Dataset · Hugging Face

berryccc1/EVM-QuestBench

Name: EVM-QuestBench
Creator: berryccc1
License: mit
Keywords: task_categories:text-generation, annotations_creators:expert-generated, language_creators:expert-generated, multilinguality:monolingual, source_datasets:original, language:en, license:mit, size_categories:n<1K, format:json, modality:text, library:datasets, library:pandas, library:polars, library:mlcroissant, arxiv:2601.06565

EVM-QuestBench EVM-QuestBench is an execution-grounded benchmark for evaluating whether large language models and AI agents can translate natural-language blockchain intent into executable transaction code that produces the intended EVM state transition. Released with the ACL 2026 Long Paper by Pei Yang, Wanyi Chen, Ke Wang, Lynn Ai, Eric Yang, and Tianyu Shi, the benchmark contains 107 expert-authored tasks: 62 atomic tasks and 45 composite workflows. Unlike code-similarity… See the full description on the dataset page: https://huggingface.co/datasets/berryccc1/EVM-QuestBench.

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Author / organization	berryccc1
License (as declared)	mit
Downloads	259 (as reported by Hugging Face)
Likes	0
Created	18 August 2026
Last updated at source	18 August 2026

benchmarkcode-generationtransaction-code-generationexecution-grounded-evaluationblockchainevmethereumbscsmart-contractsdefillmllm-agentsagent-evaluationacl-2026

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