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Text-to-Code Generation datasets

archive 2025-07-28

10 datasets carry the task tag "Text-to-Code Generation" (the task itself: Text-to-Code Generation), ordered by the archive's paper count. Page 1 of 1: 10 shown of 10. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

All 12,172 Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52Text-to-Code Generation 10

Text-to-Code Generation datasets 1–10 of 10

CodeXGLUE
CodeXGLUE is a benchmark dataset and open challenge for code intelligence.
TextsCode GenerationCode SearchCode CompletionDefect DetectionDocument TranslationClone Detection+5 tasks
205 papers · 10 benchmarks
CodeContests
CodeContests is a competitive programming dataset for machine-learning.
TextsCode GenerationText-to-Code Generation
84 papers · 1 benchmark
PyTorrent
PyTorrent contains 218,814 Python package libraries from PyPI and Anaconda environment.
TextsCode GenerationCode SearchCode Documentation GenerationCode CompletionAnnotated Code SearchCode Translation+7 tasks
5 papers · 0 benchmarks
SAFIM (Syntax-Aware Fill-In-the-Middle)
Syntax-Aware Fill-in-the-Middle (SAFIM) is a benchmark for evaluating Large Language Models (LLMs) on the code Fill-in-the-Middle (FIM) task.
TextsCode GenerationCode CompletionText-to-Code Generation
5 papers · 1 benchmark
BlendNet
📚 BlendNet The dataset contains $12k$ samples.
Texts3D3d meshesCadCAD Reconstruction3D Shape ModelingText-to-Code GenerationText to 3D
1 paper · 0 benchmarks
CADBench
📚 CADBench CADBench is a comprehensive benchmark to evaluate the ability of LLMs to generate CAD scripts.
Texts3D3d meshesCadCAD Reconstruction3D Shape ModelingText-to-Code GenerationText to 3D
1 paper · 0 benchmarks
MICRO25
To assess a model’s ability to create microcontroller-driven electronic devices, we developed a benchmark, MICRO25, that includes 25 tasks intended for the common ARDUINO microcontroller ecosystem..
TextsText-to-Code Generation
1 paper · 0 benchmarks
RES-Q (RES-Q: Evaluating Code-Editing Large Language Model Systems at the Repository Scale)
RES-Q is a natural language instruction-based benchmark for evaluating Repository Editing Systems, which consists of 100 handcrafted repository editing tasks derived from real GitHub commits.
TextsCode GenerationCode SearchText-to-Code GenerationLibrary-Oriented Code Generation
1 paper · 1 benchmark
Verireason-RTL-Coder_7b_reasoning_tb (VeriReason Verilog Dataset with Reasoning, Testbench, and Simulation Results)
Verireason-RTL-Coder7breasoningtb For implementation details, visit our GitHub repository: VeriReason Check out our paper: VeriReason: Reinforcement Learning with Testbench Feedback for Reasoning-Enhanced Verilog Generation Update Log…
TextsCode GenerationText-to-Code Generation
1 paper · 0 benchmarks
Verireason-RTL-Coder_7b_reasoning_tb_simple (Simple Problems of VeriReason Verilog Dataset with Reasoning, Testbench, and Simulation Results)
Verireason-RTL-Coder7breasoningtbsimple For implementation details, visit our GitHub repository: VeriReason Check out our paper: VeriReason: Reinforcement Learning with Testbench Feedback for Reasoning-Enhanced Verilog Generation Update…
TextsCode GenerationText-to-Code Generation
1 paper · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.