A Post-Processing Framework for Crowd Worker Responses Using Large Language Models
To develop quality crowdsourcing systems, aggregating responses from workers is a critical issue. However, it has been difficult to construct an automatic mechanism that flexibly aggregates worker responses in natural language. Accordingly, responses need to be collected in a standardized format, su...
Saved in:
| Main Authors: | Ryuya Itano, Tatsuki Tamano, Takahiro Koita, Honoka Tanitsu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
International Institute of Informatics and Cybernetics
2023-04-01
|
| Series: | Journal of Systemics, Cybernetics and Informatics |
| Subjects: | |
| Online Access: | http://www.iiisci.org/Journal/PDV/sci/pdfs/CK528SF23.pdf
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Comprehensive Analysis of a Social Intelligence Dataset and Response Tendencies Between Large Language Models (LLMs) and Humans
by: Erika Mori, et al.
Published: (2025-01-01) -
Building a Custom Crime Detection Dataset and Implementing a 3D Convolutional Neural Network for Video Analysis
by: Juan Camilo Londoño Lopera, et al.
Published: (2025-02-01) -
AI for Data Quality Auditing: Detecting Mislabeled Work Zone Crashes Using Large Language Models
by: Shadi Jaradat, et al.
Published: (2025-05-01) -
An IoT intrusion detection framework based on feature selection and large language models fine-tuning
by: Huan Ma, et al.
Published: (2025-07-01) -
A Panoramic Review on Cutting-Edge Methods for Video Anomaly Localization
by: Rashmiranjan Nayak, et al.
Published: (2024-01-01)