Papers › ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type Inference
ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type Inference
Kevin Jesse, Premkumar T. Devanbu
In this paper, we present ManyTypes4TypeScript, a very large corpus for training and evaluating machine-learning models for sequence-based type inference in TypeScript. The dataset includes over 9 million type annotations, across 13,953 projects and 539,571 files. The dataset is approximately 10x larger than analogous type inference datasets for Python, and is the largest available for TypeScript. We also provide API access to the dataset, which can be integrated into any tokenizer and used with any state-of-the-art sequence-based model. Finally, we provide analysis and performance results for state-of-the-art code-specific models, for baselining. ManyTypes4TypeScript is available on Huggingface, Zenodo, and CodeXGLUE.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Type prediction | ManyTypes4TypeScript | GraphCodeBERT-MT4TS | Average Accuracy | 63.42 | #2 of 9 | Archive leaderboard | report |
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