Concept-1K

Citation Author(s):
Junhao
Zheng
Submitted by:
Junhao Zheng
Last updated:
Thu, 10/10/2024 - 11:46
DOI:
10.21227/xjhs-7121
License:
Creative Commons Attribution
16 Views
Categories:
Machine Learning
Keywords:
Continual Learning
0
0 ratings - Please login to submit your rating.
ACCESS DATASET CITE SHARE/EMBED

Abstract 

Concept-1K is a novel dataset designed to facilitate research on incremental learning in large language models. It comprises 1,023 concepts represented as knowledge triplets, focusing on recently emerged topics to minimize data leakage. By providing a fine-grained approach to evaluating model performance, Concept-1K enhances the understanding of how these models learn and retain new information.

Instructions: 

Concept-1K is a novel dataset designed to facilitate research on incremental learning in large language models. It comprises 1,023 concepts represented as knowledge triplets, focusing on recently emerged topics to minimize data leakage. By providing a fine-grained approach to evaluating model performance, Concept-1K enhances the understanding of how these models learn and retain new information.

Dataset Files

LOGIN TO ACCESS DATASET FILES

 

QUESTIONS?