[HN Gopher] Recursive Language Models (RLMs)
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Recursive Language Models (RLMs)
Author : talhof8
Score : 48 points
Date : 2025-10-15 17:43 UTC (5 hours ago)
(HTM) web link (alexzhang13.github.io)
(TXT) w3m dump (alexzhang13.github.io)
| jgbuddy wrote:
| This is old news! Agent-loops are not a model architechture
| laughingcurve wrote:
| Everything old is new again when you are in academia
| hodgehog11 wrote:
| This feels primarily like an issue with machine learning, at
| least among mathematical subdisciplines. As new people
| continue to be drawn into the field, they rarely bother to
| read what has come even a few years prior (nevermind a few
| decades prior).
| layer8 wrote:
| Loops aren't recursion?
| halfmatthalfcat wrote:
| It broke new ground!
| ayazhan wrote:
| https://arxiv.org/abs/2510.04871 another recursive based model
| yorwba wrote:
| It's a completely different kind of recursion for a completely
| different (non-language) task.
| gdiamos wrote:
| Recursion is so popular in computing that this term "recursive
| language model" is heavily overloaded
|
| It was even before the rise of LLMs
|
| The authors may want to consider a more specific name
| quibit wrote:
| > Lastly, in our experiments we only consider a recursive depth
| of 1 -- i.e. the root LM can only call LMs, not other RLMs. It is
| a relatively easy change to allow the REPL environment to call
| RLMs instead of LMs, but we felt that for most modern "long
| context" benchmarks, a recursive depth of 1 was sufficient to
| handle most problems. However, for future work and investigation
| into RLMs, enabling larger recursive depth will naturally lead to
| stronger and more interesting systems.
|
| It feels a little disingenuous to call it a Recursive Language
| Model when the recursive depth of the study was only 1.
| yandie wrote:
| This isn't just context optimization. Not much different from
| agent-to-agent workflow IMO.
| cs702 wrote:
| Briefly, an RLM wraps an existing language model (LM) together
| with an environment that can dynamically manipulate the prompt
| that will be fed into the LM.
|
| The authors use as an environment _a Python REPL that itself can
| call other instances of the LM_. The prompt is programmatically
| manipulated as a _Python variable_ on the REPL.
|
| The motivation is for the LM to use Python commands, including
| commands that call other LM instances, to figure out how best to
| modify the context at inference time.
|
| The results from early testing look impressive at a first glance:
| An RLM wrapping GPT-5-mini outperforms GPT-5 by a wide margin on
| long-context tasks, at significant lower cost.
|
| I've added this to my reading list.
| nowittyusername wrote:
| My existing project is very similar to this with some other
| goodies. I agree with the author that focus on systems versus
| LLM's is the proper next move. Orchestrating systems that manage
| multiple different llms and other scripts together can accomplish
| a lot more then a simple ping pong type of behavior. Though I
| suspect most people who work with agentic solutions are already
| quite aware of this. What most in that space haven't cracked yet
| is the dynamic self modifying and improving system, that should
| be the ultimate goal for these types of systems.
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