Abstract With the swift growth of information over past few years, taking full benefit is increasingly essential. Question Answering System one promising methods to access this much information. The lacks humans’ common sense and reasoning power cannot identify unanswerable questions irrelevant questions. These are answered by making unreliable incorrect guesses. In paper, we address limitation...

Question Answering (QA) is an emerging important field in Information Retrieval. In a QA system the archive of previous questions asked from the system makes a collection full of useful factual nuggets. This paper makes an initial attempt to investigate the reuse of facts contained in the archive of previous questions to help and gain performance in answering future related factoid questions. I...

Counterfactuals have been shown to be a powerful method in Visual Question Answering the alleviation of Answering’s unimodal bias. However, existing counterfactual methods tend generate samples that are not diverse or require auxiliary models synthesize additional data. In this regard, we propose more and simple sample synthesis called Counterfactual Mix-Up (CoMiU), which generates image featur...

Knowledge base question answering (KBQA) aims to answer a over knowledge (KB). Early studies mainly focused on simple questions KBs and achieved great success. However, their performances complex are still far from satisfactory. Therefore, in recent years, researchers propose large number of novel methods, which looked into the challenges questions. In this survey, we review advances KBQA with ...

The ability of a computer system to be able understand surroundings and elements think like human being process the information has always been major point focus in field Computer Science. One ways achieve this artificial intelligence is Visual Question Answering. Answering (VQA) trained which can answer questions associated given image Natural Language. VQA generalized used any image-based sce...