LiST: Local-Simplex Test-Time LoRA Fusion
Task-specific LoRA adapters offer a modular way to specialize large language and vision-language models. However, existing adapter composition methods are mostly static and cannot adapt to individual test inputs. To address these issues, we propose \textbf{LiST}, a label-free test-time LoRA fusion framework that converts an existing LoRA bank into a target-conditioned local simplex and searches sample-specific fusion weights at inference time. LiST builds joint task representations from LoRA parameter anchors and prompt-level behavior vectors, retrieves neighboring adapters as a local search space, and performs branch-preserving fusion without updating the backbone or adapters. Candidate ...
| Authors | Yihua Shao, Jia Li, Siyu Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 23 August 2026 |
| Last updated at source | 31 August 2026 |
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