HEPLocalAgent 1.0: Running Collider Simulations from Plain-Language Requests on Your Own Computer
Abstract
We present HEPLocalAgent, an open source local interface that builds a bounded class of collider simulation workflows from natural language requests. A locally served language model proposes a typed workflow representation, and deterministic software then restores recognized user stated quantities, builds the HEP tool inputs, validates the supported workflow, and presents the artifacts for approval before execution. In a same response comparison on 47 evaluable model request cases, the first structured proposal gave 7 unmodified artifacts satisfying the external benchmark scorer, against 19 after the full deterministic pipeline. Under the fixed representation normalization defined by the benchmark, the counts were 11 and 43. The direction of improvement is unchanged. The gap between the two views arises because the released builder and the benchmark scorers disagree on three bookkeeping conventions, namely launch form, two fixed control lines, and the output directory name, not on physics content. Four of seven approved workflows ran to completion on the managed local software stack, with cross sections consistent between repeats. In a separate challenge set, 57 of 96 problematic requests still reached the approval stage after part of the request was dropped, defaulted, or reinterpreted. No tested unsafe payload was retained in an executable artifact before the approval gate, but this does not establish operating system level containment. The deterministic backend supports MadGraph, Pythia8, Delphes, and a restricted MadAnalysis 5 plan. Reliable natural language routing to the MadAnalysis stage was not demonstrated in the tested examples. Version 1 should therefore be seen as an inspectable, validation gated workflow constructor requiring expert approval rather than an autonomous or scientifically self validating agent.
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BibTeX
@misc{singh2026heplocalagent,
title = {{HEPLocalAgent 1.0: Running Collider Simulations from Plain-Language Requests on Your Own Computer}},
author = {Aadarsh Singh and Sudhir K. Vempati},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.28244},
eprint = {2608.28244},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.28244},
}
RIS
TY - UNPB
TI - HEPLocalAgent 1.0: Running Collider Simulations from Plain-Language Requests on Your Own Computer
AU - Aadarsh Singh
AU - Sudhir K. Vempati
PY - 2026
DA - 2026/08/28
PB - arXiv
DO - 10.48550/arxiv.2608.28244
UR - https://arxiv.org/abs/2608.28244
AB - We present HEPLocalAgent, an open source local interface that builds a bounded class of collider simulation workflows from natural language requests. A locally served language model proposes a typed workflow representation, and deterministic software then restores recognized user stated quantities, builds the HEP tool inputs, validates the supported workflow, and presents the artifacts for approval before execution. In a same response comparison on 47 evaluable model request cases, the first structured proposal gave 7 unmodified artifacts satisfying the external benchmark scorer, against 19 after the full deterministic pipeline. Under the fixed representation normalization defined by the benchmark, the counts were 11 and 43. The direction of improvement is unchanged. The gap between the two views arises because the released builder and the benchmark scorers disagree on three bookkeeping conventions, namely launch form, two fixed control lines, and the output directory name, not on physics content. Four of seven approved workflows ran to completion on the managed local software stack, with cross sections consistent between repeats. In a separate challenge set, 57 of 96 problematic requests still reached the approval stage after part of the request was dropped, defaulted, or reinterpreted. No tested unsafe payload was retained in an executable artifact before the approval gate, but this does not establish operating system level containment. The deterministic backend supports MadGraph, Pythia8, Delphes, and a restricted MadAnalysis 5 plan. Reliable natural language routing to the MadAnalysis stage was not demonstrated in the tested examples. Version 1 should therefore be seen as an inspectable, validation gated workflow constructor requiring expert approval rather than an autonomous or scientifically self validating agent.
ER -