Today, computer vision systems are tested by their accuracy in detecting and localizing instances of objects. As an alternative, and motivated by the ability of humans to provide far richer descriptions, even tell a story about an image, we construct a ”visual Turing test”: an operator-assisted device that produces a stochastic sequence of binary questions from a given test image. The query eng...

This paper describes our complex cross-lingual question answering (CCLQA) system for NTCIR-7 ACLIA track. To answer complex questions such as events, biographies, definitions, and relations, we designed two models, i.e., the centroid-vector model and the SVMbased model. In the official evaluation of the NTCIR7 CCLQA track, our SVM-based model achieved 22.11% F-score in the English-Chinese cross...