Papers by Lidiya Murakhovs’ka
MixQG: Neural Question Generation with Mixed Answer Types (2022.findings-naacl)
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| Challenge: | Existing neural question generation approaches focus on short factoid type of answers. |
| Approach: | They propose a neural question generator that trains a single generative model by combining multiple question types with different answer types. |
| Outcome: | The proposed model outperforms existing models in both seen and unseen domains and can generate questions with different cognitive levels when conditioned on different answer types. |
Quiz Design Task: Helping Teachers Create Quizzes with Automated Question Generation (2022.findings-naacl)
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| Challenge: | Question generation models are often evaluated with standardized NLG metrics that are based on n-gram overlap. |
| Approach: | They propose to use QGen to help teachers automate the generation of reading comprehension quizzes by comparing n-gram overlap with BLEU to compare system-generated questions with heldout human-written references. |
| Outcome: | The best model had only 68.4% of its questions accepted by the ten teachers who participated in the study. |
INTELMO: Enhancing Models’ Adoption of Interactive Interfaces (2023.emnlp-demo)
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| Challenge: | INTELMO is an easy-to-use library to help model developers adopt user-faced interactive interfaces for their language models. |
| Approach: | They propose a library to help model developers adopt user-faced interactive interfaces and articles from real-time RSS sources for their language models. |
| Outcome: | The proposed library categorizes common NLP tasks and provides default style patterns . it provides developers with fine-grained and flexible control over user interfaces . |
Discord Questions: A Computational Approach To Diversity Analysis in News Coverage (2022.findings-emnlp)
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| Challenge: | Modern news aggregators do the hard work of organizing the news, but choosing which source to read remains challenging. |
| Approach: | They propose a framework to help readers identify source differences and gain an understanding of news coverage diversity by generating questions with a diverse answer pool and reusing existing methods. |
| Outcome: | The proposed framework improves performance from current question generation methods by 5% and achieves 81% balanced accuracy on a realistic test set. |
Salespeople vs SalesBot: Exploring the Role of Educational Value in Conversational Recommender Systems (2023.findings-emnlp)
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| Challenge: | Existing conversational recommender systems focus on a single-shot approach to understand user preferences and provide recommendations. |
| Approach: | They propose a problem space for conversational agents that aim to provide both product recommendations and educational value through mixed-type mixed-initiative dialog. |
| Outcome: | The proposed framework can simulate salesbot and shopperbot agents and provide both product recommendations and educational value through mixed-type mixed-initiative dialog. |