ANU partners with AI safety company Anthropic to strengthen its AI research and teaching - anu.edu.au
<a href="https://news.google.com/rss/articles/CBMiwwFBVV95cUxQd1FoSHltem1yYjdFNzJGRFZtY0lOLXpnOVRiMzZENEdXZVRDYV9JQVRFbnNwdVB3QU5tYm4tWDF5V3YzYkIwYTdNYThVUjdRcjNoTmRQZWs4SWM0d1BZMi1VdEdHTG1xVWhrTkx4YzRrckVGZDFtRVdDdDVPSGFiQnBPR0tycHZrR0VSUndzODlFRi1STFM2R0NlN2RsbUo5Y3l1NzhlZmxvWXA0NHpNVDBYeGxwT0lJWFpvaUxUNDJma0U?oc=5" target="_blank">ANU partners with AI safety company Anthropic to strengthen its AI research and teaching</a> <font color="#6f6f6f">anu.edu.au</font>
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Containing the Reproducibility Gap: Automated Repository-Level Containerization for Scholarly Jupyter Notebooks
arXiv:2604.01072v1 Announce Type: new Abstract: Computational reproducibility is fundamental to trustworthy science, yet remains difficult to achieve in practice across various research workflows, including Jupyter notebooks published alongside scholarly articles. Environment drift, undocumented dependencies and implicit execution assumptions frequently prevent independent re-execution of published research. Despite existing reproducibility guidelines, scalable and systematic infrastructure for automated assessment remains limited. We present an automated, web-oriented reproducibility engineering pipeline that reconstructs and evaluates repository-level execution environments for scholarly notebooks. The system performs dependency inference, automated container generation, and isolated exe
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