PZ

9 records found

Authored

Actively engaging learners with learning materials has been shown to be very important in the Search as Learning (SAL) setting. One active reading strategy relies on asking so-called adjunct questions, i.e., manually curated questions geared towards essential concepts of the t ...

Cross-modal retrieval, as an important emerging foundational information retrieval task, benefits from recent advances in multimodal technologies. However, current cross-modal retrieval methods mainly focus on the interaction between textual information and 2D images, lacking ...

MRHF

Multi-stage Retrieval and Hierarchical Fusion for Textbook Question Answering

Textbook question answering is challenging as it aims to automatically answer various questions on textbook lessons with long text and complex diagrams, requiring reasoning across modalities. In this work, we propose MRHF, a novel framework that incorporates dense passage re-r ...

Questions are critical for information-seeking and learning. Automatic Question Generation (AQG) involves the subjects of Information Retrieval (IR) and Natural Language Processing (NLP), and focuses on automatically creating questions for various applications, subjects which hav ...

In this work, we address the information overload issue that learners in Massive Open Online Courses (MOOCs) face when attempting to close their knowledge gaps via the use of MOOC discussion forums. To this end, we investigate the recommendation of one-minute-resolution video ...

Question generation (QG) approaches based on large neural models require (i) large-scale and (ii) high-quality training data. These two requirements pose difficulties for specific application domains where training data is expensive and difficult to obtain. The trained QG mode ...

Quality control is essential for creating extractive question answering (EQA) datasets via crowdsourcing. Aggregation across answers, i.e. word spans within passages annotated, by different crowd workers is one major focus for ensuring its quality. However, crowd workers cannot r ...

Generating questions that can be answered with word spans from passages is an important natural language task, which can be used for educational applications, question-answering systems, and conversational systems. Existing question generation models suffer from creating quest ...

Question generation systems aim to generate natural language questions that are relevant to a given piece of text, and can usually be answered by just considering this text. Prior works have identified a range of shortcomings (including semantic drift and exposure bias) and th ...