SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass

• URL: http://arxiv.org/abs/2602.06358v1
• Date: Fri, 06 Feb 2026 03:40:31 GMT
• Title: SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
• Authors: Yewei Liu, Xiyuan Wang, Yansheng Mao, Yoav Gelbery, Haggai Maron, Muhan Zhang,
• Abstract summary: SHINE is a scalable hypernetwork that can map diverse meaningful contexts into high-quality LoRA adapters for large language models (LLM)<n>We introduce a pretraining and instruction fine-tuning pipeline, and train our hypernetwork to generate high quality LoRA adapters in a single forward pass.<n>Our work achieves outstanding results on various tasks, greatly saves time, computation and memory costs compared to SFT-based LLM adaptation, and shows great potential for scaling.
• Score: 55.28352410490407
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose SHINE (Scalable Hyper In-context NEtwork), a scalable hypernetwork that can map diverse meaningful contexts into high-quality LoRA adapters for large language models (LLM). By reusing the frozen LLM's own parameters in an in-context hypernetwork design and introducing architectural innovations, SHINE overcomes key limitations of prior hypernetworks and achieves strong expressive power with a relatively small number of parameters. We introduce a pretraining and instruction fine-tuning pipeline, and train our hypernetwork to generate high quality LoRA adapters from diverse meaningful contexts in a single forward pass. It updates LLM parameters without any fine-tuning, and immediately enables complex question answering tasks related to the context without directly accessing the context, effectively transforming in-context knowledge to in-parameter knowledge in one pass. Our work achieves outstanding results on various tasks, greatly saves time, computation and memory costs compared to SFT-based LLM adaptation, and shows great potential for scaling. Our code is available at https://github.com/Yewei-Liu/SHINE

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