hard parameter sharing

**Hard parameter sharing** is **a multi-task architecture where tasks use exactly the same core parameters** - All tasks update one shared backbone, maximizing reuse and minimizing model size. **What Is Hard parameter sharing?** - **Definition**: A multi-task architecture where tasks use exactly the same core parameters. - **Core Mechanism**: All tasks update one shared backbone, maximizing reuse and minimizing model size. - **Operational Scope**: It is applied during data scheduling, parameter updates, or architecture design to preserve capability stability across many objectives. - **Failure Modes**: Strong coupling can amplify interference when tasks are weakly related. **Why Hard parameter sharing Matters** - **Retention and Stability**: It helps maintain previously learned behavior while new tasks are introduced. - **Transfer Efficiency**: Strong design can amplify positive transfer and reduce duplicate learning across tasks. - **Compute Use**: Better task orchestration improves return from fixed training budgets. - **Risk Control**: Explicit monitoring reduces silent regressions in legacy capabilities. - **Program Governance**: Structured methods provide auditable rules for updates and rollout decisions. **How It Is Used in Practice** - **Design Choice**: Select the method based on task relatedness, retention requirements, and latency constraints. - **Calibration**: Apply interference diagnostics and introduce selective decoupling if persistent conflicts appear. - **Validation**: Track per-task gains, retention deltas, and interference metrics at every major checkpoint. Hard parameter sharing is **a core method in continual and multi-task model optimization** - It delivers high parameter efficiency and simple deployment footprints.