-
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper • 2309.12307 • Published • 88 -
NEFTune: Noisy Embeddings Improve Instruction Finetuning
Paper • 2310.05914 • Published • 14 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 56 -
Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon
Paper • 2401.03462 • Published • 27
Collections
Discover the best community collections!
Collections including paper arxiv:2405.01525
-
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 75 -
FLAME: Factuality-Aware Alignment for Large Language Models
Paper • 2405.01525 • Published • 25 -
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Paper • 2405.00732 • Published • 119 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 30