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Found 13 papers, 5 papers with code
How Teachers Can Use Large Language Models and Bloom's Taxonomy to Create Educational Quizzes
Question generation (QG) is a natural language processing task with an abundance of potential benefits and use cases in the educational domain.
Evaluating Dependencies in Fact Editing for Language Models: Specificity and Implication Awareness
The potential of using a large language model (LLM) as a knowledge base (KB) has sparked significant interest.
Ensemble Distillation for Unsupervised Constituency Parsing
We investigate the unsupervised constituency parsing task, which organizes words and phrases of a sentence into a hierarchical structure without using linguistically annotated data.
How Useful are Educational Questions Generated by Large Language Models?
Controllable text generation (CTG) by large language models has a huge potential to transform education for teachers and students alike.
The Stable Entropy Hypothesis and Entropy-Aware Decoding: An Analysis and Algorithm for Robust Natural Language Generation
State-of-the-art language generation models can degenerate when applied to open-ended generation problems such as text completion, story generation, or dialog modeling.
Question Personalization in an Intelligent Tutoring System
This paper investigates personalization in the field of intelligent tutoring systems (ITS).
Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment
We train a neural model with this feedback data that can generate explanations and re-score answer candidates.
Ranked #1 on
Overall - Test
on FeedbackQA
Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems
We test our method in a dialogue-based ITS and demonstrate that our approach results in high-quality feedback and significantly improved student learning gains.
Discourse-Aware Unsupervised Summarization of Long Scientific Documents
We propose an unsupervised graph-based ranking model for extractive summarization of long scientific documents.
Ranked #1 on
Unsupervised Extractive Summarization
on Pubmed
Learning Lexical Subspaces in a Distributional Vector Space
In this paper, we propose LexSub, a novel approach towards unifying lexical and distributional semantics.
What comes next? Extractive summarization by next-sentence prediction
Existing approaches to automatic summarization assume that a length limit for the summary is given, and view content selection as an optimization problem to maximize informativeness and minimize redundancy within this budget.
Detecting Large Concept Extensions for Conceptual Analysis
When performing a conceptual analysis of a concept, philosophers are interested in all forms of expression of a concept in a text---be it direct or indirect, explicit or implicit.
