# Net Utility

The work identifies the uniform assumption that every layer and every task receives the same rank budget as a major source of the gap between merged and per-task LoRAs, and introduces Net Utility, a data-free metric that decomposes each task LoRA by SVD, scores every singular direction by its benefit to its own task minus its interference with other tasks, and then globally selects the highest-scoring directions under a total rank budget; applied on top of five merging methods across three merging spaces on 7 vision and 6 language tasks, it improves performance by 2.1% on average for vision and 2.2% for language.

The work identifies the uniform assumption that every layer and every task receives the same rank budget as a major source of the gap between merged and per-task LoRAs, and introduces Net Utility, a data-free metric that decomposes each task LoRA by SVD, scores every singular direction by its benefit to its own task minus its interference with other tasks, and then globally selects the highest-scoring directions under a total rank budget; applied on top of five merging methods across three merging spaces on 7 vision and 6 language tasks, it improves performance by 2.1% on average for vision and 2.2% for language.