If the weights never change, is it really recursive self-improvement?
Mirrored from r/LocalLLaMA for archival readability. Support the source by reading on the original site.
| This paper is using a much narrower definition of recursive self-improvement than the phrase usually suggests. AQuA stores validated evidence in a persistent research state that shapes later hypotheses. The underlying language model and evaluator remain fixed. I still find the narrower claim interesting, even if it sits closer to memory-augmented research automation than to a model rewriting itself. The paper does not establish any weight-level capability gain. Is persistent memory that improves later research decisions enough to call a system RSI, or should the term require changes to the system’s underlying capabilities? [link] [comments] |
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