<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Scalable Oversight by Learning to Decompose Tasks</title><description>Research notes from a project on scalable oversight: training an AI to break hard tasks into subtasks that weaker models, or humans, can reliably judge.</description><link>https://mai-alignment.github.io/superalignment-task-decomposition/</link><item><title>Decomposing difficult tasks is ... difficult</title><link>https://mai-alignment.github.io/superalignment-task-decomposition/updates/1_baselines/</link><guid isPermaLink="true">https://mai-alignment.github.io/superalignment-task-decomposition/updates/1_baselines/</guid><description>The system in which reasoning LLM decomposes complex tasks into simpler ones for a weaker LLM to implement loses with single zero-shot thinking LLM but wins with zero-shot non-thinking model. This leaves a lot of room for improvement.</description><pubDate>Wed, 04 Nov 2026 00:00:00 GMT</pubDate></item><item><title>Scalable oversight by learning to decompose tasks</title><link>https://mai-alignment.github.io/superalignment-task-decomposition/updates/0_vision/</link><guid isPermaLink="true">https://mai-alignment.github.io/superalignment-task-decomposition/updates/0_vision/</guid><description>Our vision and goals for scalable oversight over AI systems.</description><pubDate>Tue, 03 Nov 2026 00:00:00 GMT</pubDate></item></channel></rss>