rlm

It's more-so recursive decomposition rather than clustering failures or stream summarizing. You can look at this repo if you want to learn more about how RLM's work: https://github.com/alexzhang13/rlm

Very interesting. Haven't heard of RLMs before. https://github.com/alexzhang13/rlm > We propose Recursive Language Models (RLMs), a general inference paradigm that treats long prompts as part of an external environment and allows the LLM to programmatically examine, decompose, and recursively call itself over snippets of the prompt. > We find that RLMs can successfully process inputs up to two orders of magnitude beyond model context windows and, even for shorter prompts, dramatically outperform the quality of vanilla frontier LLMs and common long-context and coding scaffolds [...] across four diverse long-context tasks while having comparable cost. https://arxiv.org/abs/2512.24601 I had a similar thought the other day. When doing a research task, you don't want to crap up the context with all the web scrapes. But you want to ask follow u

I am primarily experimenting on post training stack. As of now working on training a model that is natively RLM https://github.com/alexzhang13/rlm