Method Drift›Parameter-efficient fine-tuning (LoRA family)
Superseded baseline#101 of 1,113 most-superseded
CoOp
Parameter-efficient fine-tuning (LoRA family)
superseded — cited as a baseline and beaten by newer methods
0 papers critique it · 2 beat it on benchmarks
Beaten on benchmarks
Head-to-head results where a newer method reports beating CoOp. Values are copied from the source paper's tables — verify against the cited paper.
- Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Network
99.02 beats CoOp · accuracy [Flowers102]
99.02 vs 94.51
- Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Network
92.63 beats CoOp · accuracy [Oxford Pets]
92.63 vs 87.01
- Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Network
78.46 beats CoOp · accuracy [Food101]
78.46 vs 74.67
- ACE-LoRA: Graph-Attentive Context Enhancement for Parameter-Efficient Adaptation of Medical Vision-Language Models
ACE-LoRA beats CoOp · Accuracy [Zero-shot classification (Radiology)]
49.80 vs 40.90
Newer alternatives
Recent methods in the same sub-problem, not yet superseded in the knowledge base.