https://github.com/IBM/Project_CodeNet
공식 코드CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks
Papers with Code 아카이브
Code Translation
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Code translation is the process of converting code written in one programming language to another programming language while maintaining the same functionality. This process is also known as code conversion, source-to-source translation, or transpilation. Code translation is often performed when developers want to take advantage of new programming languages, improve code performance, or maintain legacy systems. Some common examples include translating code from Python to Java, or from JavaScript to TypeScript.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Intelligent-CAT-Lab/AlphaTrans
공식 코드https://github.com/RISElabQueens/InterTrans
공식 코드InterTrans: Leveraging Transitive Intermediate Translations to Enhance LLM-based Code Translation
https://github.com/adf1178/pt4code
공식 코드No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence
https://github.com/amazon-research/mbxp-exec-eval
공식 코드https://github.com/anirudhkhatry/crust-bench
공식 코드CRUST-Bench: A Comprehensive Benchmark for C-to-safe-Rust Transpilation
https://github.com/bin123apple/fortran-cpp-hpc-code-translation-dataset
공식 코드https://github.com/facebookresearch/CodeGen
공식 코드https://github.com/facebookresearch/CodeGen/blob/main/docs/dobf.md
공식 코드DOBF: A Deobfuscation Pre-Training Objective for Programming Languages
https://github.com/facebookresearch/mbr-exec
공식 코드https://github.com/geliang0114/nvagent
공식 코드nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflow
https://github.com/google-research/babelcode
공식 코드https://github.com/hpc-fortran2cpp/fortran2cpp
공식 코드https://github.com/huangd1999/EffiBench
공식 코드EffiBench: Benchmarking the Efficiency of Automatically Generated Code
https://github.com/imamnurby/transducer-tuning
공식 코드Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs
https://github.com/jordiae/neural-compilers
공식 코드Learning C to x86 Translation: An Experiment in Neural Compilation
https://github.com/jxh4945777/ChatEA
공식 코드Unlocking the Power of Large Language Models for Entity Alignment
https://github.com/kcxain/musl
공식 코드Mutual-Supervised Learning for Sequential-to-Parallel Code Translation
https://github.com/large-scale-sustainable-computing-lsc/green-code
공식 코드GREEN-CODE: Learning to Optimize Energy Efficiency in LLM-based Code Generation
https://github.com/magnumresearchgroup/bash_gen
공식 코드NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
https://github.com/magnumresearchgroup/magnum-nlc2cmd
공식 코드NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
https://github.com/mbzuai-llm/web2code
공식 코드Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs
https://github.com/microsoft/CodeBERT
공식 코드GraphCodeBERT: Pre-training Code Representations with Data Flow
https://github.com/microsoft/CodeXGLUE
공식 코드CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
https://github.com/microsoft/monitors4codegen
공식 코드Guiding Language Models of Code with Global Context using Monitors
https://github.com/moment-timeseries-foundation-model/timeseriesgym
공식 코드TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
https://github.com/neucol/llm-conversion-performance
공식 코드https://github.com/neuir/intervenor
공식 코드https://github.com/p-lambda/composed_finetuning
공식 코드Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization
https://github.com/p-lambda/unlabeled_outputs
공식 코드Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization
https://github.com/pootiet/explain-then-translate
공식 코드https://github.com/prithwishjana/cotran
공식 코드https://github.com/qiushisun/transcoder
공식 코드TransCoder: Towards Unified Transferable Code Representation Learning Inspired by Human Skills
https://github.com/reddy-lab-code-research/PPOCoder
공식 코드Execution-based Code Generation using Deep Reinforcement Learning
https://github.com/reddy-lab-code-research/codeattack
공식 코드CodeAttack: Code-Based Adversarial Attacks for Pre-trained Programming Language Models
https://github.com/reddy-lab-code-research/structcoder
공식 코드StructCoder: Structure-Aware Transformer for Code Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.