Papers by Dongwen Tang

1 papers
ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion (2025.findings-emnlp)

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Challenge: Existing approaches to low-rank Adaptation (LoRA) are limited in scalability and controllability.
Approach: They propose a conditional recurrent diffusion framework that generates LoRA parameters directly . they integrate model architecture and textual task specifications to generate task-specific parameters .
Outcome: The proposed framework scales to billions-of-parameter LLMs and maintains controllability.

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