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Comments on that paper? PDF: [1] What they are measuring, it seems, is whether LLMs can be built which will retrieve a reliable known correct answer on request

Comments on that paper? PDF: [1] What they are measuring, it seems, is whether LLMs can be built which will retrieve a reliable known correct answer on request. That's an information retrieval problem, and, in fact, they solve it by adding "Memory Experts" which are basically data storage. It's not clear that this helps either replies which require synthesizing disparate information, or detecting that the training data does not contain info needed to construct a reply. [1] https://arxiv.org/pdf/2406.17642 https://arxiv.org/pdf/2406.17642

nickpsecurity 2y ago
On the second paragraph, there’s been work that shows whether a model has memorized or is strongly replying to certain prompts. Something like that combined with a memory-equipped model would tell you if it might contain the info. From there, you need multiple layers building on info it contains to synthesize a reply that might be good. Alternatively, an iterative process going a few rounds through a model, re-presenting the combo of results together, and it fuses them. All based on known data or what’s in the prompt with nothing else. This is speculative based on a few things our own minds do.