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Jan 9, 2024 · In recent years, the fusion of textual and visual data has garnered significant attention in the realm of deep learning, offering unprecedented opportunities to enhance question generation systems.
- Standalone Question Generation
- Visual Question Generation
- Conversational Question Generation
- Summary of Approaches For AQG
In this type of question generation, the questions are generated independently of each other. This is typically the idea about machine reading comprehension systems where the only goal is to produce semantically and syntactically correct questions based on a paragraph of text or certain rules for language modeling. However, there is no correlation ...
Such systems are useful as an alternative to the solution of image captioning. In image captioning, the goal is to generate an account of the objects seen in an image. On the other hand, visual question generation (VQG) tries to accomplish the same goal by generating questions based on the objects in the image.
The primary objective of a conversational question generation model lies in generating questions that are rich in the context of the conversation. The main idea is to generate a series of questions for maintaining the conversation. In these systems, care must be taken that the conversation does not get stuck in a loop or gets too boring. The primar...
We summarize the use-case-based question generation classification in terms of the preprocessing techniques and the methodologies in Fig. 4. In Table 5, we list the different models used for each use-case of question generation. We also list the strengths and weaknesses of each model and identify the research gaps in them.
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience, and resources. This, in turn, hinders and slows down the use of educational activities (e.g. providing practice questions) and new advances (e.g. adaptive testing) that require a large pool of questions. To reduce ...
- Ghader Kurdi, Jared Leo, Bijan Parsia, Uli Sattler, Salam Al-Emari
- 2020
Automatic question generation finds application in dialog systems or virtual assistants where asking questions is an important part of interactions between humans and machines. In this paper, we propose a state-of-the-art solution using a pipeline that utilizes natural language processing and image captioning techniques capable of generating questions not only for textual but also for visual ...
Oct 31, 2023 · Questioning plays a vital role in education, directing knowledge construction and assessing students’ understanding. However, creating high-level questions requires significant creativity and effort. Automatic question generation is expected to facilitate the generation of not only fluent and relevant but also educationally valuable questions. While rule-based methods are intuitive for short ...
Oct 12, 2024 · In recent years, large language models (LLMs) and generative AI have revolutionized natural language processing (NLP), offering unprecedented capabilities in education. This chapter explores the transformative potential of LLMs in automated question generation and answer assessment. It begins by examining the mechanisms behind LLMs, emphasizing their ability to comprehend and generate human ...
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Can deep learning improve question generation systems?
Should deep learning be focused solely on visual question generation?
Can deep reinforcement learning be used for automatic question generation?
Are deep learning models better than rule-based approaches?
Why do we need question generation?
Why do we use natural language generation & processing techniques?
learning, offering unprecedented opportunities to enhance question generation systems. This paper delves into the exploration of methodologies leveraging deep learning techniques to generate ...
