Hate speech detection is an important research area owing to the severe effects of hate speech on the society. Hence automated hate speech detection based on textual data assumed a pivotal role among the research groups. ...

Conversational question answering systems areaway ofhuman-computer interaction which integrates the automation into everyday life. Chatbots gained popularity because of their ease and simplicity, which helps the user to ...

Visual question answering (VQA) is one of the most exciting problems of computer vision and natural language processing tasks. It requires understanding and reasoning of the image to answer a human query. Text Visual ...

Real-time information is transforming due to technological advancements and widespread internet access. In our increasingly digital culture, fake news and misinformation are more common in journalism, news reporting, social ...

The evaluation of answer scripts is vital for assessing a student’s performance. The manual evaluation of the answers can sometimes be biased. The assessment depends on various factors, including the evaluator’s mental ...

People are now consuming news on social media platforms rather than through traditional sources as a result of easy access to the internet. This has allowed for the recent rise in the online dissemination of false information. ...

This paper describes the proposed system for the machine translation of Indic language pairs Odia - Hindi and Hindi - Odia for the General Translation and Domain Specific Translation tasks proposed by Forum of Information ...

A legal document is usually long and dense requiring human effort to parse it. It also contains significant amounts of jargon which make deriving insights from it using existing models a poor approach. This paper presents ...

The use of internet advertising as a primary customer acquisition strategy is becoming increasingly common among businesses. Internet companies like Google, Facebook, and Amazon have become platforms for these online ...

A legal document is usually long and dense requiring human effort to parse it. It also contains significant amounts of jargon which make deriving insights from it using existing models a poor approach. This paper ...