SOTAVerified

Code Generation

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

Papers

Showing 110 of 1697 papers

TitleStatusHype
CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning0
Towards Formal Verification of LLM-Generated Code from Natural Language Prompts0
MERA Code: A Unified Framework for Evaluating Code Generation Across Tasks0
Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training0
The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMsCode2
Turning the Tide: Repository-based Code Reflection0
CodeAssistBench (CAB): Dataset & Benchmarking for Multi-turn Chat-Based Code Assistance0
CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks0
Kodezi Chronos: A Debugging-First Language Model for Repository-Scale, Memory-Driven Code UnderstandingCode9
Multilingual Multimodal Software Developer for Code Generation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EG-CFG (DeepSeek-V3-0324)Test Set pass@158.18Unverified
2LPW (GPT-4o)Test Set pass@134.7Unverified
3MapCoder (GPT-4)Test Set pass@128.5Unverified
4CodeSim (GPT4)Test Set pass@128.4Unverified
5MoTCoder-15BTest Set pass@126.34Unverified
6MoTCoder-7B-v1.5Test Set pass@120.77Unverified
7CodeChain + WizardCoder-15BTest Set pass@12.35Unverified
8WizardCoder-15BTest Set pass@11.11Unverified