13 citations · 18 across the 7 of their papers we have counts for
4 papers · 1 filter
Assessing Parameter Redundancy in Transformers for Jet Tagging
Huitong Cheng, Yabo Dong, Jun Fan +4
Transformer-based jet taggers, such as the Particle Transformer (ParT) and the More-Interaction Particle Transformer (MIParT), achieve excellent discrimination by exploiting correl…
Deep-learning jet flavor tagging for precision hadronic Higgs measurements at future Higgs factories
Xinzhu Wang, Yifan Zhu, Chunxiang Zhu +5
Precise measurements of Higgs decays into quarks and gluons are essential for probing the Yukawa couplings of the Higgs boson and testing the flavor structure of the Standard Model…
Particle-level transformers for 95 GeV Higgs boson searches at future Higgs factories
Yabo Dong, Manqi Ruan, Kun Wang +2
Motivated by several mild excesses around 95~GeV, we investigate the prospects for a light scalar produced via Higgsstrahlung, , at future Higgs…
Testing a 95 GeV Scalar at the CEPC with Machine Learning
Yabo Dong, Manqi Ruan, Kun Wang +2
Several possible excesses around 95 GeV hint at an additional light scalar beyond the Standard Model. We examine the capability of the CEPC to test this hypothesis in the Higgsstra…