LoRA training scripts of the world, unite!

Goodbye cold boot - how we made LoRA Inference 300% faster

PLoRA: Efficient Concurrent LoRA Training for Large Language Models

arXiv:2508. 02932v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has gained popularity as a fine-tuning approach for Large Language Models (LLMs) due to its low resource requirements and good performance.

Code Llama: Llama 2 learns to code

Beyond LoRA: Can you beat the most popular fine-tuning technique?

Two-Stage Mixture-of-LoRA for Multi-Task Medical Vision-Language Learning

arXiv:2609.14350v1 Announce Type: new Abstract: Medical vision-language models (VLMs) allow a single model to perform clinical image analysis tasks ranging from diagnosis classification to report gen...

Transformers Stop Thinking Too Early, and a Tiny LoRA Fixes It

The paper shows that pretrained transformers often stop using their depth early, following only a few lines of context. A small rank‑8 LoRA applied to an early layer can extend this chain‑following ability, enabling models like Qwen3‑8B to achieve near‑perfect accuracy on 24‑line chains and significantly longer chains with further training. The LoRA acts as a relay, passing chain identity through middle layers and allowing frozen heads to read further up the chain, with the last useful intervention layer identified in most held‑out models.