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Active inference is an account of cognition and behavior in complex systems which brings together action, perception, and learning under the theoretical mantle of Bayesian inference. Active inference has seen growing applications in…
The principles of automation and innovation serve as foundational elements for advancement in contemporary science and technology. Here, we introduce Pygen, an automation platform designed to empower researchers, technologists, and…
Automated GUI testing is crucial in ensuring that presentation logic behaves as expected. However, existing tools often apply end-to-end approaches and face challenges such as high specification efforts, maintenance difficulties, and flaky…
The great diversity of end-user tasks ranging from manufacturing environments to personal homes makes pre-programming robots for general purpose applications extremely challenging. In fact, teaching robots new actions from scratch that can…
Publicly available source-code libraries are continuously growing and changing. This makes it impossible for models of code to keep current with all available APIs by simply training these models on existing code repositories. Thus,…
In the last few years the Web has progressively acquired the status of an infrastructure for social computation that allows researchers to coordinate the cognitive abilities of human agents in on-line communities so to steer the collective…
Dynamically typed languages such as Python have become very popular. Among other strengths, Python's dynamic nature and its straightforward linking to native code have made it the de-facto language for many research areas such as Artificial…
A decade after its first release, the Go programming language has become a major programming language in the development landscape. While praised for its clean syntax and C-like performance, Go also contains a strong static type-system that…
Multilingual software development integrates multiple languages into a single application, with the Foreign Function Interface (FFI) enabling seamless interaction. While FFI boosts efficiency and extensibility, it also introduces risks.…
Computing students increasingly rely on generative AI tools for programming assistance, often without formal instruction or guidance. This highlights a need to teach students how to effectively interact with AI models, particularly through…
Rapid progress in high-level task planning and code generation for open-world robot manipulation has been witnessed in Embodied AI. However, previous studies put much effort into general common sense reasoning and task planning capabilities…
We consider the task of analyzing message-passing programs by observing their run-time behavior. We introduce a purely library-based instrumentation method to trace communication events during execution. A model of the dependencies among…
Recent surge in Large Language Model (LLM) availability has opened exciting avenues for research. However, efficiently interacting with these models presents a significant hurdle since LLMs often reside on proprietary or self-hosted API…
While there are high-quality software frameworks for information retrieval experimentation, they do not explicitly support cross-language information retrieval (CLIR). To fill this gap, we have created Patapsco, a Python CLIR framework.…
Experiments require human decisions in the design process, which in turn are reformulated and summarized as inputs into a system (computational or otherwise) to generate the experimental design. I leverage this system to promote a language…
Simulating learner actions helps stress-test open-ended interactive learning environments and prototype new adaptations before deployment. While recent studies show the promise of using large language models (LLMs) for simulating human…
Recently, the computational neuroscience community has pushed for more transparent and reproducible methods across the field. In the interest of unifying the domain of auditory neuroscience, naplib-python provides an intuitive and general…
In software development there is a constant pressure to produce code faster and faster without compromising on quality. New tools supporting developers are created in response to this demand. Currently a new generation of such solutions is…
Sequential algorithms are popular for experimental design, enabling emulation, optimisation and inference to be efficiently performed. For most of these applications bespoke software has been developed, but the approach is general and many…
Despite recent efforts to collect multi-task, multi-embodiment datasets, to design recipes for training Vision-Language-Action models (VLAs), and to showcase these models on different robot platforms, generalist cross-embodiment robot…