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Long-Transduction: A Controlled Diagnostic for Measuring Drift in Long-Horizon AI Agents

Long-Transduction: A Controlled Diagnostic for Measuring Drift in Long-Horizon AI Agents

A new preprint introduces Long-Transduction, a test designed to isolate how errors in AI models grow as context lengthens, input data formats change, or sub-task complexity increases. The authors report significant performance drops in seven open-weight models, highlighting a critical vulnerability for long-duration agentic workflows.

Mistral Large 4: a large-scale model whose performance still needs to be measured

Mistral Large 4: a large-scale model whose performance still needs to be measured

Mistral introduced Large 4 as a public preview and said it would release the weights at the end of October. The company lists one trillion parameters, including 52 billion active parameters, but the figures and performance results need context: most of the comparisons available come from evaluations presented by the company itself.