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SOTA
基于文本的从头分子生成
Text Based De Novo Molecule Generation On
Text Based De Novo Molecule Generation On
评估指标
BLEU
Exact Match
Frechet ChemNet Distance (FCD)
Levenshtein
MACCS FTS
Morgan FTS
Parameter Count
RDK FTS
Text2Mol
Validity
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
BLEU
Exact Match
Frechet ChemNet Distance (FCD)
Levenshtein
MACCS FTS
Morgan FTS
Parameter Count
RDK FTS
Text2Mol
Validity
Paper Title
Repository
MolT5-Large
85.4
30.2
1.20
16.07
83.4
68.4
770000000
74.6
55.4
90.5
Translation between Molecules and Natural Language
-
GIT-Mol-caption
75.6
5.1
-
26.315
73.8
51.9
-
58.2
-
92.8
GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text
-
Text+Chem T5 base
75
21.2
0.061
27.39
87.4
69.7
220000000
76.7
-
79.2
Unifying Molecular and Textual Representations via Multi-task Language Modelling
-
MolReGPT (GPT-4-0413)
85.7
28.0
0.41
17.14
90.3
73.9
None
80.5
59.3
89.9
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
-
BioT5+
87.2
52.2
0.353
12.776
90.7
77.9
252000000
83.5
57.9
100
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
-
LDMol
92.6
53.3
0.20
6.750
97.3
93.1
-
95.0
-
94.1
LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR Models
-
MolT5-small
75.5
7.9
2.49
25.988
70.3
51.7
60000000
56.8
48.2
72.1
Translation between Molecules and Natural Language
-
MolReFlect
90.3
51.0
-
11.84
92.9
81.3
-
86.0
-
97.7
MolReFlect: Towards Fine-grained In-Context Alignment between Molecules and Texts
-
BioT5
86.7
41.3
.43
15.097
88.6
73.4
252000000
80.1
57.6
100
BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations
-
Text+Chem T5 small
73.9
15.7
0.066
28.54
85.9
66
60000000
73.6
-
77.6
Unifying Molecular and Textual Representations via Multi-task Language Modelling
-
MolFM-Small
80.3
16.9
-
20.868
83.4
72.1
13620000
66.2
57.3
85.9
MolFM: A Multimodal Molecular Foundation Model
-
MolReGPT (GPT-3.5-turbo)
79.0
13.9
0.57
24.91
84.7
62.4
-
70.8
57.1
88.7
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
-
Text+Chem T5-augm small
81.5
19.1
0.06
21.78
86.4
67.2
60000000
74.4
-
95.1
Unifying Molecular and Textual Representations via Multi-task Language Modelling
-
TGM-DLM
82.6
24.2
0.77
17.003
85.4
68.8
180000000
73.9
58.1
87.1
Text-Guided Molecule Generation with Diffusion Language Model
-
MolXPT
-
21.5
0.45
-
85.9
66.7
350000000
75.7
57.8
98.3
MolXPT: Wrapping Molecules with Text for Generative Pre-training
-
MolT5-Large-HV
81.0
31.4
0.44
16.758
87.2
72.2
770000000
78.6
59.0
99.6
Translation between Molecules and Natural Language
-
MolT5-base
76.9
8.1
2.18
24.458
72.1
52.9
220000000
58.8
49.6
77.2
Translation between Molecules and Natural Language
-
MolFM-Base
82.2
21.0
-
19.445
85.4
75.8
296200000
69.7
58.3
89.2
MolFM: A Multimodal Molecular Foundation Model
-
Text+Chem T5-augm base
85.3
32.2
.05
16.87
90.1
75.7
220000000
81.6
-
94.3
Unifying Molecular and Textual Representations via Multi-task Language Modelling
-
TGM-DLM w/o corr
82.8
24.2
0.89
16.897
87.4
72.2
180000000
77.1
58.9
78.9
Text-Guided Molecule Generation with Diffusion Language Model
-
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