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Δ-Mem: Efficient Online Memory for Large Language Models

https://arxiv.org/abs/2605.12357
28•44za12•1h ago

Comments

DeathArrow•29m ago
I see lots of techniques proposed to give LLM the capacity to recall things, I even saw a lot of memory plugins for AI coding agents, I tried some myself.

What I want to see is something that was tested and proved in practice to be genuinely useful, especially for coding agents.

stephantul•13m ago
How would you conceptualize recall in this case? Is searching through the current version of your code and possibly git history not enough?
ktallett•29m ago
The obvious energy saving step would be to utilise previous searches by others. Many of the tasks people do are rather similar, it is such an energy waste to start again each time.

(Obviously ignoring the huge energy saver, which is to observe if you even need to bother doing the task at all.)

duskdozer•14m ago
A lot of what I see people using LLMs for would be more cheaply and reliably done by [scripts]. A search engine style suggestion thing like "Have you tried `sed`?" would be beneficial imo
3form•11m ago
Interesting points:

- fixed size of the memory seems like a good idea to overcome the current limitations

- skimming through the thing, I can't find any mention of the cost?

- I would need more time to read it in-depth to see if this is legitimate and not just fancy form of overfitting or training on testing data

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Δ-Mem: Efficient Online Memory for Large Language Models

https://arxiv.org/abs/2605.12357
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