The Visual Question Answering (VQA) task utilizes both visual image and language analysis to answer a textual question with respect an image. It has been popular research topic increasing number of real-world applications in the last decade. This paper introduces novel hierarchical integration vision AliceMind-MMU (ALIbaba’s Collection Encoder-decoders from Machine IntelligeNce lab Damo academy...

Abstract Automatic text processing is now a mature discipline in computer science, and so attempts at advancements using quantum computation have emerged as the new frontier, often under term of natural language processing. The main challenges consist finding most adequate ways encoding words their interactions on computer, considering hardware constraints, well building algorithms that take ad...

In this project, we exploit several deep learning architectures in Question Answering field, based on the newly released Stanford Question Answering dataset (SQuAD)[7]. We introduce a multi-stage process that encodes context paragraphs at different levels of granularity, uses co-attention mechanism to fuse representations of questions and context paragraphs, and finally decodes the co-attention...

The goal of a Question Answering (QA) system is to provide inexperienced users with a flexible access to the information allowing them for writing a query in natural language and obtaining a concise answer. QA systems are mainly suited to English as the target language. In this paper we will investigate how much the translation of the queries, from the Arabic into the English language, could re...

The need for making the Semantic Web better accessible for lay users and the uptake of interactive systems and smart assistants for the Web have spawned a new generation of RDF-based question answering systems. However, comparing the quality of these systems, repeating the published experiments or running on the same datasets remains a complex and time-consuming task. Thus, we extended the GERB...

The increasing amount of information available online has led to the development of technologies that help to deal with it. One of them is interactive question answering (IQA), a research field that has emerged at the intersection of question answering and dialogue systems, and which allows users to find the answers to questions in an interactive way. During the answering process, the automatic...

In this paper, we investigate how an accurate question classifier contributes to a question answering system. We first present a Maximum Entropy (ME) based question classifier which makes use of head word features and their WordNet hypernyms. We show that our question classifier can achieve the state of the art performance in the standard UIUC question dataset. We then investigate quantitativel...