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Generative Task on PubMedQA labeled (0.8:0.2)

76.8AccuracyLoRA + SAM
18.35233.52648.763.874Jun 22, 2026

Evaluation results

MethodLinks
LoRA + SAMBackbone=Ministral-14B2026.0676.8
LoRA + NoisyTuneBackbone=Ministral-14B2026.0676.7
GRAINBackbone=Qwen-14B2026.0676.58
LoRA + PCGradBackbone=Qwen-14B2026.0676.1
LoRA + SWABackbone=Ministral-14B2026.0675.95
LoRA + SAMBackbone=Qwen-14B2026.0675.65
GRAINBackbone=Ministral-14B2026.0675.2
LoRA + FocalLossBackbone=Ministral-14B2026.0674.66
LoRABackbone=Qwen-14B2026.0674.58
LoRA + NoisyTuneBackbone=Qwen-14B2026.0674.2
GRAINBackbone=Qwen-7B2026.0674.15
LoRA + FocalLossBackbone=Qwen-14B2026.0673.8
LoRA + SWABackbone=Qwen-14B2026.0673.65
LoRA + PCGradBackbone=Ministral-14B2026.0673.15
LoRABackbone=Qwen-7B2026.0672.6
LoRA + FocalLossBackbone=Qwen-7B2026.0671.62
LoRA + SAMBackbone=Qwen-7B2026.0670.95
LoRA + NoisyTuneBackbone=Qwen-7B2026.0670.05
LoRA + PCGradBackbone=Mistral-7B2026.0669.9
LoRA + SWABackbone=Qwen-7B2026.0668.15
LoRABackbone=Ministral-14B2026.0667.9
GRAINBackbone=Mistral-7B2026.0667.6
LoRA + SWABackbone=Mistral-7B2026.0667.55
LoRA + SAMBackbone=Mistral-7B2026.0666.95
LoRA + PCGradBackbone=Qwen-7B2026.0666.4
LoRA + NoisyTuneBackbone=Mistral-7B2026.0664.86
LoRABackbone=Mistral-7B2026.0646.05
LoRA + FocalLossBackbone=Mistral-7B2026.0620.6