Low bit parameters is always talked about in terms of performance benefits but I wonder if allowing the LLM to combine parameters to represent values, means it

Low bit parameters is always talked about in terms of performance benefits but I wonder if allowing the LLM to combine parameters to represent values, means it can select the resolution of each value, that is use a kind of internal scientific notation to track the uncertainty of values. More low bit parameters combined together means more precision and resolution, less can mean more uncertainty. This might allow the LLM to better calibrate the uncertainty of it's knowledge in a Bayesian way, to prevent hallucinations from the overconfidence you get from overfitting on too many bits.