Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper
• 2311.07989 • Published
• 26
Code LMs Evaluation
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SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Paper • 2310.06770 • Published • 9 -
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Paper • 2401.03065 • Published • 11 -
Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming
Paper • 2402.14261 • Published • 10 -
CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code
Paper • 2302.05527 • Published • 1 -
Copilot Refinement: Addressing Code Smells in Copilot-Generated Python Code
Paper • 2401.14176 • Published -
CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model
Paper • 2310.06266 • Published • 2 -
TACO: Topics in Algorithmic COde generation dataset
Paper • 2312.14852 • Published • 4 -
CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion
Paper • 2310.11248 • Published • 4 -
DevEval: Evaluating Code Generation in Practical Software Projects
Paper • 2401.06401 • Published -
CodeApex: A Bilingual Programming Evaluation Benchmark for Large Language Models
Paper • 2309.01940 • Published • 2 -
Improving Natural Language Capability of Code Large Language Model
Paper • 2401.14242 • Published • 1 -
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
Paper • 2305.01210 • Published • 3 -
A Static Evaluation of Code Completion by Large Language Models
Paper • 2306.03203 • Published • 3 -
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems
Paper • 2306.03091 • Published • 1 -
MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation
Paper • 2208.08227 • Published • 1 -
Large Language Models Are State-of-the-Art Evaluators of Code Generation
Paper • 2304.14317 • Published • 2 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 89 -
Textbooks Are All You Need
Paper • 2306.11644 • Published • 154 -
Evaluating Large Language Models Trained on Code
Paper • 2107.03374 • Published • 8 -
Design2Code: How Far Are We From Automating Front-End Engineering?
Paper • 2403.03163 • Published • 98 -
Large Language Models Meet NL2Code: A Survey
Paper • 2212.09420 • Published • 1 -
Large Language Models for Software Engineering: A Systematic Literature Review
Paper • 2308.10620 • Published • 1 -
Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
Paper • 2310.17903 • Published • 1 -
A Survey on Pretrained Language Models for Neural Code Intelligence
Paper • 2212.10079 • Published • 1 -
An Empirical Comparison of Pre-Trained Models of Source Code
Paper • 2302.04026 • Published • 1 -
Towards an Understanding of Large Language Models in Software Engineering Tasks
Paper • 2308.11396 • Published • 1 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 152 -
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
Paper • 2401.14196 • Published • 70 -
Unsupervised Evaluation of Code LLMs with Round-Trip Correctness
Paper • 2402.08699 • Published • 1 -
Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities
Paper • 2311.16169 • Published • 1 -
Magicoder: Source Code Is All You Need
Paper • 2312.02120 • Published • 82 -
On the Effectiveness of Large Language Models in Domain-Specific Code Generation
Paper • 2312.01639 • Published • 2 -
CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation
Paper • 2311.08588 • Published -
Fusion-Eval: Integrating Evaluators with LLMs
Paper • 2311.09204 • Published • 6 -
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
Paper • 2302.00288 • Published -
Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain
Paper • 2310.14053 • Published -
Can ChatGPT replace StackOverflow? A Study on Robustness and Reliability of Large Language Model Code Generation
Paper • 2308.10335 • Published -
CodeScore: Evaluating Code Generation by Learning Code Execution
Paper • 2301.09043 • Published -
InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
Paper • 2306.14898 • Published -
Language Models for Code Completion: A Practical Evaluation
Paper • 2402.16197 • Published • 1 -
DevBench: A Comprehensive Benchmark for Software Development
Paper • 2403.08604 • Published • 2 -
CodeEditorBench: Evaluating Code Editing Capability of Large Language Models
Paper • 2404.03543 • Published • 18 -
CodeCompose: A Large-Scale Industrial Deployment of AI-assisted Code Authoring
Paper • 2305.12050 • Published • 2 -
Stable Code Technical Report
Paper • 2404.01226 • Published • 1 -
CodeShell Technical Report
Paper • 2403.15747 • Published • 1 -
A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond
Paper • 2403.14734 • Published • 21 -
PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations
Paper • 2307.02762 • Published -
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models
Paper • 2405.01535 • Published • 124 -
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Paper • 2404.18796 • Published • 71