Text-to-Code Generation
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Benchmarks
CodeXGLUE - CONCODE
Most implemented
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
Magicoder: Empowering Code Generation with OSS-Instruct
Bridging the Gap Between Open-Source and Proprietary LLMs in Table QA
Planning-Driven Programming: A Large Language Model Programming Workflow
Papers
CS-Guard: Benchmarking LLM Guardrails for Code Generation Security
Large language models (LLMs) have been ex- ploited to generate malware, but the effective- ness of guardrails for code generation secu- rity remains unclear. We introduce CS-Guard, the first benchmark to systematically e…
Text-to-Code GenerationCode TranslationCode CompletionExploring different approaches to customize language models for domain-specific text-to-code generation
Large language models (LLMs) have demonstrated strong capabilities in generating executable code from natural language descriptions. However, general-purpose models often struggle in specialized programming contexts wher…
parameter-efficient fine-tuningText-to-Code GenerationFew-Shot LearningCangjieBench: Benchmarking LLMs on a Low-Resource General-Purpose Programming Language
Large Language Models excel in high-resource programming languages but struggle with low-resource ones. Existing research related to low-resource programming languages primarily focuses on Domain-Specific Languages (DSLs…
Text-to-Code GenerationCode TranslationBridging the Gap Between Open-Source and Proprietary LLMs in Table QA
This paper presents a system developed for SemEval 2025 Task 8: Question Answering (QA) over tabular data. Our approach integrates several key components: text-to-SQL and text-to-code generation modules, a self-correctio…
Code GenerationLanguage ModelingLanguage ModellingLarge Language Model+6Aligning Crowd-sourced Human Feedback for Reinforcement Learning on Code Generation by Large Language Models
This paper studies how AI-assisted programming and large language models (LLM) improve software developers' ability via AI tools (LLM agents) like Github Copilot and Amazon CodeWhisperer, while integrating human feedback…
Bayesian OptimizationCode GenerationLanguage ModelingLanguage Modelling+2Planning-Driven Programming: A Large Language Model Programming Workflow
The strong performance of large language models (LLMs) raises extensive discussion on their application to code generation. Recent research suggests continuous program refinements through visible tests to improve code ge…
Code GenerationHumanEvalLanguage ModelingLanguage Modelling+4