Method Drift›Parameter-efficient fine-tuning (LoRA family)
Superseded baseline#106 of 1,113 most-superseded
Effort
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superseded — cited as a baseline and beaten by newer methods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 Effort. Values are copied from the source paper's tables — verify against the cited paper.
- LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection
LEGO beats Effort · AUC [Chameleon]
92.8 vs 83.7
- LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection
LEGO beats Effort · ACC [Chameleon]
83.6 vs 64.6
- LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection
LEGO beats Effort · EER [Chameleon]
15.0 vs 24.3
- LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection
LEGO beats Effort · A.P. [Chameleon]
89.9 vs 76.9
Newer alternatives
Recent methods in the same sub-problem, not yet superseded in the knowledge base.
- Structured Convolutional Projection + LoRAEfficient and Adaptive Human Activity Recognition via LLM BackbonesMay 12, 2026
- May 6, 2026
- layer-selective multimodal large language models (MLLMs) with contrastive LoRA tuning and layer sensitivity analysis (LSA)Fine-Grained Human Pose Editing Assessment via Layer-Selective MLLMsJan 15, 2026
- Dec 19, 2025