MIT CSAIL Explains: Recursive Language Models

Alex Zhang, Graduate Student | MIT EECS CSAIL
https://alexzhang13.github.io/blog/2025/rlm/

DIrector: Rachel Gordon
Preditor: Tim Malieckal
Script Supervisor: Alex Shipps

Chapters:

00:00 - Introduction
00:27 - LMs are more capable than we’ve realized
01:27 - What is a Recursive Language Model?
02:41 - What does your approach do that people are missing?
04:00 - What does treating a prompt as an environment enable?
05:36 - How does a RLM know what is worth looking at, and what isn’t?
07:30 - What does it take to build a RLM?
08:29 - An example of what a RLM can achieve that was out of reach before?
10:09 - Explain the ‘mismanaged genius’ hypothesis
11:33 - How does a RLM keep errors from compounding over many steps?
12:28 - How do RLMs fit into a multi-agent landscape?

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