Program Synthesis on ManyTypes4TypeScript

Metric: Average Accuracy (higher is better)

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#	Model↕	Average Accuracy▼	Extra Data	Paper	Date↕	Code
1	CodeTIDAL5	71.27	No	Learning Type Inference for Enhanced Dataflow An...	2023-10-01	Code
2	GraphCodeBERT-MT4TS	63.42	No	-	-	Code
3	GraphCodeBERT	62.51	No	GraphCodeBERT: Pre-training Code Representations...	2020-09-17	Code
4	CodeBERT	61.72	No	CodeBERT: A Pre-Trained Model for Programming an...	2020-02-19	Code
5	PolyGot	61.29	No	Multilingual training for Software Engineering	2021-12-03	-
6	GraphPolyGot	61	No	Multilingual training for Software Engineering	2021-12-03	-
7	RoBERTa	59.84	No	RoBERTa: A Robustly Optimized BERT Pretraining A...	2019-07-26	Code
8	CodeBERTa	59.81	No	-	-	-
9	BERT	57.52	No	BERT: Pre-training of Deep Bidirectional Transfo...	2018-10-11	Code

#1CodeTIDAL5SOTA
71.27
Average Accuracy· 2023-10-01
Learning Type Inference for Enhanced Dataflow Analysis Code
#2GraphCodeBERT-MT4TS
63.42
Average Accuracy
No paperCode
#3GraphCodeBERTSOTA
62.51
Average Accuracy· 2020-09-17
GraphCodeBERT: Pre-training Code Representations with Data Flow Code
#4CodeBERTSOTA
61.72
Average Accuracy· 2020-02-19
CodeBERT: A Pre-Trained Model for Programming and Natural Languages Code
#5PolyGot
61.29
Average Accuracy· 2021-12-03
Multilingual training for Software Engineering
#6GraphPolyGot
61
Average Accuracy· 2021-12-03
Multilingual training for Software Engineering
#7RoBERTaSOTA
59.84
Average Accuracy· 2019-07-26
RoBERTa: A Robustly Optimized BERT Pretraining Approach Code
#8CodeBERTa
59.81
Average Accuracy
No paper
#9BERTSOTA
57.52
Average Accuracy· 2018-10-11
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Code