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Yang Gao

Researcher at University of Surrey

Publications -  2109
Citations -  158938

Yang Gao is an academic researcher from University of Surrey. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 168, co-authored 2047 publications receiving 146301 citations. Previous affiliations of Yang Gao include China Agricultural University & University of Kassel.

Papers
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Search for heavy lepton resonances decaying to a Z boson and a lepton in pp collisions at √s=8 TeV with the ATLAS detector

Georges Aad, +2878 more
- 16 Sep 2015 - 
TL;DR: In this paper, a search for heavy leptons decaying to a Z boson and an electron or a muon is presented, based on pp collision data taken at root s = 8TeV by the ATLAS experiment at the CERN Large Hadron Collider, corresponding to an integrated luminosity of 20.3 fb(-1).
Journal ArticleDOI

Updated search for long-lived particles decaying to jet pairs

Roel Aaij, +784 more
- 29 Nov 2017 - 
TL;DR: A search is presented for long-lived particles with a mass between 25 and 50 GeV/c2 and a lifetime between 2 and 500 ps, using proton–proton collision data corresponding to an integrated luminosity of 2.0 TeV.
Journal ArticleDOI

Search for the Standard Model Higgs boson produced in association with a vector boson and decaying to a b-quark pair with the ATLAS detector

Georges Aad, +2866 more
- 05 Dec 2012 - 
TL;DR: In this article, the results of a direct search with the ATLAS detector at the LHC for a Standard Model Higgs boson of mass 110 l(+)l(+)b (b) over bar, WH -> lvbb (b)) over bar and ZH ->...
Journal ArticleDOI

Search for pair-produced dijet resonances in four-jet final states in pp collisions at √s=7 TeV

S. Chatrchyan, +2190 more
- 04 Apr 2013 - 
TL;DR: A search for the pair production of a heavy, narrow resonance decaying into two jets has been performed using events collected in sqrt[s] = 7 TeV pp collisions with the CMS detector at the LHC.
Posted Content

SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarization

Yang Gao, +2 more
- 07 May 2020 - 
TL;DR: This work proposes SUPERT, which rates the quality of a summary by measuring its semantic similarity with a pseudo reference summary, i.e. selected salient sentences from the source documents, using contextualized embeddings and soft token alignment techniques.