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Found 6 papers, 4 papers with code
CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code
Recent works have widely adopted large language model pretraining for source code, suggested source code-specific pretraining objectives and investigated the applicability of various Transformer-based language model architectures for source code.
SantaCoder: don't reach for the stars!
The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code.
Probing Pretrained Models of Source Code
Deep learning models are widely used for solving challenging code processing tasks, such as code generation or code summarization.
Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems
Channel decoding, channel detection, channel assessment, and resource management for wireless multiple-input multiple-output (MIMO) systems are all examples of problems where machine learning (ML) can be successfully applied.
A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code
There is an emerging interest in the application of natural language processing models to source code processing tasks.
Empirical Study of Transformers for Source Code
In this work, we conduct a thorough empirical study of the capabilities of Transformers to utilize syntactic information in different tasks.
