Computer Science > Computation and Language
arXiv:2601.06565 (cs)
[Submitted on 10 Jan 2026 (v1), last revised 10 Mar 2026 (this version, v2)]
Title:EVM-QuestBench: An Execution-Grounded Benchmark for Natural-Language Transaction Code Generation
View a PDF of the paper titled EVM-QuestBench: An Execution-Grounded Benchmark for Natural-Language Transaction Code Generation, by Pei Yang and 5 other authors
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Abstract:Large language models are increasingly applied to various development scenarios. However, in on-chain transaction scenarios, even a minor error can cause irreversible loss for users. Existing evaluations often overlook execution accuracy and safety. We introduce EVM-QuestBench, an execution-grounded benchmark for natural-language transaction-script generation on EVM-compatible chains. The benchmark employs dynamic evaluation: instructions are sampled from template pools, numeric parameters are drawn from predefined intervals, and validators verify outcomes against these instantiated values. EVM-QuestBench contains 107 tasks (62 atomic, 45 composite). Its modular architecture enables rapid task development. The runner executes scripts on a forked EVM chain with snapshot isolation; composite tasks apply step-efficiency decay. We evaluate 20 models and find large performance gaps, with split scores revealing persistent asymmetry between single-action precision and multi-step workflow completion. Code: this https URL.
| Comments: | |
| Subjects: | Computation and Language (cs.CL) |
| ACM classes: | I.2.7 |
| Cite as: | arXiv:2601.06565 [cs.CL] |
| (or arXiv:2601.06565v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2601.06565
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Submission history
From: Wanyi Chen [view email][v1] Sat, 10 Jan 2026 13:25:27 UTC (362 KB)
[v2] Tue, 10 Mar 2026 07:27:42 UTC (1,179 KB)
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View a PDF of the paper titled EVM-QuestBench: An Execution-Grounded Benchmark for Natural-Language Transaction Code Generation, by Pei Yang and 5 other authors
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