---
title: "Multi-Task Learning"
created: 2026-04-15
updated: 2026-04-15
type: concept
tags: [training]
sources: []
---

# Multi-Task Learning

Multi-Task Learning (MTL) is a learning paradigm where a single model is trained to perform multiple tasks simultaneously, leveraging shared representations to improve generalization. In the context of [[policy-distillation]], multi-task learning is relevant because distillation often involves transferring capabilities across multiple tasks or domains to a single student model.

## Related

- [[policy-distillation]] — Policy distillation naturally handles multi-task scenarios
- [[multi-domain-on-policy-distillation]] — Extension of OPD to multi-domain settings

## References