arXiv Machine Learning September 17, 2026 By Ho Fung Tsoi, Alex Yang, Luis Felipe Gutierrez Zagazeta, Shion Chen, Dylan Rankin

Self-Supervised Learning for Robust Resonance Mass Regression in Cascade Decays

Read the original on arXiv Machine Learning →

The paper presents a self‑supervised learning approach for reconstructing the mass of a heavy resonance in cascade decays with missing energy. By pre‑training a transformer encoder with VICReg to learn corruption‑invariant embeddings and then fine‑tuning for mass regression, the authors demonstrate sharper resonance peaks and more stable performance compared to a supervised model trained from scratch on the same data. The study focuses on resonances with masses between 2.5 and 6.5 TeV decaying into an eleven‑body final state.

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