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This research explores a novel modality for generating questions from images, focusing on user interaction and evaluation. Users engage solely with visuals, answering questions linked to specific regions within the images. The system facilitates the collection of answers to generated questions and allows users to evaluate one another's responses. The goal is to create an effective strategy for questioning that motivates children while assessing the quality of question-answer pairs. The study aims to refine the question generation process by developing a user model and evaluating user intent in real time.
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Task 2: Extrinsic Evaluation VasileRus, Wei Chen, Pascal Kuyten, Ron Artstein, ElnazNouri
New modality • Generate questions from pictures • Provide text/metadata description as a seed for QG systems (to be dispensed with in the future) • Users/evaluators only see the picture • Answer = region in image; users interact graphically
Users evaluate each other • Users provide answers to generated questions • Users evaluate answers from other users • http://anawiki.essex.ac.uk/phrasedetectives/
Evaluate Q-A pairs • Motivate children to answer questions • Correct answer = plant seed in virtual garden • http://pbskids.org/arthur/games/groovygarden/groovygarden.html • Systems provide questions and answers • Perhaps questions, answers and distractors? • Rate of correct responses = quality of q-a pair
Guess who • User chooses a picture element • System asks yes/no questions • User can answer yes, no, don’t understand • Evaluates question answerability • Goal: best strategy to get to user’s choice • Metric: number of steps • Question formulation might be trivial • Hard part is deciding what to ask • Build model of user inentions • Create taxonomy on the fly? In a short time?
What systems should win • QG has two essential components • What to ask • How to ask it • (Optional: answer your question) • Either what or how should be non-trivial • Winner = the most templates: is that good?