🌐 Entity

LoRA (machine learning)

Parameter-efficient fine-tuning technique for large language models

📊 Rating

3 news mentions · 👍 0 likes · 👎 0 dislikes

📌 Topics

Artificial Intelligence (3)
Machine Learning (3)
Data Efficiency (1)
Model Optimization (1)
Technology (1)

🏷️ Keywords

LoRA (3) · arXiv (2) · Machine learning efficiency (2) · Large Language Models (2) · Fine-tuning (1) · Foundation models (1) · Task similarity (1) · Data scarcity (1) · Finetuning (1) · Learning Rate Scaling (1) · Adapter Rank (1) · Hyperparameters (1) · SHINE (1) · Hypernetwork (1) · In-context learning (1)

📖 Key Information

LoRA (Low-Rank Adaptation) is a parameter-efficient fine-tuning technique for large language models and other deep neural networks. Introduced in 2021 by researchers at Microsoft, LoRA enables adaptation of pre-trained models to specific tasks while requiring significantly fewer computational resources and trainable parameters than traditional full model fine-tuning.

📰 Related News (3)

🇺🇸 Collaborative and Efficient Fine-tuning: Leveraging Task Similarity (2026-02-10)
arXiv:2602.07218v1 Announce Type: cross Abstract: Adaptability has been regarded as a central feature in the foundation models, enabling them to effe...
🇺🇸 Learning Rate Scaling across LoRA Ranks and Transfer to Full Finetuning (2026-02-09)
arXiv:2602.06204v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) is a standard tool for parameter-efficient finetuning of large models. W...
🇺🇸 SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass (2026-02-09)
arXiv:2602.06358v1 Announce Type: cross Abstract: We propose SHINE (Scalable Hyper In-context NEtwork), a scalable hypernetwork that can map diverse ...

🔗 Entity Intersection Graph

People and organizations frequently mentioned alongside LoRA (machine learning):

🌐 Large language model (2 shared articles)
🌐 Shine (1 shared articles)
🌐 Fine-tuning (1 shared articles)
🏢 Foundation model (1 shared articles)

Точка Синхронізації