Causal Orthogonal Representations for Multi-Task Learning
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CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations
arXiv:2606.02221v1 Announce Type: new Abstract: Multi-task learning (MTL) aims to construct a joint model for multiple tasks by sharing a common representation across domains. To achieve this goal, existing optimization-centric methods either balance task gradients or modify the shared architecture.