Sentence retrieval method [P]

I have been working on a memory management system SALT for a while now and the idea is that all input is saved in a trie structure in dram and then retrieved sentences based on a keyword theme dominance system through CELF currently at a 20% budget. It’s very efficient however most of the time too much is retrieved which makes smaller models hallucinate. Currently we have tried to use the theme coverage as a unit to measure how much we need to retrieve but it still get a lot of not important information within theme. It’s runs as a chatbot accuracy however we are adding agents now and we believe the memory will start becoming a huge issue once multiple modules are loaded despite the compression we have. So if anyone has any ideas or suggestions please share.

In GitHub it’s under oteomamo/salt