Task-set switching with natural scenes: Measuring the cost of deploying top-down attention

In many everyday situations, we bias our perception from the top down, based on a task or an agenda. Frequently, this entails shifting attention to a specific attribute of a particular object or scene. To explore the cost of shifting top-down attention to a different stimulus attribute, we adopt the task-set switching paradigm, in which switch trials are contrasted with repeat trials in mixed-task blocks and with single-task blocks. Using two tasks that relate to the content of a natural scene in a gray-level photograph and two tasks that relate to the color of the frame around the image, we were able to distinguish switch costs with and without shifts of attention. We found a significant cost in reaction time of 23–31 ms for switches that require shifting attention to other stimulus attributes, but no significant switch cost for switching the task set within an attribute. We conclude that deploying top-down attention to a different attribute incurs a significant cost in reaction time, but that biasing to a different feature value within the same stimulus attribute is effortless

Scene Graph Generation by Iterative Message Passing

Understanding a visual scene goes beyond recognizing individual objects in isolation. Relationships between objects also constitute rich semantic information about the scene. In this work, we explicitly model the objects and their relationships using scene graphs, a visually-grounded graphical structure of an image. We propose a novel end-to-end model that generates such structured scene representation from an input image. The model solves the scene graph inference problem using standard RNNs and learns to iteratively improves its predictions via message passing. Our joint inference model can take advantage of contextual cues to make better predictions on objects and their relationships. The experiments show that our model significantly outperforms previous methods for generating scene graphs using Visual Genome dataset and inferring support relations with NYU Depth v2 dataset.Comment: CVPR 201

DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs

A major difficulty of solving continuous POMDPs is to infer the multi-modal distribution of the unobserved true states and to make the planning algorithm dependent on the perceived uncertainty. We cast POMDP filtering and planning problems as two closely related Sequential Monte Carlo (SMC) processes, one over the real states and the other over the future optimal trajectories, and combine the merits of these two parts in a new model named the DualSMC network. In particular, we first introduce an adversarial particle filter that leverages the adversarial relationship between its internal components. Based on the filtering results, we then propose a planning algorithm that extends the previous SMC planning approach [Piche et al., 2018] to continuous POMDPs with an uncertainty-dependent policy. Crucially, not only can DualSMC handle complex observations such as image input but also it remains highly interpretable. It is shown to be effective in three continuous POMDP domains: the floor positioning domain, the 3D light-dark navigation domain, and a modified Reacher domain.Comment: IJCAI 202

Fractional exclusion and braid statistics in one dimension: a study via dimensional reduction of Chern-Simons theory

The relation between braid and exclusion statistics is examined in one-dimensional systems, within the framework of Chern-Simons statistical transmutation in gauge invariant form with an appropriate dimensional reduction. If the matter action is anomalous, as for chiral fermions, a relation between braid and exclusion statistics can be established explicitly for both mutual and nonmutual cases. However, if it is not anomalous, the exclusion statistics of emergent low energy excitations is not necessarily connected to the braid statistics of the physical charged fields of the system. Finally, we also discuss the bosonization of one-dimensional anyonic systems through T-duality.Comment: 19 pages, fix typo

Lower Bound of Concurrence Based on Positive Maps

We study the concurrence of arbitrary dimensional bipartite quantum systems. An explicit analytical lower bound of concurrence is obtained, which detects entanglement for some quantum states better than some well-known separability criteria, and improves the lower bounds such as from the PPT, realignment criteria and the Breuer's entanglement witness.Comment: 8 pages, 1 figur

Semileptonic BB Meson Decays Into A Highly Excited Charmed Meson Doublet

We study the heavy quark effective theory prediction for semileptonic $B$ decays into an orbital excited $F$-wave charmed doublet, the ($2^{+}$, $3^{+}$) states ($D^{*'}_{2}$, $D_{3}$), at the leading order of heavy quark expansion. The corresponding universal form factor is estimated by using the QCD sum rule method. The decay rates we predict are $\Gamma_{B\to D^{*'}_{2}\ell\overline{\nu}}=1.85\times10^{-19} {GeV}$ and $\Gamma_{B\to D_{3}\ell\overline{\nu}}=1.78\times10^{-19} {GeV}$. The branching ratios are $\mathcal {B}(B\to D_{2}^{*'}\ell\overline{\nu})=4.6\times10^{-7}$ and $\mathcal {B}(B\to D_{3}\ell\overline{\nu})=4.4\times10^{-7}$, respectively.Comment: 6 pages,2 figure

Search for Zs1+Z^{+}_{s1} and Zs2+Z^{+}_{s2} strangeonium-like structures

Theoretically, it has been presumed from an effective Lagrangian calculation that there could exist two charged strangeonium-like molecular states $Z^{+}_{s1}$ and $Z^{+}_{s2}$, with $K\bar{K}^{*}$ and $K^{*}\bar{K}^{*}$ configurations respectively. In the framework of QCD sum rules, we predict that masses of $Z^{+}_{s1}$ ($K\bar{K}^{*}$) and $Z^{+}_{s2}$ ($K^{*}\bar{K}^{*}$) are $1.85\pm0.14 GeV$ and $2.02\pm0.15 GeV$ respectively, which are both above their respective two meson thresholds. We suggest to put in practice the search for these two charged strangeonium-like structures in future experiments.Comment: 7 pages, 4 eps figures; the version accepted for publication in PRD. arXiv admin note: text overlap with arXiv:1203.070