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Code Generation

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하위 태스크: 5
평가표: 28
보존된 평가 기록: 241

Code Generation is an important field to predict explicit code or program structure from multimodal data sources such as incomplete code, programs in another programming language, natural language descriptions or execution examples. Code Generation tools can assist the development of automatic programming tools to improve programming productivity.

Source: Deep Learning for Source Code Modeling and Generation

Image source: Measuring Coding Challenge Competence With APPS

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/0914eagle/code-diversity

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Is Functional Correctness Enough to Evaluate Code Language Models? Exploring Diversity of Generated Codes

https://github.com/22strongestme/LOCO-Annotations

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LogiCode: an LLM-Driven Framework for Logical Anomaly Detection

https://github.com/23japhone/halo

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HALO: Hierarchical Autonomous Logic-Oriented Orchestration for Multi-Agent LLM Systems

https://github.com/455849940/MPCoder

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MPCODER: Multi-user Personalized Code Generator with Explicit and Implicit Style Representation Learning

https://github.com/AICPS/LLM_4_PLC

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LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems

https://github.com/AUCOHL/RTL-Repo

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RTL-Repo: A Benchmark for Evaluating LLMs on Large-Scale RTL Design Projects

https://github.com/AhilanPonnusamy/Reverse-Generation-and-SBC-Metric--Reference-Implementation

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Bridging LLM-Generated Code and Requirements: Reverse Generation technique and SBC Metric for Developer Insights

https://github.com/Andreou-JHULabOrg/tinytapeout_05_chatgpt_snn

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Designing Silicon Brains using LLM: Leveraging ChatGPT for Automated Description of a Spiking Neuron Array

https://github.com/Avmb/code-docstring-corpus

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A parallel corpus of Python functions and documentation strings for automated code documentation and code generation

https://github.com/Avmb/semantic_neq_game

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Program Semantic Inequivalence Game with Large Language Models

https://github.com/BohdanPetryshyn/code-llama-fim-fine-tuning

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Optimizing Large Language Models for OpenAPI Code Completion

https://github.com/BohdanPetryshyn/openapi-completion-benchmark

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Optimizing Large Language Models for OpenAPI Code Completion

https://github.com/Bolin0215/CSCGDual

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Code Generation as a Dual Task of Code Summarization

https://github.com/CGCL-codes/naturalcc

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Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedback

https://github.com/CatIIIIIIII/veriseek

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Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning

https://github.com/ChuyueSun/Clover

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Clover: Closed-Loop Verifiable Code Generation

https://github.com/ClaasBeger/StructuralCodeUnderstanding

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CoCoNUT: Structural Code Understanding does not fall out of a tree

https://github.com/CodeEval-Pro/CodeEval-Pro

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HumanEval Pro and MBPP Pro: Evaluating Large Language Models on Self-invoking Code Generation

https://github.com/DIRECT-BIT/SRA-MCTS

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SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation

https://github.com/DeepAuto-AI/automl-agent

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AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

https://github.com/DeepLearnXMU/CG-RL

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Exploring Dynamic Selection of Branch Expansion Orders for Code Generation

https://github.com/DeepSoftwareAnalytics/CoSQA_Plus

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CoSQA+: Pioneering the Multi-Choice Code Search Benchmark with Test-Driven Agents

https://github.com/DfX-NYUAD/LLM4IC

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LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trust

https://github.com/DokiHollin/Multi-LLM-Based-Agent-RGD

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RGD: Multi-LLM Based Agent Debugger via Refinement and Generation Guidance

https://github.com/E-Nyamsuren/qLMM-Lua-Eval-Pipeline

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Evaluating Quantized Large Language Models for Code Generation on Low-Resource Language Benchmarks

https://github.com/FSoft-AI4Code/RepoExec

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On the Impacts of Contexts on Repository-Level Code Generation

https://github.com/FloatAI/HumanEval-XL

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HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization

https://github.com/GU-DataLab/Chatbot-Auditing-Framework

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It is Time to Develop an Auditing Framework to Promote Value Aware Chatbots

https://github.com/GeMoLLM/GeMO

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Generative Monoculture in Large Language Models

https://github.com/GitsSaikat/Pygen

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PyGen: A Collaborative Human-AI Approach to Python Package Creation

https://github.com/HKUNLP/DS-1000

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DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation

https://github.com/HosnLS/Hierarchical-Language-Agent

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LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordination

https://github.com/HumanEval-V/HumanEval-V-Benchmark

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HumanEval-V: Evaluating Visual Understanding and Reasoning Abilities of Large Multimodal Models Through Coding Tasks

https://github.com/IBM/Project_CodeNet

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CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks

https://github.com/IBM/nl2bash-eabench

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Execution-Based Evaluation of Natural Language to Bash and PowerShell for Incident Remediation

https://github.com/IPRC-DIP/ANPL

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ANPL: Towards Natural Programming with Interactive Decomposition

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