A language model is trained exclusively on text sequences with a maximum length of 1024 tokens. Its design includes a component where a unique, learnable numerical bias is assigned to every possible relative distance between token pairs (e.g., a specific bias for a distance of 1, another for a distance of 2, up to the maximum possible distance in the training data). What is the most likely outcome when this model is later tasked with processing a document of 1500 tokens?

Critique of a Relative Positional Bias Method

Diagnosing Model Generalization Failure