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2,517 papers
Background: Sports betting is one of the most popular, rapidly evolving, and attractive forms of gambling. It is associated with an increased risk of gambling-related harms, including relationship difficulties, crime, and physical and mental health problems. Understanding the subjective experiences of sports betting is...
Several strong solar resonance lines show observable linear scattering polarization signals, holding a great potential for investigating the magnetism of the outer solar atmosphere. Accurately modeling these signals requires consideration of the detailed 3D structure of the solar atmosphere and accounting for partial f...
Numerous publications and technical papers have investigated thermal interface materials (TIMs) and the optimized use of TIMs and heat sinks for thermal management in integrated circuit (IC). Several of these studies employ scanning acoustic microscopy (SAM), which is widely recognized as a highly effective, non-dest...
Conventional dynamic laser stimulation (DLS) relies on binary pass/fail detection and sequential single-parameter analysis, which limits sensitivity, efficiency, and robustness when applied to analog soft failures. This paper presents Parametric Laser Mapping (PLM), a boundary-free fault isolation technique that cont...
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This article presents an analysis of the empirical results of the initial stage of scientific research carried out to identify the structural components and predictors of students' social giftedness. The main goal of the study is to identify the predictors of students' social giftedness. Students from state and non-sta...
The HPC site profile is proposed, a structured, evidence-backed document that preflights a workflow into an execution plan or an early, explainable failure and is presented as a case study of preflighting a real workflow.
Statement-level fault localization (FL) is critical for effective software debugging, as it enables developers to precisely identify faulty lines of code. While traditional spectrum-based, mutation-based, and deep learning-based FL techniques have achieved notable progress, they remain limited in modeling rich fault se...
Quantum computing platforms are susceptible to quantum-specific bugs, such as incorrectly ordering qubits or incorrectly implementing quantum abstractions. These bugs are difficult to detect and require specialized expertise. The field faces challenges due to a fragmented landscape of platforms and rapid development cy...
AnaDroid is proposed, a novel LLM training framework specifically tailored for analyzing failed mobile tests that first leverages bidirectional pre-training to instill the domain-specific knowledge and reasoning capabilities required for failed test analysis into the model and employs preference optimization to enhance...
Method relocation refactorings, primarily Move Method and Pull Up/Push Down Method, are indispensable for reducing coupling and enhancing cohesion. Despite their widespread automation in modern refactoring engines, these algorithms remain notoriously error-prone, posing significant risks to software reliability. A prim...
Software debugging is a critical and time-consuming aspect of software development, with fault localization being a fundamental step that significantly impacts debugging efficiency. Mutation-Based Fault Localization (MBFL) has gained prominence due to its robust theoretical foundations and fine-grained analysis capabil...
Analyzing, understanding, and validating the performance of modern processors present significant challenges. These stem from two primary issues. First, it is difficult to construct “performance tests” that can test precisely scoped hypotheses about microarchitectural behavior. Second, it is difficult to make sense of...
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
GPT-Lab
· gpt-lab.eu
Sep 23, 2026
Requirements in large systems rarely exist in isolation. Their meaning depends on the wider project context - other requirements, policies, decisions, tests, and implementation details. That becomes especially important when AI is used for review, because spotting a possible conflict or gap is only the beginning. ReqSpace explores how AI, visualisation, and connected project context can help reviewers understand those findings, trace the relationships behind them, and focus on the questions that…
GPT-Lab
· gpt-lab.eu
Sep 17, 2026
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
We’re launching agentic video understanding across our latest Gemini models for improved accuracy and lower costs and token usage.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
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