Method Drift›Parameter-efficient fine-tuning (LoRA family)
Superseded baseline#735 of 1,113 most-superseded
LIFT
LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning TasksParameter-efficient fine-tuning (LoRA family) · first seen Jun 14, 2022
superseded — cited as a baseline and beaten by newer methods
1 papers critique it · 0 beat it on benchmarks
What papers say
Verbatim critique sentences, each from a paper that cites LIFT as a baseline.
“Although effective, these methods require substantial storage equivalent to the full model since all parameters are being updated. Furthermore, these approaches do not deeply explore joint use with PEFT and have employed relatively simple selection strategies, limiting their performance.”
— Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models
Newer alternatives
Recent methods in the same sub-problem, not yet superseded in the knowledge base.