However, wecanmake(9)moretractable (bothforpredictionandtraining) byreducingittoa1-dimensional root-findingproblem: Find ?

This enables individual tasks tofully leverage inductivebiases provided byrelated tasks, therefore improving the overall performance of all tasks. Experimental results demonstrate that the proposed VMTL is able to effectively tackle a variety of challenging multi-task learning settings with limited training data for both classification and regression.

Unfortunately, existing faithfulness criteria for PRP are limited to coarse-grained LLM-based scoring without a clear definition or formulation.