20 papers · ranked by Valyu relevance
Azam Rabiee, Alok Goel, Johnson D'Souza, Saurabh Khanwalkar
Online learning platforms provide learning materials and answers to students' academic questions by experts, peers, or systems. This paper explores question-type identification as a step in content understanding for an online learning platform. The aim of the question-type identifier is to categorize question types…
Wenjie Zhou, Minghua Zhang, Yunfang Wu
Question generation is a challenging task which aims to ask a question based on an answer and relevant context. The existing works suffer from the mismatching between question type and answer, i.e. generating a question with type how while the answer is a personal name. We propose to automatically predict the question…
Akira R. Kinjo, Yasunori Yamamoto, Samuel Bustamante-Larriet, Jose-Emilio Labra-Gayo + 1 more
Querying the RDF Portal knowledge graph maintained by DBCLS—which aggregates approximately 60 life-science databases—requires proficiency in both SPARQL and database-specific RDF schemas, placing this resource beyond the reach of most researchers. Large Language Models (LLMs) can, in principle, translate…
Shuyang Cao, Lu Wang
We investigate the less-explored task of generating open-ended questions that are typically answered by multiple sentences. We first define a new question type ontology which differentiates the nuanced nature of questions better than widely used question words. A new dataset with 4, 959 questions is labeled based on…
Xiaohui Dong, Xinyu Zhang, Zhengluo Li, Quanxin Hou + 3 more
As a key natural language processing (NLP) task, question generation (QG) is crucial for boosting educational quality and fostering personalized learning. This article offers an in-depth review of the research advancements and future directions in QG in education (QGEd). We start by tracing the evolution of QG and…
Lishan Zhang, Kurt VanLehn
Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply biology instructors with questions for…
Laurie Burchell, Jie Chi, Tom Hosking, Nina Markl + 1 more
Multi-sentence questions (MSQs) are sequences of questions connected by relations which, unlike sequences of standalone questions, need to be answered as a unit. Following Rhetorical Structure Theory (RST), we recognise that different "question discourse relations" between the subparts of MSQs reflect different speaker…
Sarthak Dash, Nandana Mihindukulasooriya, Alfio Gliozzo, Mustafa Canim
'Mustafa Canim'] Inferring semantic types for entity mentions within text documents is an important asset for many downstream NLP tasks, such as Semantic Role Labelling, Entity Disambiguation, Knowledge Base Question Answering, etc. Prior works have mostly focused on supervised solutions that generally operate on…
Justine Zhang, Arthur Spirling, Cristian Danescu-Niculescu-Mizil
Questions play a prominent role in social interactions, performing rhetorical functions that go beyond that of simple informational exchange. The surface form of a question can signal the intention and background of the person asking it, as well as the nature of their relation with the interlocutor. While the…
Jovana Dobreva, Ivana Karasmanakis, Filip Ivanisevic, Tadej Horvat + 4 more
The paper introduces RAGCare-QA, an extensive dataset of 420 theoretical medical knowledge questions for assessing Retrieval-Augmented Generation (RAG) pipelines in medical education and evaluation settings. The dataset includes one-choice-only questions from six medical specialties (Cardiology, Endocrinology…
Alice Huang, Dale Hancock, Matthew Clemson, Giselle Yeo + 3 more
Production of high-quality multiple-choice questions (MCQs) for both formative and summative assessment is a time-consuming task requiring great skill, creativity, and insight. The transition to online examinations, with the concomitant exposure of previously tried-and-tested MCQs, exacerbates the challenges of…
Yuda Munarko, Dewan M. Sarwar, Anand Rampadarath, Koray Atalag + 3 more
Semantic annotation is a crucial step to assure reusability and reproducibility of biosimulation models in biology and physiology. For this purpose, the COmputational Modeling in BIology NEtwork (COMBINE) community recommends the use of the Resource Description Framework (RDF). This grounding in RDF provides the…
Alexander Muacevic, John R Adler, Sofia Lopiano, Evan S Cohen + 2 more
Purpose Current research has shown that Generative AI language models (e.g., ChatGPT) can answer and provide explanations for practice questions and generate new questions. Further investigation is needed to assess how ChatGPT-generated questions compare with National Board of Medical Examiners (NBME)-style questions…
Nguyen-Thinh Le, Niels Pinkwart
Discourse and argumentation are effective techniques for education not only in social domains but also in science domains. However, it is difficult for some teachers to stimulate an active discussion between students because several students might not be able to develop their arguments. This paper proposes to use…
Yichun Feng, Lu Zhou, Yikai Zheng, Ruikun He + 2 more
In recent years, Large Language Models (LLMs) have shown promise in various domains, notably in biomedical sciences. However, their real-world application is often limited by issues like erroneous outputs and hallucinatory responses. We developed the Knowledge Graph-based Thought (KGT) framework, an innovative solution…
George Adrian Muntean, Anca Marginean, Adrian Groza, Ioana Damian + 7 more
'Sara Alexia Roman' 'Mădălina Claudia Hapca' 'Anca Mădălina Sere' 'Roxana Mihaela Mănoiu' 'Maximilian Vlad Muntean' 'Simona Delia Nicoară' 'Jae-Ho Han'] Patient compliance in chronic illnesses is essential for disease management. This also applies to age-related macular degeneration (AMD), a chronic acquired retinal…
Dezheng Han, Yibin Jia, Ruxiao Chen, Wenjie Han + 2 more
To enable precise and fully automated cell type annotation with large language models (LLMs), we developed a graph-structured feature–marker database to retrieve entities linked to differential genes for cell reconstruction. We further designed a multi-task workflow to optimize the annotation process. Compared to…
Szu Szu Ling, Fabrice Saffre, Deborah L. Gater, Lilia Halim + 1 more
Computer quiz games are introduced to improve teaching and learning in a freshman engineering chemistry course in an English-as-a-Second-Language (ESL) environment. These quiz games are developed and implemented as a supplemental and augmentative tool to enhance traditionally delivered lectures. The paper shows an…
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The Socratic method, grounded in iterative questioning and critical dialogue, offers a compelling framework for leveraging large language models (LLMs) to advance scientific reasoning and discovery in chemistry and materials science. In this paper, we explore how Socratic principles can be integrated into prompt…
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Artificial intelligence, represented by large language models (LLMs), has demonstrated tremendous capabilities in natural language recognition and extraction. To further evaluate the performance of various LLMs in extracting information from academic papers, this study explores the application of LLMs in reticular…