8,695 research outputs found
Neutrinos in the Simplest Little Higgs Model
The simplest little Higgs model based on a SU(3) global symmetry contains a
triplet and a singlet per a generation in the lepton sector. A
neutral component of the triplet and the singlet turn into a neutral
vector-like singlet after electroweak symmetry breaking while the
other neutral component of the triplet is the SM neutrino. At tree level,
Yukawa couplings of the lepton sector not only allow the neutral vector-like
lepton to couple to the SM neutrino, but also give them a Dirac mass. Majorana
mass terms for the SM neutrinos and their partners arise at one loops, leading
to neutrino flavor mixing in addition to neutrino-heavy neutral lepton mixing.Comment: 13 pages, 3 figures, contents change
Weakly-supervised Visual Grounding of Phrases with Linguistic Structures
We propose a weakly-supervised approach that takes image-sentence pairs as
input and learns to visually ground (i.e., localize) arbitrary linguistic
phrases, in the form of spatial attention masks. Specifically, the model is
trained with images and their associated image-level captions, without any
explicit region-to-phrase correspondence annotations. To this end, we introduce
an end-to-end model which learns visual groundings of phrases with two types of
carefully designed loss functions. In addition to the standard discriminative
loss, which enforces that attended image regions and phrases are consistently
encoded, we propose a novel structural loss which makes use of the parse tree
structures induced by the sentences. In particular, we ensure complementarity
among the attention masks that correspond to sibling noun phrases, and
compositionality of attention masks among the children and parent phrases, as
defined by the sentence parse tree. We validate the effectiveness of our
approach on the Microsoft COCO and Visual Genome datasets.Comment: CVPR 201
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