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Molecular property prediction on BACE (test)

89.4ROC-AUCBioT5
47.59258.44669.380.154Jun 8, 2020Jan 20, 2021Sep 4, 2021Apr 18, 2022Dec 1, 2022Jul 15, 2023Feb 27, 2024
Updated 5mo ago

Evaluation results

MethodLinks
BioT5Model Category=Single-task Specialist Models2024.0289.4
MolCLRModel Category=Single-task Specialist Models2024.0289
MolXPTModel Category=Single-task Specialist Models2024.0288.4
ProtoW-L2Contrastive regularization=true, Distance metric=L22020.0687.3
ProtoW-DotContrastive regularization=true, Distance metric=Dot2020.0687.1
Fingerprint+MLP2020.0687
ProtoW-L2Contrastive regularization=false, Distance metric=L22020.0687
ProtoW-DotContrastive regularization=false, Distance metric=Dot2020.0686.7
D-MPNNPooling method=summation2020.0686.5
ProtoS-L2Contrastive regularization=true, Distance metric=L22020.0686.5
BioT5+Model Category=LLM-based Generalist Models2024.0286.2
GINPooling method=summation2020.0686.1
GATPooling method=summation2020.0686
D-MPNN+TopK PoolPooling method=TopK Pool2020.0686
InstructMol-G-6.9BModel Category=LLM-based Generalist Models2024.0285.9
GPF-plusPre-training Strategy=ContextPred2022.0985.81
GPF-plusPre-training Strategy=AttrMasking2022.0985.76
Uni-MolModel Category=Single-task Specialist Models2024.0285.7
GEMModel Category=Single-task Specialist Models2024.0285.6
D-MPNN+SAG PoolPooling method=SAG Pool2020.0685.5
GPFPre-training Strategy=ContextPred2022.0985.32
SUPTsoftPre-training Strategy=ContextPred2024.0285.27
SUPTsoftPre-training Strategy=AttrMasking2024.0285.22
SUPThardPre-training Strategy=ContextPred2024.0285.21
GPFPre-training Strategy=ContextPred2024.0285.03
GPF-plusPre-training Strategy=AttrMasking2024.0285.01
SUPThardPre-training Strategy=AttrMasking2024.0284.98
GPFPre-training Strategy=AttrMasking2024.0284.77
FTPre-training Strategy=ContextPred2022.0984.66
FTPre-training Strategy=ContextPred2024.0284.66
GPF-plusPre-training Strategy=ContextPred2024.0284.5
GPFPre-training Strategy=AttrMasking2022.0984.33
SUPThardPre-training Strategy=Infomax2024.0284.05
SUPTsoftPre-training Strategy=Infomax2024.0284.01
MolFMModel Category=Single-task Specialist Models2024.0283.9
GPF-plusPre-training Strategy=Infomax2022.0983.67
GPFPre-training Strategy=Infomax2022.0983.6
GPFPre-training Strategy=Infomax2024.0283.24
GPF-plusPre-training Strategy=Infomax2024.0282.96
InstructMol-GS-6.9BModel Category=LLM-based Generalist Models2024.0282.3
GPF-plusPre-training Strategy=EdgePred2022.0981.75
SUPThardPre-training Strategy=EdgePred2024.0281.72
GPFPre-training Strategy=EdgePred2022.0981.57
SUPTsoftPre-training Strategy=EdgePred2024.0281.44
FTPre-training Strategy=Infomax2022.0981.32
FTPre-training Strategy=Infomax2024.0281.32
GraphMVP-CModel Category=Single-task Specialist Models2024.0281.2
GIT-MolInput Modality=Graph + SMILES2023.0881.08
FTPre-training Strategy=AttrMasking2022.0980.94
FTPre-training Strategy=AttrMasking2024.0280.94
GPF-plusPre-training Strategy=EdgePred2024.0280.91
FTPre-training Strategy=EdgePred2022.0980.9
FTPre-training Strategy=EdgePred2024.0280.9
Mole-BERT2023.0880.8
GPFPre-training Strategy=EdgePred2024.0279.76
MGSSL (DFS)Backbone=GIN, Evaluation Protocol=Fine-tuning2021.1079.7
MGSSLModel Category=Single-task Specialist Models2024.0279.7
GPF-plusPre-training Strategy=GCL2022.0979.61
GroverBackbone=GIN, Evaluation Protocol=Fine-tuning2021.1079.5
GraphMVP2023.0879.3
SUPThardPre-training Strategy=GCL2024.0279.17
MGSSL (BFS)Backbone=GIN, Evaluation Protocol=Fine-tuning2021.1079.1
SUPTsoftPre-training Strategy=GCL2024.0278.92
GPFPre-training Strategy=GCL2022.0978.55
GPT-GNNBackbone=GIN, Evaluation Protocol=Fine-tuning2021.1078.5
KV-PLM2023.0878.5
Attribute maskingBackbone=GIN, Evaluation Protocol=Fine-tuning2021.1078.3
GPF-plusPre-training Strategy=GCL2024.0277.84
MoMuModel Category=Single-task Specialist Models2024.0276.7
MoMu2023.0876.7
GPFPre-training Strategy=GCL2024.0276.67
FTPre-training Strategy=GCL2022.0975.51
FTPre-training Strategy=GCL2024.0275.51
GraphCLModel Category=Single-task Specialist Models2024.0275.4
InfomaxBackbone=GIN, Evaluation Protocol=Fine-tuning2021.1075
GCCBackbone=GIN, Evaluation Protocol=Fine-tuning2021.1075
Llama-2-7B-chatModel Category=LLM-based Generalist Models, tuning=LoRA2024.0274.8
GraphCL2023.0874.6
Galactica-30BModel Category=LLM-based Generalist Models2024.0272.7
KV-PLMModel Category=Single-task Specialist Models2024.0271.9
GPPTPre-training Strategy=EdgePred2022.0970.85
GPPTPre-training Strategy=EdgePred2024.0270.85
GPPT (w/o ol)Pre-training Strategy=EdgePred2022.0970.31
GPPTw/o olPre-training Strategy=EdgePred2024.0270.31
No pretrainBackbone=GIN, Evaluation Protocol=Fine-tuning2021.1070
GIT-MolInput Modality=SMILES2023.0868.4
Vicuna-v1.3-7BModel Category=LLM-based Generalist Models, tuning=LoRA2024.0268.3
GraphPromptPre-training Strategy=EdgePred2022.0967.7
GraphPromptPre-training Strategy=EdgePred2024.0267.7
GIT-MolInput Modality=Graph2023.0865.8
Galactica-120BModel Category=LLM-based Generalist Models2024.0261.7
Galactica-6.7BModel Category=LLM-based Generalist Models2024.0258.4
Vicuna-v1.5-13B-16kModel Category=LLM-based Generalist Models, Shot=4-shot2024.0249.2