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From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds What LLMs Must Forget to Teach Effectively: A DIY Approach to Premodern Japanese Language Pedagogy Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis
Characterizing Usability Issue Discussions in Open Source...
Arghavan Sanei, Jinghui Cheng · 2023-08-19 · via cs.HC updates on arXiv.org

Usability is a crucial factor but one of the most neglected concerns in open source software (OSS). While far from an ideal approach, a common practice that OSS communities adopt to collaboratively address usability is through discussions on issue tracking systems (ITSs). However, there is little knowledge about the extent to which OSS community members engage in usability issue discussions, the aspects of usability they frequently target, and the characteristics of their collaboration around usability issue discussions. This knowledge is important for providing practical recommendations and research directions to better support OSS communities in addressing this important topic and improve OSS usability in general. To help achieve this goal, we performed an extensive empirical study on issues discussed in five popular OSS applications: three data science notebook projects (Jupyter Lab, Google Colab, and CoCalc) and two code editor projects (VSCode and Atom). Our results indicated that while usability issues are extensively discussed in the OSS projects, their scope tended to be limited to efficiency and aesthetics. Additionally, these issues are more frequently posted by experienced community members and display distinguishable characteristics, such as involving more visual communication and more participants. Our results provide important implications that can inform the OSS practitioners to better engage the community in usability issue discussion and shed light on future research efforts toward collaboration techniques and tools for discussing niche topics in diverse communities, such as the usability issues in the OSS context.