Verified claim · AI-ML · 100% confidence
LoRA (Low-Rank Adaptation) introduced in paper: LoRA: Low-Rank Adaptation of Large Language Models (Hu et al., 2021).
Last verified 2026-05-16 · Methodology veritas-v0.1 · f191b2876790dc6e
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Structured fields
- Subject
- LoRA (Low-Rank Adaptation)
- Predicate
introduced_in_paper- Object
- LoRA: Low-Rank Adaptation of Large Language Models (Hu et al., 2021)
- Confidence
- 100%
- Tags
- lora · peft · fine-tuning · foundational · 2021 · microsoft
Sources (2)
[1] preprint · arXiv (Hu, Shen, Wallis, Allen-Zhu, Li, Wang, Wang, Chen) · 2021-06-17
LoRA: Low-Rank Adaptation of Large Language Models“We propose Low-Rank Adaptation, or LoRA, which freezes the pre-trained model weights and injects trainable rank decomposition matrices into each layer of the Transformer architecture, greatly reducing the number of trainable parameters for downstream tasks.”
[2] github release · Microsoft · 2021-06-17
microsoft/LoRA — official implementation
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// "LoRA (Low-Rank Adaptation) introduced in paper: LoRA: Low-Rank Adaptation of Large Language Models (Hu et al., 2021)."Python
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# "LoRA (Low-Rank Adaptation) introduced in paper: LoRA: Low-Rank Adaptation of Large Language Models (Hu et al., 2021)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_lora_low_rank_adaptation_fact() -> dict:
"""Fetch the verified SourceScore claim for LoRA (Low-Rank Adaptation)."""
r = httpx.get("https://sourcescore.org/api/v1/claims/f191b2876790dc6e.json")
return r.json()