The long-range interactions between branes in diverse dimensions

We calculate the long-range interactions between two simple branes placed parallel at a separation in diverse dimensions via an effective field theory approach. We also compute for the first time the explicit long-range interaction between two D-branes with each carrying a world-volume non-abelian magnetic flux in three special cases, respectively. In particular, we demonstrate that the half-string creation between a D$_0$-brane and a D$_8$-brane continues to hold even in the present context, therefore lending further support to the previous assertion of this. Our computations re-raise also the issue in one case on whether so constructed (D$_0$, D$_8$) bound state is actually a marginal one.Comment: 28 pages, various discussions expanded and references adde

Video Question Answering via Attribute-Augmented Attention Network Learning

Video Question Answering is a challenging problem in visual information retrieval, which provides the answer to the referenced video content according to the question. However, the existing visual question answering approaches mainly tackle the problem of static image question, which may be ineffectively for video question answering due to the insufficiency of modeling the temporal dynamics of video contents. In this paper, we study the problem of video question answering by modeling its temporal dynamics with frame-level attention mechanism. We propose the attribute-augmented attention network learning framework that enables the joint frame-level attribute detection and unified video representation learning for video question answering. We then incorporate the multi-step reasoning process for our proposed attention network to further improve the performance. We construct a large-scale video question answering dataset. We conduct the experiments on both multiple-choice and open-ended video question answering tasks to show the effectiveness of the proposed method.Comment: Accepted for SIGIR 201