I’ve repeatedly run into the same issue when working with ML / NLP systems (and more recently LLM-based ones): there often isn’t a single correct answer – only better or worse behavior – and small changes can have non-local effects across the system. Traditional testing approaches (assertions, snapshot tests, benchmarks) tend to break down here: failures don’t explain what changed evaluation is expensive tests become brittle or get ignored We ended up building a review-driven regression testing approach […]

Ver mais

arXiv:2601.02559v1 Announce Type: new Abstract: Despite growing awareness of ethical challenges in software development, practitioners still lack structured tools that help them critically engage with the lived experiences of marginalized users. This paper presents PerspectiveCoach, a large language model (LLM)-powered conversational tool designed to guide developers through structured perspective-taking exercises and deepen critical reflection on how software design decisions affect marginalized communities. Through a controlled study with 18 front-end developers (balanced by sex), who interacted with the tool […]

Ver mais

What are techniques for writing maintainable Python code? How do you make your Python more readable and easier to refactor? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

Ver mais

Separable polynomial constraints arise naturally in numerous engineering applications, including sensor positioning systems, robotic kinematics, and regularized optimization. While general-purpose iterative solvers are widely available, their computational overhead and non-deterministic convergence behavior can be limiting factors in real-time and resourceconstrained environments. This paper presents the Parametric K-Formula (PK-Formula), a straightforward closed-form method for solving a specific but practically important class of separable polynomial equations. The method achieves O(n) computational complexity through parametric decomposition, offering 50–120× speedups over Newton-Raphson […]

Ver mais

Robotic imitation learning typically requires models that capture multimodal action distributions while operating at real-time control rates and accommodating multiple sensing modalities. Although recent generative approaches such as diffusion models, flow matching, and Implicit Maximum Likelihood Estimation (IMLE) have achieved promising results, they often satisfy only a subset of these requirements. To address this, we introduce PRISM, a single-pass policy based on a batch-global rejection-sampling variant of IMLE. PRISM couples a temporal multisensory encoder (integrating RGB, depth, tactile, […]

Ver mais

A Software Library with No Code Provocative experiment from Drew Breunig, who designed a new library for time formatting (“3 hours ago” kind of thing) called “whenwords” that has no code at all, just a carefully written specification, an AGENTS.md and a collection of conformance tests in a YAML file. Pass that to your coding agent of choice, tell it what language you need and it will write it for you on demand! This meshes nearly with my […]

Ver mais

Autoencoders have long been considered a nonlinear extension of Principal Component Analysis (PCA). Prior studies have demonstrated that linear autoencoders (LAEs) can recover the ordered, axis-aligned principal components of PCA by incorporating non-uniform $ell_2$ regularization or by adjusting the loss function. However, these approaches become insufficient in the nonlinear setting, as the remaining variance cannot be properly captured independently of the nonlinear mapping. In this work, we propose a novel autoencoder framework that integrates non-uniform variance regularization with […]

Ver mais