Cover Image

Leveraging Large Language Models to Generate Course-specific Semantically Annotated Learning Objects

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lohr, Dominic, Berges, Marc, Chugh, Abhishek, Kohlhase, Michael, Müller, Dennis
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging Large Language Models to Generate Course‐Specific Semantically Annotated Learning Objects
by: Dominic Lohr, et al.
Published: (2024)

The Potential of Answer Classes in Large-scale Written Computer-Science Exams -- Vol. 2
by: Lohr, Dominic, et al.
Published: (2024)

You're (Not) My Type -- Can LLMs Generate Feedback of Specific Types for Introductory Programming Tasks?
by: Lohr, Dominic, et al.
Published: (2024)

RECAP: A Resource-Efficient Method for Adversarial Prompting in Large Language Models
by: Chugh, Rishit
Published: (2026)

Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning Approach with Large Language Models
by: Yadav, Sargam, et al.
Published: (2024)

The Hidden Bias: A Study on Explicit and Implicit Political Stereotypes in Large Language Models
by: Löhr, Konrad, et al.
Published: (2025)

Toward Semantic Interoperability of Electronic Health Records
by: Berges, Idoia, et al.
Published: (2024)

Large Language Models Preserve Semantic Isotopies in Story Continuations
by: Cavazza, Marc
Published: (2025)

LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource Languages
by: Kholodna, Nataliia, et al.
Published: (2024)

Using Large Language Models and Knowledge Graphs to Improve the Interpretability of Machine Learning Models in Manufacturing
by: Bayer, Thomas, et al.
Published: (2026)

Understanding Physical Properties of Unseen Deformable Objects by Leveraging Large Language Models and Robot Actions
by: Park, Changmin, et al.
Published: (2025)

A Semantic Approach for Big Data Exploration in Industry 4.0
by: Berges, Idoia, et al.
Published: (2024)

Leveraging Large Language Models (LLMs) to Support Collaborative Human-AI Online Risk Data Annotation
by: Park, Jinkyung, et al.
Published: (2024)

The Forecast Critic: Leveraging Large Language Models for Poor Forecast Identification
by: Bhan, Luke, et al.
Published: (2025)

CoLa: Learning to Interactively Collaborate with Large Language Models
by: Sharma, Abhishek, et al.
Published: (2025)

Leveraging Large Language Models for Enhancing the Understandability of Generated Unit Tests
by: Deljouyi, Amirhossein, et al.
Published: (2024)

Large Language Models Are Effective Human Annotation Assistants, But Not Good Independent Annotators
by: Gu, Feng, et al.
Published: (2025)

Getting In Contract with Large Language Models -- An Agency Theory Perspective On Large Language Model Alignment
by: Kaltenpoth, Sascha, et al.
Published: (2025)

Token-Efficient Leverage Learning in Large Language Models
by: Zeng, Yuanhao, et al.
Published: (2024)

CAUS: A Dataset for Question Generation based on Human Cognition Leveraging Large Language Models
by: Shin, Minjung, et al.
Published: (2024)

How Good Are Large Language Models for Course Recommendation in MOOCs?
by: Ma, Boxuan, et al.
Published: (2025)

On the Semantics of Large Language Models
by: Schuele, Martin
Published: (2025)

ANAH: Analytical Annotation of Hallucinations in Large Language Models
by: Ji, Ziwei, et al.
Published: (2024)

LLMTrack: Semantic Multi-Object Tracking with Multi-modal Large Language Models
by: Liao, Pan, et al.
Published: (2026)

Leveraging Large Language Models for Enhanced Process Model Comprehension
by: Kourani, Humam, et al.
Published: (2024)

Leveraging Large Language Models for Entity Matching
by: Huang, Qianyu, et al.
Published: (2024)

Bridging Traditional Machine Learning and Large Language Models: A Two-Part Course Design for Modern AI Education
by: Li, Fang
Published: (2025)

Improving User Behavior Prediction: Leveraging Annotator Metadata in Supervised Machine Learning Models
by: Ng, Lynnette Hui Xian, et al.
Published: (2025)

Grading Massive Open Online Courses Using Large Language Models
by: Golchin, Shahriar, et al.
Published: (2024)

Leveraging Large Language Models for Fuzzy String Matching in Political Science
by: Wang, Yu
Published: (2024)

Leveraging Large Language Models to Develop Heuristics for Emerging Optimization Problems
by: Bömer, Thomas, et al.
Published: (2025)

Improving Tool Retrieval by Leveraging Large Language Models for Query Generation
by: Kachuee, Mohammad, et al.
Published: (2024)

Entity Alignment with Noisy Annotations from Large Language Models
by: Chen, Shengyuan, et al.
Published: (2024)

Leveraging Large Language Model-based Room-Object Relationships Knowledge for Enhancing Multimodal-Input Object Goal Navigation
by: Sun, Leyuan, et al.
Published: (2024)

Semantic-aware Graph-guided Behavior Sequences Generation with Large Language Models for Smart Homes
by: Xu, Zhiyao, et al.
Published: (2025)

Leveraging Large Language Models for Enhancing Autonomous Vehicle Perception
by: Karagounis, Athanasios
Published: (2024)

RadAnnotate: Large Language Models for Efficient and Reliable Radiology Report Annotation
by: Shetty, Saisha Pradeep, et al.
Published: (2026)

Learning Semantic Traversability with Egocentric Video and Automated Annotation Strategy
by: Kim, Yunho, et al.
Published: (2024)

Semantic Alignment of Multilingual Knowledge Graphs via Contextualized Vector Projections
by: Kumar, Abhishek
Published: (2025)

Automated Multi-Label Annotation for Mental Health Illnesses Using Large Language Models
by: Hassan, Abdelrahaman A., et al.
Published: (2024)