Papers by Rafae Abdullah
Context-Conditioned Masked LoRA: Dynamic Rank Routing for Compute-Efficient Parameter-Efficient Fine-Tuning (2026.findings-acl)
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| Challenge: | Large pretrained language models (LMs) are commonly adapted via fine-tuning, but full updates are costly at scale. |
| Approach: | They propose a lightweight router that activates an input-dependent subset of LoRA rank directions and turns it into dynamic rank routing. |
| Outcome: | The proposed method improves accuracy–efficiency Pareto frontier versus static-rank LoRA and adaptive-rank baselines, while preserving memory and reducing overhead. |