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The rapid advancements in Vision-Language Models (VLMs) have shown great potential in tackling mathematical reasoning tasks that involve visual context. Unlike humans who can reliably apply solution steps to similar problems with minor…
Mobile app GUI (Graphical User Interface) pages now contain rich visual information, with the visual semantics of each page helping users understand the application logic. However, these complex visual and functional logic present new…
The HTML5 <canvas> is used to display high quality graphics in web applications such as web games (i.e., <canvas> games). However, automatically testing <canvas> games is not possible with existing web testing techniques and tools, and…
A critical part of creating code suggestion systems is the pre-training of Large Language Models on vast amounts of source code and natural language text, often of questionable origin or quality. This may contribute to the presence of bugs…
Security vulnerabilities introduced by applications using third-party dependencies are on the increase, caused by the emergence of large ecosystems of libraries such as the NPM packages for JavaScript. Nowadays, libraries depend on each…
Prior natural language datasets for data visualization have focused on tasks such as visualization literacy assessment, insight generation, and visualization generation from natural language instructions. These studies often rely on…
Database Management Systems (DBMSs) are vital components in modern data-driven systems. Their complexity often leads to logic bugs, which are implementation errors within the DBMSs that can lead to incorrect query results, data exposure,…
Tile-based programming frameworks are increasingly adopted to write high-performance GPU kernels in domains such as deep learning and scientific computing. While these frameworks enhance productivity and hardware utilization, their…
Vision Language Models (VLMs) are prone to errors, and identifying where these errors occur is critical for ensuring the reliability and safety of AI systems. In this paper, we propose an approach that automatically generates questions…
Vision-Language-Action (VLA) models have recently achieved remarkable progress in robotic manipulation, yet they remain limited in failure diagnosis and learning from failures. Additionally, existing failure datasets are mostly generated…
In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis…
Static analysis plays a crucial role in software vulnerability detection, yet faces a persistent precision-scalability tradeoff. In large codebases like the Linux kernel, traditional static analysis tools often generate excessive false…
Security vulnerabilities in software systems represent significant risks as potential entry points for malicious attacks. Traditional dashboards that display the results of static analysis security testing often use 2D or 3D visualizations,…
The identification of vulnerabilities is a continuous challenge in software projects. This is due to the evolution of methods that attackers employ as well as the constant updates to the software, which reveal additional issues. As a…
Despite recent advances in Vision-Language Models (VLMs), they may over-rely on visual language priors existing in their training data rather than true visual reasoning. To investigate this, we introduce ViLP, a benchmark featuring…
The frequent need for analysts to create visualizations to derive insights from data has driven extensive research into the generation of natural Language to Visualization (NL2VIS). While recent progress in large language models (LLMs)…
GPUs play an increasingly important role in modern software. However, the heterogeneous host-device execution model and expanding software stacks make GPU programs prone to memory-safety and concurrency bugs that evade static analysis.…
Data visualization (DV) is the fundamental and premise tool to improve the efficiency in conveying the insights behind the big data, which has been widely accepted in existing data-driven world. Task automation in DV, such as converting…
Despite the rising popularity of automated visualization tools, existing systems tend to provide direct results which do not always fit the input data or meet visualization requirements. Therefore, additional specification adjustments are…
Large language models (LLMs) have achieved remarkable performance across a wide range of natural language tasks. Understanding how LLMs internally represent knowledge remains a significant challenge. Despite Sparse Autoencoders (SAEs) have…