2023
EMNLP
EMNLP 2023
Interpreting Answers to Yes-No Questions in User-Generated Content
Abstract
AbstractInterpreting answers to yes-no questions in social media is difficult. Yes and no keywords are uncommon, and the few answers that include them are rarely to be interpreted what the keywords suggest. In this paper, we present a new corpus of 4,442 yes-no question-answer pairs from Twitter. We discuss linguistic characteristics of answers whose interpretation is yes or no, as well as answers whose interpretation is unknown. We show that large language models are far from solving this problem, even after fine-tuning and blending other corpora for the same problem but outside social media.
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Interdisciplinary Bridge
— Deep Learning and Interdisciplinary and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Natural Language Processing > Applications > Question Answering
Natural Language Processing > Applications > Text Classification
Interdisciplinary > Social > Social Media Analysis
Natural Language Processing > Applications > Natural Language Inference
Deep Learning > Models > Large Language Models
Machine Learning > Learning Types > Fine-Tuning