Code Completion
63 papers with code • 4 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Code Completion
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Libraries
Use these libraries to find Code Completion models and implementationsDatasets
CodeXGLUE
PyTorrent
SAFIM
Most implemented papers
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Benchmark datasets have a significant impact on accelerating research in programming language tasks.
Open Vocabulary Learning on Source Code with a Graph-Structured Cache
Machine learning models that take computer program source code as input typically use Natural Language Processing (NLP) techniques.
Structural Language Models of Code
tech-srl/slm-code-generation
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ICML 2020
We introduce a new approach to any-code completion that leverages the strict syntax of programming languages to model a code snippet as a tree - structural language modeling (SLM).
Neural Software Analysis
The resulting tools complement and outperform traditional program analyses, and are used in industrial practice.
UniXcoder: Unified Cross-Modal Pre-training for Code Representation
microsoft/CodeBERT
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ACL 2022
Furthermore, we propose to utilize multi-modal contents to learn representation of code fragment with contrastive learning, and then align representations among programming languages using a cross-modal generation task.
Multi-lingual Evaluation of Code Generation Models
Using these benchmarks, we are able to assess the performance of code generation models in a multi-lingual fashion, and discovered generalization ability of language models on out-of-domain languages, advantages of multi-lingual models over mono-lingual, the ability of few-shot prompting to teach the model new languages, and zero-shot translation abilities even on mono-lingual settings.
Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
Large Language Models (LLMs) are increasingly being integrated into various applications.
CodeKGC: Code Language Model for Generative Knowledge Graph Construction
zjunlp/deepke
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However, large generative language model trained on structured data such as code has demonstrated impressive capability in understanding natural language for structural prediction and reasoning tasks.
MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with Transformers
Message Passing Interface (MPI) plays a crucial role in distributed memory parallelization across multiple nodes.
Scope is all you need: Transforming LLMs for HPC Code
scientific-computing-lab-nrcn/tokompiler
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With easier access to powerful compute resources, there is a growing trend in the field of AI for software development to develop larger and larger language models (LLMs) to address a variety of programming tasks.
