LoRA (Low-Rank Adaptation)

This technical repository presents SRM-LoRA, a novel approach designed to minimize hallucinations in LLMs via specialized metric updates. The research demonstrates superior performance compared to standard LoRA techniques across various ablation studies.

Security researchers have proven that open-weight AI models can be maliciously backdoored using minimal resources and training data. This discovery highlights a critical lack of observability and verification capabilities in the current AI supply chain.

This paper proposes ReChannel, a novel architecture that transforms text-to-image models from RGB generators into efficient dense prediction engines. By treating transformer tokens as spatial carriers for task-specific data rather than RGB pixels, the method achieves new state-of-the-art performance with much higher computational efficiency.

This paper proposes ReChannel, a novel architecture that transforms text-to-image models from RGB generators into efficient dense prediction engines. By treating transformer tokens as spatial carriers for task-specific data rather than RGB pixels, the method achieves new state-of-the-art performance with much higher computational efficiency.