Related papers: Crucible: Graphical Test Cases for Alloy Models
Additive models offer accurate and interpretable predictions for tabular data, a critical tool for statistical modeling. Recent advances in Neural Additive Models (NAMs) allow these models to handle complex machine learning tasks, including…
The integration of large language models (LLMs) into materials science offers a transformative opportunity to streamline computational workflows, yet current agentic systems remain constrained by rigid, carefully crafted domain-specific…
Multimodal classifiers function as opaque black box models. While several techniques exist to interpret their predictions, very few of them are as intuitive and accessible as natural language explanations (NLEs). To build trust, such…
Accelerated discovery in materials science demands autonomous systems capable of dynamically formulating and solving design problems. In this work, we introduce a novel framework that leverages Bayesian optimization over a problem…
Online experiments are ubiquitous. As the scale of experiments has grown, so has the complexity of their design and implementation. In response, firms have developed software frameworks for designing and deploying online experiments.…
Program verifiers such as Dafny automate proofs by outsourcing them to an SMT solver. This automation is not perfect, however, and the solver often requires hints in the form of assertions, creating a burden for the proof engineer. In this…
Graphical user interfaces (GUIs) are integral parts of software systems that require interactions from their users. Software testers have paid special attention to GUI testing in the last decade, and have devised techniques that are…
We present VERIFAI, a software toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components. VERIFAI particularly seeks to address challenges with applying formal…
Software artifacts are ubiquitous in our lives being an essential part of home appliances, cars, cel phones, and even in more critical activities like aeronautics and health sciences. In this context software failures may produce enormous…
Governmental organisations cope with many laws and policies when handling administrative law cases. Making sure these norms are enforced in the handling of cases is for the most part done manually. However, enforcing policies can get…
Most explainable AI (XAI) techniques are concerned with the design of algorithms to explain the AI's decision. However, the data that is used to train these algorithms may contain features that are often incomprehensible to an end-user even…
Automated slicing aims to identify subsets of evaluation data where a trained model performs anomalously. This is an important problem for machine learning pipelines in production since it plays a key role in model debugging and comparison,…
Vision transformer (ViT) models, when coupled with interpretation models, are regarded as secure and challenging to deceive, making them well-suited for security-critical domains such as medical applications, autonomous vehicles, drones,…
Developing industry-wide standards and ensuring producers of mission-critical systems comply with them is crucial to fostering consumer acceptance. Producers of such systems can rely on assurance cases to demonstrate to regulatory…
Computerized Adaptive Testing (CAT) is emerging as a promising testing application in many scenarios, such as education, game and recruitment, which targets at diagnosing the knowledge mastery levels of examinees on required concepts. It…
Analyzing non-compilable C/C++ submodules without a resolved build environment remains a critical bottleneck for industrial software evolution. Traditional static analysis tools often fail in these scenarios due to their reliance on…
This paper presents the outcome of a research collaboration between academia and industry to implement and utilize the capabilities of constrained interaction testing for an open-source tool for industrial-scale application. The project…
API testing has increasing demands for software companies. Prior API testing tools were aware of certain types of dependencies that needed to be concise between operations and parameters. However, their approaches, which are mostly done…
This paper presents catsim, the first package written in the Python language specialized in computerized adaptive tests and the logistical models of Item Response Theory. catsim provides functions for generating item and examinee…
Education in the practical applications of logic and proving such as the formal specification and verification of computer programs is substantially hampered by the fact that most time and effort that is invested in proving is actually…