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Code Generation
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Cataloguing Hugging Face Models to Software Engineering Activities: Automation and Findings
Large Language Model Guided Self-Debugging Code Generation
Towards Functional Correctness of Code Models with Selective Generation
CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning
Towards Formal Verification of LLM-Generated Code from Natural Language Prompts
MERA Code: A Unified Framework for Evaluating Code Generation Across Tasks
Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training
Function-to-Style Guidance of LLMs for Code Translation
The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMs
Turning the Tide: Repository-based Code Reflection
CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks
CodeAssistBench (CAB): Dataset & Benchmarking for Multi-turn Chat-Based Code Assistance
Kodezi Chronos: A Debugging-First Language Model for Repository-Scale, Memory-Driven Code Understanding
Multilingual Multimodal Software Developer for Code Generation
OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique
Automating MD simulations for Proteins using Large language Models: NAMD-Agent
Rethinking Verification for LLM Code Generation: From Generation to Testing
ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
Learn Globally, Speak Locally: Bridging the Gaps in Multilingual Reasoning
EvoAgentX: An Automated Framework for Evolving Agentic Workflows
CoreCodeBench: A Configurable Multi-Scenario Repository-Level Benchmark
CORE: Benchmarking LLMs Code Reasoning Capabilities through Static Analysis Tasks
LLM-based Realistic Safety-Critical Driving Video Generation
A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis
Where to find Grokking in LLM Pretraining? Monitor Memorization-to-Generalization without Test
Estimating Correctness Without Oracles in LLM-Based Code Generation
SACL: Understanding and Combating Textual Bias in Code Retrieval with Semantic-Augmented Reranking and Localization
Language Modeling by Language Models
SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models
ReCode: Updating Code API Knowledge with Reinforcement Learning
DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
From Reproduction to Replication: Evaluating Research Agents with Progressive Code Masking
Why Do Open-Source LLMs Struggle with Data Analysis? A Systematic Empirical Study
QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges
Use Property-Based Testing to Bridge LLM Code Generation and Validation
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