{"paper":{"title":"Benchmarking Machine Learning Architectures for ttH Multilepton Signal Sensitivity","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"hep-ph","authors_text":"Andr\\'e Sopczak, Luk\\'a\\v{s} Vicen\\'ik, Oleksandr Shekhovtsov","submitted_at":"2026-07-20T14:55:38Z","abstract_excerpt":"Statistical testing for signal discovery and signal-strength estimation in high-energy physics increasingly relies on machine-learning models trained on simulated data. We present a synthetic dataset for $t\\bar t H$ multilepton signal--background classification and perform a systematic evaluation of machine-learning models ranging from the widely used XGBoost for tabular data to LorentzNet, which processes events with built-in Lorentz symmetry. Existing studies often differ in feature definitions, training procedures, and evaluation metrics, making it difficult to isolate the impact of model a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18022","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.18022/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}