-Flury, Yanyan Wei, Shan Zhao, Jian Zhao, Mohamad Sawan
https://arxiv.org/abs/2510.10770

The Cost of Simplicity: How Reducing EEG Electrodes Affects Source Localization and BCI Accuracy
Electrode density optimization in electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) requires balancing practical usability against signal fidelity, particularly for source localization. Reducing electrodes enhances portability but its effects on neural source reconstruction quality and source connectivity - treated as proxies to BCI performance - remain understudied. We address this gap through systematic evaluation of 62-, 32-, and 16-channel configurations using a fixed, ful…

Oh fun find, there was actually something called Oxide in the history of #Rust already - a formalization attempt:
https://arxiv.org/abs/1903.00982 🦀
cc @…

Oxide: The Essence of Rust
Rust claims to advance industrial programming by bridging the gap between low-level systems programming and high-level application programming. At the heart of the argument that this enables programmers to build more reliable and efficient software is the borrow checker - a novel approach to ownership that aims to balance type system expressivity with usability. And yet, to date there is no core type system that captures Rust's notion of ownership and borrowing, and hence no foundation for rese…

Fanatics, I am once again boosting this into the void for your edification.
https://mas.to/@markwyner/109797687993819959

Weekend Reads
* URI redirection patterns https://arxiv.org/abs/2507.22019
* AI and college grad jobs https://www.

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. …

Replaced article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[1/1]:
- TRIP: Coercion-resistant Registration for E-Voting with Verifiability and Usability in Votegral
Henri Merino, et al.

Beyond Blanket Masking: Examining Granularity for Privacy Protection in Images Captured by Blind and Low Vision Users
Jeffri Murrugarra-LLerena, Haoran Niu, K. Suzanne Barber, Hal Daum\'e III, Yang Trista Cao, Paola Cascante-Bonilla
https://arxiv.org/abs/2508.09245

Beyond Blanket Masking: Examining Granularity for Privacy Protection in Images Captured by Blind and Low Vision Users
As visual assistant systems powered by visual language models (VLMs) become more prevalent, concerns over user privacy have grown, particularly for blind and low vision users who may unknowingly capture personal private information in their images. Existing privacy protection methods rely on coarse-grained segmentation, which uniformly masks entire private objects, often at the cost of usability. In this work, we propose FiGPriv, a fine-grained privacy protection framework that selectively mask…

'Bound to browsable' - love this detailed overview of the work that goes into making specific formats (like magazines) more findable in online catalogues https://blogs.loc.gov/thesignal/2025/09/unlocking-historical-media-publications/

Bound to Browsable: Unlocking the Historical Media Publications Collection | The Signal
This post details the exciting transformation of the Historical Media Publications Collection, a challenging digital collection of historical media industry magazines spanning the late 19th to mid-20th century. Expanding online presentation from dense bound volumes into searchable, issue-level resources, this collaborative project improved discoverability and usability of this collection and set a foundation for working with other serialized content though innovative new workflows and next-gene…

Towards Recommending Usability Improvements with Multimodal Large Language Models
Sebastian Lubos, Alexander Felfernig, Gerhard Leitner, Julian Schwazer
https://arxiv.org/abs/2508.16165

Towards Recommending Usability Improvements with Multimodal Large Language Models
Usability describes a set of essential quality attributes of user interfaces (UI) that influence human-computer interaction. Common evaluation methods, such as usability testing and inspection, are effective but resource-intensive and require expert involvement. This makes them less accessible for smaller organizations. Recent advances in multimodal LLMs offer promising opportunities to automate usability evaluation processes partly by analyzing textual, visual, and structural aspects of softwa…

Development of aiocoap, my Python CoAP library, is approaching its next breaking release.
If there's anything about its usability as a library that has been bugging you, especially if it would require breaking changes: Let me know soon, either here or on the issue tracker at https://github.com/chrysn/aiocoap/issu

chrysn/aiocoap
The Python CoAP library. Contribute to chrysn/aiocoap development by creating an account on GitHub.

Interpretable Robot Control via Structured Behavior Trees and Large Language Models
Ingrid Ma\'eva Chekam, Ines Pastor-Martinez, Ali Tourani, Jose Andres Millan-Romera, Laura Ribeiro, Pedro Miguel Bastos Soares, Holger Voos, Jose Luis Sanchez-Lopez
https://arxiv.org/abs/2508.09621

Interpretable Robot Control via Structured Behavior Trees and Large Language Models
As intelligent robots become more integrated into human environments, there is a growing need for intuitive and reliable Human-Robot Interaction (HRI) interfaces that are adaptable and more natural to interact with. Traditional robot control methods often require users to adapt to interfaces or memorize predefined commands, limiting usability in dynamic, unstructured environments. This paper presents a novel framework that bridges natural language understanding and robotic execution by combinin…

VCO-CARE: VCO-based Calibration-free Analog Readout for Electrodermal activity sensing
Leidy Mabel Alvero-Gonzalez, Matias Miguez, Eric Gutierrez, Juan Sapriza, Susana Pat\'on, David Atienza, Jos\'e Miranda
https://arxiv.org/abs/2509.06698

VCO-CARE: VCO-based Calibration-free Analog Readout for Electrodermal activity sensing
Continuous monitoring of electrodermal activity (EDA) through wearable devices has attracted much attention in recent times. However, the persistent challenge demands analog front-end (AFE) systems with high sensitivity, low power consumption, and minimal calibration requirements to ensure practical usability in wearable technologies. In response to this challenge, this research introduces VCO-CARE, a Voltage-Controlled Oscillator-based Analog Readout tailored for continuous EDA sensing. The re…

Enhancements to XAML Live Preview in Visual Studio for .NET MAUI. This feature is available in Visual Studio 2022 version 17.14 and the Visual Studio 2026 Insiders release.
#visualstudio #visualstudio2026

COVID-BLUeS -- A Prospective Study on the Value of AI in Lung Ultrasound Analysis
Nina Wiedemann, Dianne de Korte-de Boer, Matthias Richter, Sjors van de Weijer, Charlotte Buhre, Franz A. M. Eggert, Sophie Aarnoudse, Lotte Grevendonk, Steffen R\"ober, Carlijn M. E. Remie, Wolfgang Buhre, Ronald Henry, Jannis Born
https://arxiv.org/abs…

COVID-BLUeS -- A Prospective Study on the Value of AI in Lung Ultrasound Analysis
As a lightweight and non-invasive imaging technique, lung ultrasound (LUS) has gained importance for assessing lung pathologies. The use of Artificial intelligence (AI) in medical decision support systems is promising due to the time- and expertise-intensive interpretation, however, due to the poor quality of existing data used for training AI models, their usability for real-world applications remains unclear. In a prospective study, we analyze data from 63 COVID-19 suspects (33 positive) coll…

Type, Ability, and Effect Systems: Perspectives on Purity, Semantics, and Expressiveness
Yuyan Bao, Tiark Rompf
https://arxiv.org/abs/2510.07582 https://ar…

Type, Ability, and Effect Systems: Perspectives on Purity, Semantics, and Expressiveness
Programming benefits from a clear separation between pure, mathematical computation and impure, effectful interaction with the world. Existing approaches to enforce this separation include monads, type-and-effect systems, and capability systems. All share a tension between precision and usability, and each one has non-obvious strengths and weaknesses. This paper aims to raise the bar in assessing such systems. First, we propose a semantic definition of purity, inspired by contextual equivalen…

Who Benefits from AI Explanations? Towards Accessible and Interpretable Systems
Maria J. P. Peixoto, Akriti Pandey, Ahsan Zaman, Peter R. Lewis
https://arxiv.org/abs/2508.10806 …

Who Benefits from AI Explanations? Towards Accessible and Interpretable Systems
As AI systems are increasingly deployed to support decision-making in critical domains, explainability has become a means to enhance the understandability of these outputs and enable users to make more informed and conscious choices. However, despite growing interest in the usability of eXplainable AI (XAI), the accessibility of these methods, particularly for users with vision impairments, remains underexplored. This paper investigates accessibility gaps in XAI through a two-pronged approach. …

die beA client security lässt sich nicht mehr per menu beenden. Ich kille das Ding halt dann. Das Ding ist ein usability - Scheiterhaufen.

Developing a Cost-Effective Spectrometer: A Practical Approach
Mohammad Tahsin Alam, Zafrin Jahan Nikita, Yasir Mahmud, Rafichha Yeasmin, Fairuz Darimi Bushra, Sheikh Hasib Cheragee, Redwanul Talukder Zeem
https://arxiv.org/abs/2510.06703

Developing a Cost-Effective Spectrometer: A Practical Approach
The paper demonstrates the design and execution of a low-cost optical spectrometer that employs a webcam, diffraction grating & Python (a free, open-source programming language). The device's design prioritized economy and usability, with a black box casing to reduce stray light and increase measurement accuracy. A diffraction grating made from a DVD was used to split light into its constituent wavelengths, which were then collected by the camera. The calibration procedure used a RED TIDE USB65…

Public records show C3 AI's Project Sherlock, company's flagship contract to speed up policing in San Mateo County, has struggled with usability issues and more (Thomas Brewster/Forbes)
https://www.forbes.com/sites/thomasbrewste

Billionaire Tom Siebel's C3 AI Was Supposed To Speed Up Policing. It’s Not Going Well.
San Mateo County pumped $12 million into a grand AI surveillance system that was supposed to level up its police work. Three years later, it still hasn’t seen the benefits.

Universal Discrete-Domain Speech Enhancement
Fei Liu, Yang Ai, Ye-Xin Lu, Rui-Chen Zheng, Hui-Peng Du, Zhen-Hua Ling
https://arxiv.org/abs/2510.09974 https://

Universal Discrete-Domain Speech Enhancement
In real-world scenarios, speech signals are inevitably corrupted by various types of interference, making speech enhancement (SE) a critical task for robust speech processing. However, most existing SE methods only handle a limited range of distortions, such as additive noise, reverberation, or band limitation, while the study of SE under multiple simultaneous distortions remains limited. This gap affects the generalization and practical usability of SE methods in real-world environments.To add…

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Evaluating the Usability of Microgestures for Text Editing Tasks in Virtual Reality
Xiang Li, Wei He, Per Ola Kristensson

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

Towards an Efficient, Customizable, and Accessible AI Tutor
Juan Segundo Hevia, Facundo Arredondo, Vishesh Kumar
https://arxiv.org/abs/2510.06255 https://a…

Towards an Efficient, Customizable, and Accessible AI Tutor
The integration of large language models (LLMs) into education offers significant potential to enhance accessibility and engagement, yet their high computational demands limit usability in low-resource settings, exacerbating educational inequities. To address this, we propose an offline Retrieval-Augmented Generation (RAG) pipeline that pairs a small language model (SLM) with a robust retrieval mechanism, enabling factual, contextually relevant responses without internet connectivity. We evalua…

AI Agents for Web Testing: A Case Study in the Wild
Naimeng Ye, Xiao Yu, Ruize Xu, Tianyi Peng, Zhou Yu
https://arxiv.org/abs/2509.05197 https://arxiv.org/…

AI Agents for Web Testing: A Case Study in the Wild
Automated web testing plays a critical role in ensuring high-quality user experiences and delivering business value. Traditional approaches primarily focus on code coverage and load testing, but often fall short of capturing complex user behaviors, leaving many usability issues undetected. The emergence of large language models (LLM) and AI agents opens new possibilities for web testing by enabling human-like interaction with websites and a general awareness of common usability problems. In thi…

The MUG-10 Framework for Preventing Usability Issues in Mobile Application Development
Pawel Weichbroth, Tomasz Szot
https://arxiv.org/abs/2509.21914 https://

The MUG-10 Framework for Preventing Usability Issues in Mobile Application Development
Nowadays, mobile applications are essential tools for everyday life, providing users with anytime, anywhere access to up-to-date information, communication, and entertainment. Needless to say, hardware limitations and the diverse needs of different user groups pose a number of design and development challenges. According to recent studies, usability is one of the most revealing among many others. However, few have made the direct effort to provide and discuss what countermeasures can be applied…

SPARE: Securing Progressive Web Applications Against Unauthorized Replications
Sajib Talukder, Nur Imtiazul Haque, Khandakar Ashrafi Akbar
https://arxiv.org/abs/2508.07053 https…

SPARE: Securing Progressive Web Applications Against Unauthorized Replications
WebView applications are widely used in mobile applications to display web content directly within the app, enhancing user engagement by eliminating the need to open an external browser and providing a seamless experience. Progressive Web Applications (PWAs) further improve usability by combining the accessibility of web apps with the speed, offline capabilities, and responsiveness of native applications. However, malicious developers can exploit this technology by duplicating PWA web links to …

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. …

Multimodal Feedback for Task Guidance in Augmented Reality
Hu Guo, Lily Patel, Rohan Gupt
https://arxiv.org/abs/2510.01690 https://arxiv.org/pdf/2510.01690…

Multimodal Feedback for Task Guidance in Augmented Reality
Optical see-through augmented reality (OST-AR) overlays digital targets and annotations on the physical world, offering promising guidance for hands-on tasks such as medical needle insertion or assembly. Recent work on OST-AR depth perception shows that target opacity and tool visualization significantly affect accuracy and usability; opaque targets and rendering the real instrument reduce depth errors, whereas transparent targets and absent tools impair performance. However, reliance on visual…

Bridging Technical Capability and User Accessibility: Off-grid Civilian Emergency Communication
Karim Khamaisi, Oliver Kamer, Bruno Rodrigues, Jan von der Assen, Burkhard Stiller
https://arxiv.org/abs/2509.22568

Bridging Technical Capability and User Accessibility: Off-grid Civilian Emergency Communication
During large-scale crises disrupting cellular and Internet infrastructure, civilians lack reliable methods for communication, aid coordination, and access to trustworthy information. This paper presents a unified emergency communication system integrating a low-power, long-range network with a crisis-oriented smartphone application, enabling decentralized and off-grid civilian communication. Unlike previous solutions separating physical layer resilience from user layer usability, our design mer…

Neural likelihood estimators for flexible gravitational wave data analysis
Luca Negri, Anuradha Samajdar
https://arxiv.org/abs/2509.17606 https://arxiv.org…

Neural likelihood estimators for flexible gravitational wave data analysis
In this paper, we develop a Neural Likelihood Estimator and apply it to analyse real gravitational-wave (GW) data for the first time. We assess the usability of neural likelihood for GW parameter estimation and report the parameter space where neural likelihood performs as a robust estimator to output posterior probability distributions using modest computational resources. In addition, we demonstrate that the trained Neural likelihood can also be used in further analysis, enabling us to obtain…

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.…

BridgeScope: A Universal Toolkit for Bridging Large Language Models and Databases
Lianggui Weng, Dandan Liu, Rong Zhu, Bolin Ding, Jingren Zhou
https://arxiv.org/abs/2508.04031 …

BridgeScope: A Universal Toolkit for Bridging Large Language Models and Databases
As large language models (LLMs) demonstrate increasingly powerful reasoning and orchestration capabilities, LLM-based agents are rapidly proliferating for complex data-related tasks. Despite this progress, the current design of how LLMs interact with databases exhibits critical limitations in usability, security, privilege management, and data transmission efficiency. To resolve these challenges, we introduce BridgeScope, a universal toolkit bridging LLMs and databases through three key innovat…

Virtual Reality User Interface Design: Best Practices and Implementation
Esin Mehmedova, Santiago Berrezueta-Guzman, Stefan Wagner
https://arxiv.org/abs/2508.09358 https://

Virtual Reality User Interface Design: Best Practices and Implementation
Designing effective user interfaces (UIs) for virtual reality (VR) is essential to enhance user immersion, usability, comfort, and accessibility in virtual environments. Despite the growing adoption of VR across domains such as education, healthcare, gaming, and rehabilitation, there is a noticeable lack of unified and comprehensive design guidelines for VR UI design. To address this gap, we conducted a systematic literature review to identify existing best practices and propose complete and un…

CloudBreaker: Breaking the Cloud Covers of Sentinel-2 Images using Multi-Stage Trained Conditional Flow Matching on Sentinel-1
Saleh Sakib Ahmed, Sara Nowreen, M. Sohel Rahman
https://arxiv.org/abs/2508.03608

CloudBreaker: Breaking the Cloud Covers of Sentinel-2 Images using Multi-Stage Trained Conditional Flow Matching on Sentinel-1
Cloud cover and nighttime conditions remain significant limitations in satellite-based remote sensing, often restricting the availability and usability of multi-spectral imagery. In contrast, Sentinel-1 radar images are unaffected by cloud cover and can provide consistent data regardless of weather or lighting conditions. To address the challenges of limited satellite imagery, we propose CloudBreaker, a novel framework that generates high-quality multi-spectral Sentinel-2 signals from Sentinel-…

LLMs are All You Need? Improving Fuzz Testing for MOJO with Large Language Models
Linghan Huang, Peizhou Zhao, Huaming Chen
https://arxiv.org/abs/2510.10179 https://

LLMs are All You Need? Improving Fuzz Testing for MOJO with Large Language Models
The rapid development of large language models (LLMs) has revolutionized software testing, particularly fuzz testing, by automating the generation of diverse and effective test inputs. This advancement holds great promise for improving software reliability. Meanwhile, the introduction of MOJO, a high-performance AI programming language blending Python's usability with the efficiency of C and C++, presents new opportunities to enhance AI model scalability and programmability. However, as a new l…

ENSI: Efficient Non-Interactive Secure Inference for Large Language Models
Zhiyu He, Maojiang Wang, Xinwen Gao, Yuchuan Luo, Lin Liu, Shaojing Fu
https://arxiv.org/abs/2509.09424

ENSI: Efficient Non-Interactive Secure Inference for Large Language Models
Secure inference enables privacy-preserving machine learning by leveraging cryptographic protocols that support computations on sensitive user data without exposing it. However, integrating cryptographic protocols with large language models (LLMs) presents significant challenges, as the inherent complexity of these protocols, together with LLMs' massive parameter scale and sophisticated architectures, severely limits practical usability. In this work, we propose ENSI, a novel non-interactive se…

PEAR: Phase Entropy Aware Reward for Efficient Reasoning
Chen Huang, Wei Lu, Wenxuan Zhang
https://arxiv.org/abs/2510.08026 https://arxiv.org/pdf/2510.0802…

PEAR: Phase Entropy Aware Reward for Efficient Reasoning
Large Reasoning Models (LRMs) have achieved impressive performance on complex reasoning tasks by generating detailed chain-of-thought (CoT) explanations. However, these responses are often excessively long, containing redundant reasoning steps that inflate inference cost and reduce usability. Controlling the length of generated reasoning without sacrificing accuracy remains an open challenge. Through a systematic empirical analysis, we reveal a consistent positive correlation between model entr…

Recommendations for Best Practices for Data Preservation and Open Science in HEP
Simone Campana (CERN, Switzerland), Irakli Chakaberia (Lawrence Berkeley National Laboratory, USA), Gang Chen (Institute of High Energy Physics, China), Cristinel Diaconu (Centre de Physique des Particules de Marseille CPPM, France, CNRS/IN2P3 and Aix-Marseille Universit\'e, France), Caterina Doglioni (University of Manchester, UK), Dillon S. Fitzgerald (University of Michigan, USA), Vincent Garonne (B…

Recommendations for Best Practices for Data Preservation and Open Science in HEP
These recommendations are the result of reflections by scientists and experts who are, or have been, involved in the preservation of high-energy physics data. The work has been done under the umbrella of the Data Lifecycle panel of the International Committee of Future Accelerators (ICFA), drawing on the expertise of a wide range of stakeholders. A key indicator of success in the data preservation efforts is the long-term usability of the data. Experience shows that achieving this requires pr…

Designing Walrus: Relational Programming with Rich Types, On-Demand Laziness, and Structured Traces
Santiago Cu\'ellar, Naomi Spargo, Jonathan Daugherty, David Darais
https://arxiv.org/abs/2510.02579

Designing Walrus: Relational Programming with Rich Types, On-Demand Laziness, and Structured Traces
We present Walrus, a functional relational programming language embedded in Haskell that extends the miniKanren model with type-polymorphic unification, on-demand laziness, and a range of usability features aimed at practical development. These include use of Haskell Generics for boilerplate reduction, structured debugging traces, and ergonomic support for product types. We describe the design and implementation of Walrus through the lens of our experience developing bidirectional compilers, an…

Computational approaches for virus host prediction: A review of methods and applications
Jiayu Shang, Cheng Peng, Jiaojiao Guan, Dehan Cai, Donglin Wang, Yanni Sun
https://arxiv.org/abs/2509.00349

Computational approaches for virus host prediction: A review of methods and applications
Accurate prediction of virus-host interactions is critical for understanding viral ecology and developing applications like phage therapy. However, the growing number of computational tools has created a complex landscape, making direct performance comparison challenging due to inconsistent benchmarks and varying usability. Here, we provide a systematic review and a rigorous benchmark of 27 virus-host prediction tools. We formulate the host prediction task into two primary frameworks, link pred…

Adoption, usability and perceived clinical value of a UK AI clinical reference platform (iatroX): a mixed-methods formative evaluation of real-world usage and a 1,223-respondent user survey
Kolawole Tytler
https://arxiv.org/abs/2509.21188

Adoption, usability and perceived clinical value of a UK AI clinical reference platform (iatroX): a mixed-methods formative evaluation of real-world usage and a 1,223-respondent user survey
Clinicians face growing information overload from biomedical literature and guidelines, hindering evidence-based care. Retrieval-augmented generation (RAG) with large language models may provide fast, provenance-linked answers, but requires real-world evaluation. We describe iatroX, a UK-centred RAG-based clinical reference platform, and report early adoption, usability, and perceived clinical value from a formative implementation evaluation. Methods comprised a retrospective analysis of usage …

Auto-Cal: Automated and Continuous Geo-Referencing of All-Sky Imagers Using Fisheye Lens Modeling and Star Tracks
Sudha Kapali, Michael P. Henderson, Juanita Riccobono, Michael A. Migliozzi, Robert B. Kerr
https://arxiv.org/abs/2508.17146

Auto-Cal: Automated and Continuous Geo-Referencing of All-Sky Imagers Using Fisheye Lens Modeling and Star Tracks
A fully automated and continuous calibration framework for All-Sky Imagers (ASIs) that significantly enhances the spatial accuracy and reliability of geo-referenced ASI data is presented. The technique addresses a critical bottleneck in ASI image data reliability and usability for real time space weather via automated geo-referencing under real-world field conditions. The system corrects the lens distortion in ASIs using a well-established fisheye lens model and automatically estimates camera o…

A Survey on Current Trends and Recent Advances in Text Anonymization
Tobias Deu{\ss}er, Lorenz Sparrenberg, Armin Berger, Max Hahnb\"uck, Christian Bauckhage, Rafet Sifa
https://arxiv.org/abs/2508.21587

A Survey on Current Trends and Recent Advances in Text Anonymization
The proliferation of textual data containing sensitive personal information across various domains requires robust anonymization techniques to protect privacy and comply with regulations, while preserving data usability for diverse and crucial downstream tasks. This survey provides a comprehensive overview of current trends and recent advances in text anonymization techniques. We begin by discussing foundational approaches, primarily centered on Named Entity Recognition, before examining the tr…

SilentLedger: Privacy-Preserving Auditing for Blockchains with Complete Non-Interactivity
Zihan Liu, Xiaohu Wang, Chao Lin, Minghui Xu, Debiao He, Xinyi Huang
https://arxiv.org/abs/2509.08722

SilentLedger: Privacy-Preserving Auditing for Blockchains with Complete Non-Interactivity
Privacy-preserving blockchain systems are essential for protecting transaction data, yet they must also provide auditability that enables auditors to recover participant identities and transaction amounts when warranted. Existing designs often compromise the independence of auditing and transactions, introducing extra interactions that undermine usability and scalability. Moreover, many auditable solutions depend on auditors serving as validators or recording nodes, which introduces risks to bo…

Impact of Target and Tool Visualization on Depth Perception and Usability in Optical See-Through AR
Yue Yang, Xue Xie, Xinkai Wang, Hui Zhang, Chiming Yu, Xiaoxian Xiong, Lifeng Zhu, Yuanyi Zheng, Jue Cen, Bruce Daniel, Fred Baik
https://arxiv.org/abs/2508.18481

Impact of Target and Tool Visualization on Depth Perception and Usability in Optical See-Through AR
Optical see-through augmented reality (OST-AR) systems like Microsoft HoloLens 2 hold promise for arm's distance guidance (e.g., surgery), but depth perception of the hologram and occlusion of real instruments remain challenging. We present an evaluation of how visualizing the target object with different transparencies and visualizing a tracked tool (virtual proxy vs. real tool vs. no tool tracking) affects depth perception and system usability. Ten participants performed two experiments on Ho…

Minimum Data, Maximum Impact: 20 annotated samples for explainable lung nodule classification
Luisa Gall\'ee, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael G\"otz
https://arxiv.org/abs/2508.00639

Minimum Data, Maximum Impact: 20 annotated samples for explainable lung nodule classification
Classification models that provide human-interpretable explanations enhance clinicians' trust and usability in medical image diagnosis. One research focus is the integration and prediction of pathology-related visual attributes used by radiologists alongside the diagnosis, aligning AI decision-making with clinical reasoning. Radiologists use attributes like shape and texture as established diagnostic criteria and mirroring these in AI decision-making both enhances transparency and enables expli…

Position: Intelligent Coding Systems Should Write Programs with Justifications
Xiangzhe Xu, Shiwei Feng, Zian Su, Chengpeng Wang, Xiangyu Zhang
https://arxiv.org/abs/2508.06017 …

Position: Intelligent Coding Systems Should Write Programs with Justifications
Intelligent coding systems are transforming software development by enabling users to specify code behavior in natural language. However, the opaque decision-making of AI-driven coders raises trust and usability concerns, particularly for non-expert users who cannot inspect low-level implementations. We argue that these systems should not only generate code but also produce clear, consistent justifications that bridge model reasoning and user understanding. To this end, we identify two critical…

Alzheimer's Clinical Research Data via R Packages: the alzverse
Michael C. Donohue (for the Alzheimer's Disease Neuroimaging Initiative), Kedir Hussen (for the Alzheimer's Disease Neuroimaging Initiative), Oliver Langford (for the Alzheimer's Disease Neuroimaging Initiative), Richard Gallardo (for the Alzheimer's Disease Neuroimaging Initiative), Gustavo Jimenez-Maggiora (for the Alzheimer's Disease Neuroimaging Initiative), Paul S. Aisen (for the Alzheimer'…

Alzheimer's Clinical Research Data via R Packages: the alzverse
Sharing clinical research data is essential for advancing research in Alzheimer's disease (AD) and other therapeutic areas. However, challenges in data accessibility, standardization, documentation, usability, and reproducibility continue to impede this goal. In this article, we highlight the advantages of using R packages to overcome these challenges using two examples. The A4LEARN R package includes data from a randomized trial (the Anti-Amyloid Treatment in Asymptomatic Alzheimer's [A4] stud…

Between Knowledge and Care: Evaluating Generative AI-Based IUI in Type 2 Diabetes Management Through Patient and Physician Perspectives
Yibo Meng, Ruiqi Chen, Zhiming Liu, Xiaolan Ding, Yan Guan
https://arxiv.org/abs/2510.10048

Between Knowledge and Care: Evaluating Generative AI-Based IUI in Type 2 Diabetes Management Through Patient and Physician Perspectives
Generative AI systems are increasingly adopted by patients seeking everyday health guidance, yet their reliability and clinical appropriateness remain uncertain. Taking Type 2 Diabetes Mellitus (T2DM) as a representative chronic condition, this paper presents a two-part mixed-methods study that examines how patients and physicians in China evaluate the quality and usability of AI-generated health information. Study~1 analyzes 784 authentic patient questions to identify seven core categories of …

ARMimic: Learning Robotic Manipulation from Passive Human Demonstrations in Augmented Reality
Rohan Walia (Department of Computer Engineering, Munich Institute of Robotics and Machine Intelligence), Yusheng Wang (Department of Precision Engineering, Research into Artifacts, Center for Engineering), Ralf R\"omer (Department of Computer Engineering, Munich Institute of Robotics and Machine Intelligence), Masahiro Nishio (Toyota Motor Corporation, Japan), Angela P. Schoellig (Departm…

ARMimic: Learning Robotic Manipulation from Passive Human Demonstrations in Augmented Reality
Imitation learning is a powerful paradigm for robot skill acquisition, yet conventional demonstration methods--such as kinesthetic teaching and teleoperation--are cumbersome, hardware-heavy, and disruptive to workflows. Recently, passive observation using extended reality (XR) headsets has shown promise for egocentric demonstration collection, yet current approaches require additional hardware, complex calibration, or constrained recording conditions that limit scalability and usability. We pre…

Poster: ChatIYP: Enabling Natural Language Access to the Internet Yellow Pages Database
Vasilis Andritsoudis, Pavlos Sermpezis, Ilias Dimitriadis, Athena Vakali
https://arxiv.org/abs/2509.19411

Poster: ChatIYP: Enabling Natural Language Access to the Internet Yellow Pages Database
The Internet Yellow Pages (IYP) aggregates information from multiple sources about Internet routing into a unified, graph-based knowledge base. However, querying it requires knowledge of the Cypher language and the exact IYP schema, thus limiting usability for non-experts. In this paper, we propose ChatIYP, a domain-specific Retrieval-Augmented Generation (RAG) system that enables users to query IYP through natural language questions. Our evaluation demonstrates solid performance on simple quer…

Improving the Developer Experience with a Low-Code Process Modelling Language
Henrique Henriques, Hugo Louren\c{c}o, Vasco Amaral, Miguel Goul\~ao
https://arxiv.org/abs/2508.06299

Improving the Developer Experience with a Low-Code Process Modelling Language
Context: The OutSystems Platform is a development environment composed of several DSLs, used to specify, quickly build, and validate web and mobile applications. The DSLs allow users to model different perspectives such as interfaces and data models, define custom business logic and construct process models. Problem: The DSL for process modelling (Business Process Technology (BPT)), has a low adoption rate and is perceived as having usability problems hampering its adoption. This is problematic…

Crosslisted article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- Impact of Target and Tool Visualization on Depth Perception and Usability in Optical See-Through AR
Yang, Xie, Wang, Zhang, Yu, Xiong, Zhu, Zheng, Cen, Daniel, Baik

A Hybrid CAPTCHA Combining Generative AI with Keystroke Dynamics for Enhanced Bot Detection
Ayda Aghaei Nia
https://arxiv.org/abs/2510.02374 https://arxiv.…

A Hybrid CAPTCHA Combining Generative AI with Keystroke Dynamics for Enhanced Bot Detection
Completely Automated Public Turing tests to tell Computers and Humans Apart (CAPTCHAs) are a foundational component of web security, yet traditional implementations suffer from a trade-off between usability and resilience against AI-powered bots. This paper introduces a novel hybrid CAPTCHA system that synergizes the cognitive challenges posed by Large Language Models (LLMs) with the behavioral biometric analysis of keystroke dynamics. Our approach generates dynamic, unpredictable questions tha…

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…

bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs
Wence Ji, Jiancan Wu, Aiying Li, Shuyi Zhang, Junkang Wu, An Zhang, Xiang Wang, Xiangnan He
https://arxiv.org/abs/2509.19775

bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs
With the rapid advancement of large language models (LLMs), their robustness against adversarial manipulations, particularly jailbreak backdoor attacks, has become critically important. Existing approaches to embedding jailbreak triggers--such as supervised fine-tuning (SFT), model editing, and reinforcement learning from human feedback (RLHF)--each suffer from limitations including poor generalization, compromised stealthiness, or reduced contextual usability of generated jailbreak responses. …

Improving Assignment Submission in Higher Education through a Git-Enabled System: An Iterative Case Study
Ololade Babatunde, Tomisin Ayodabo, Raqibul Raqibul
https://arxiv.org/abs/2510.06363

Improving Assignment Submission in Higher Education through a Git-Enabled System: An Iterative Case Study
This study addresses challenges in traditional assignment submission methods used in higher education by introducing and evaluating a customized Git-based submission system. Employing iterative software development and user-centered design methodologies, the system was integrated within a real-world university environment. Empirical evaluation, including usability testing and student feedback, indicated significant improvements in assignment tracking, collaboration, and submission efficiency. S…

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. …

"It feels like hard work trying to talk to it": Understanding Older Adults' Experiences of Encountering and Repairing Conversational Breakdowns with AI Systems
Niharika Mathur, Tamara Zubatiy, Agata Rozga, Elizabeth Mynatt
https://arxiv.org/abs/2510.06690

"It feels like hard work trying to talk to it": Understanding Older Adults' Experiences of Encountering and Repairing Conversational Breakdowns with AI Systems
Designing Conversational AI systems to support older adults requires more than usability and reliability, it also necessitates robustness in handling conversational breakdowns. In this study, we investigate how older adults navigate and repair such breakdowns while interacting with a voice-based AI system deployed in their homes for medication management. Through a 20-week in-home deployment with 7 older adult participant dyads, we analyzed 844 recoded interactions to identify conversational br…

A Bag of Tricks for Efficient Implicit Neural Point Clouds
Florian Hahlbohm, Linus Franke, Leon Overk\"amping, Paula Wespe, Susana Castillo, Martin Eisemann, Marcus Magnor
https://arxiv.org/abs/2508.19140

A Bag of Tricks for Efficient Implicit Neural Point Clouds
Implicit Neural Point Cloud (INPC) is a recent hybrid representation that combines the expressiveness of neural fields with the efficiency of point-based rendering, achieving state-of-the-art image quality in novel view synthesis. However, as with other high-quality approaches that query neural networks during rendering, the practical usability of INPC is limited by comparatively slow rendering. In this work, we present a collection of optimizations that significantly improve both the training …

Trust in Transparency: How Explainable AI Shapes User Perceptions
Allen Daniel Sunny
https://arxiv.org/abs/2510.04968 https://arxiv.org/pdf/2510.04968

Trust in Transparency: How Explainable AI Shapes User Perceptions
This study explores the integration of contextual explanations into AI-powered loan decision systems to enhance trust and usability. While traditional AI systems rely heavily on algorithmic transparency and technical accuracy, they often fail to account for broader social and economic contexts. Through a qualitative study, I investigated user interactions with AI explanations and identified key gaps, in- cluding the inability of current systems to provide context. My findings underscore the lim…

Wrist2Finger: Sensing Fingertip Force for Force-Aware Hand Interaction with a Ring-Watch Wearable
Yingjing Xiao (East China Normal University, Shanghai, China), Zhichao Huang (East China Normal University, Shanghai, China), Junbin Ren (East China Normal University, Shanghai, China), Haichuan Song (East China Normal University, Shanghai, China), Yang Gao (East China Normal University, Shanghai, China), Yuting Bai (South China University of Technology, Guangzhou, China), Zhanpeng Jin (So…

Wrist2Finger: Sensing Fingertip Force for Force-Aware Hand Interaction with a Ring-Watch Wearable
Hand pose tracking is essential for advancing applications in human-computer interaction. Current approaches, such as vision-based systems and wearable devices, face limitations in portability, usability, and practicality. We present a novel wearable system that reconstructs 3D hand pose and estimates per-finger forces using a minimal ring-watch sensor setup. A ring worn on the finger integrates an inertial measurement unit (IMU) to capture finger motion, while a smartwatch-based single-channel…

Characterizing Trust Boundary Vulnerabilities in TEE Containers
Weijie Liu, Hongbo Chen, Shuo Huai, Zhen Xu, Wenhao Wang, Zhi Li, Zheli Liu
https://arxiv.org/abs/2508.20962 http…

Characterizing Trust Boundary Vulnerabilities in TEE Containers
Trusted Execution Environments (TEEs) have emerged as a cornerstone of confidential computing, garnering significant attention from both academia and industry. To enable the secure development, execution, and deployment, of applications on TEE platforms, TEE containers have been introduced as middleware solutions. These containers aim to shield applications from potentially malicious operating systems and orchestration interfaces while maintaining usability and reliability. In this paper, we an…

Evaluating Citizen Satisfaction with Saudi Arabia's E-Government Services: A Standards-Based, Theory-Informed Approach
Mohammed O. Alannsary
https://arxiv.org/abs/2508.17912

Evaluating Citizen Satisfaction with Saudi Arabia's E-Government Services: A Standards-Based, Theory-Informed Approach
As digital government platforms become central to public service delivery, understanding citizen assessment is crucial for enhancing usability, trust, and inclusivity. This study investigates citizen satisfaction with the e-government services in Saudi Arabia through a quality-in-use framework based on ISO/IEC 25010 and ISO/IEC 25022 standards, interpreted through the lens of the Unified Theory of Acceptance and Use of Technology (UTAUT). A structured questionnaire was administered to 500 citiz…

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…

Floor sensors are cheap and easy to use! A Nihon Buyo Case Study
Miho Imai
https://arxiv.org/abs/2508.19261 https://arxiv.org/pdf/2508.19261

Floor sensors are cheap and easy to use! A Nihon Buyo Case Study
As floor-sensing technologies gain traction in movement research, questions remain about their usability and effectiveness for non-expert users. This study presents a case study evaluating Flexel, a modular, low-cost, high-resolution pressure-sensing floor interface, in the context of Nihon Buyo, a traditional Japanese dance. The system was installed, calibrated, and used by a first-time, non-technical user to track weight distribution patterns of a teacher and learner over nine weeks. Live pre…

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…

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…

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…

Designing Usable Controls for Customizable Social Media Feeds
Frederick Choi, Eshwar Chandrasekharan
https://arxiv.org/abs/2509.19615 https://arxiv.org/pdf…

Designing Usable Controls for Customizable Social Media Feeds
Personalized recommendation algorithms deliver content to the user on most major social media platforms. While these algorithms are crucial for helping users find relevant content, users lack meaningful control over them. This reduces users' sense of agency and their ability to adapt social media feeds to their own needs and values. Efforts have been made to give users more control over their feeds, but usability remains a major barrier to adoption. Drawing upon prior work in designing teachabl…

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 …