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ResearchFormerly WizWand

Regression on MoleculeNet LIPO

0.645RMSETokenMol
0.587920.973211.35851.74379Nov 19, 2022Jun 18, 2023Jan 16, 2024Aug 15, 2024Mar 15, 2025Oct 13, 2025May 13, 2026
Updated 5mo ago

Evaluation results

MethodLinks
TokenMol2025.120.645
ChemRL-GEMFine-tuned=true2022.110.66
LLM4SD2025.120.68
D-MPNNFine-tuned=true2022.110.683
SPMMPre-training=true, Fine-tuned=true2022.110.692
MoleculeSTM2025.120.6944
MolFormerFine-tuned=true2022.110.7
ChemATPBackbone=DeepSeek-V3.22025.120.7143
PretrainGNNFine-tuned=true2022.110.739
ChemBERTa-2Pre-training strategy=MTR, Pre-training size=10M2026.050.744
ChemBERTa-2Pre-training strategy=MTR, Pre-training size=5M2026.050.758
GCNPre-training strategy=None2026.050.781
ChemBERTa-2Fine-tuned=true2022.110.798
ChemBERTa-2Pre-training strategy=MTR, Pre-training size=77M2026.050.798
N-GramRFFine-tuned=true2022.110.812
GROVER_largeFine-tuned=true2022.110.823
Chem-GMNetPre-training strategy=MLM, Pre-training size=10M2026.050.932
Random ForestPre-training strategy=None2026.050.962
Chem-GMNetPre-training strategy=scratch, k=82026.050.968
ChemBERTa-2Pre-training strategy=MLM, Pre-training size=5M2026.050.986
ChemBERTa-2Pre-training strategy=MLM, Pre-training size=77M2026.050.987
SPMM (w/o pre-train)Pre-training=false, Fine-tuned=true2022.111.009
ChemBERTa-2Pre-training strategy=MLM, Pre-training size=10M2026.051.009
MolRAG2025.121.1251
CoTBackbone=DeepSeek-V3.2, Few-Shot=false2025.121.2098
D-MPNN (Chemprop)Pre-training strategy=None2026.051.212
CoT+FSBackbone=DeepSeek-V3.2, Few-Shot=true2025.121.2479
DABackbone=DeepSeek-V3.2, Few-Shot=false2025.121.3517
DA+FSBackbone=DeepSeek-V3.2, Few-Shot=true2025.121.4555
N-GramXGBFine-tuned=true2022.112.072