Systems and methods for adapting prediction models by compressing encoded data

A non-transitory computer-readable medium comprising:

• instructions that when executed by a processor cause the processor to:
• receive, by a subject vehicle, packets with compressed partial representations of a latent space associated with different views of target vehicles;
• generate an attention vector about the different views by aggregating the packets for the target vehicles;
• compute, by a prediction model, an addition vector that optimizes data decoding by the prediction model using acquired data from the attention vector;
• and
• train the prediction model using the addition vector to reduce data representations and adapt data compression associated with the latent space.

A method comprising:

• receiving, by a subject vehicle, packets with compressed partial representations of a latent space associated with different views of target vehicles;
• generating an attention vector about the different views by aggregating the packets for the target vehicles;
• computing, by a prediction model, an addition vector that optimizes data decoding by the prediction model using acquired data from the attention vector;
• and
• training the prediction model using the addition vector to reduce data representations and adapt data compression associated with the latent space.