Video Captioning via Hierarchical Reinforcement Learning

Video captioning is the task of automatically generating a textual description of the actions in a video. Although previous work (e.g. sequence-to-sequence model) has shown promising results in abstracting a coarse description of a short video, it is still very challenging to caption a video containing multiple fine-grained actions with a detailed description. This paper aims to address the challenge by proposing a novel hierarchical reinforcement learning framework for video captioning, where a high-level Manager module learns to design sub-goals and a low-level Worker module recognizes the primitive actions to fulfill the sub-goal. With this compositional framework to reinforce video captioning at different levels, our approach significantly outperforms all the baseline methods on a newly introduced large-scale dataset for fine-grained video captioning. Furthermore, our non-ensemble model has already achieved the state-of-the-art results on the widely-used MSR-VTT dataset.Comment: CVPR 2018, with supplementary materia

Rapidity bin multiplicity correlations from a multi-phase transport model

The central-arbitrary bin and forward-backward bin multiplicity correlation patterns for Au+Au collisions at $\sqrt{s_{NN}}$= $7.7-62.4$ GeV are investigated within a multi-phase transport (AMPT) model. An interesting observation is that for $\sqrt{s_{NN}} <19.6$ GeV Au+Au collisions, these two correlation patterns both have an increase with the pseudorapidity gap, while for $\sqrt{s_{NN}} >19.6$ GeV Au+Au collisions, they decrease. We mainly discuss the influence of different evolution stages of collision system on the central-arbitrary bin correlations, such as the initial conditions, partonic scatterings, hadronization scheme and hadronic scatterings. Our results show that the central-arbitrary bin multiplicity correlations have different responses to partonic phase and hadronic phase, which can be suggested as a good probe to explore the dynamical evolution mechanism of the hot dense matter in high-energy heavy-ion collisions.Comment: 7pages, 6 figures, accepted for publication in EPJ