6 papers
Synthetic Series-Symbol Data Generation for Time Series Foundation Models
Wenxuan Wang, Kai Wu, Yujian Betterest Li +2
Foundation models for time series analysis (TSA) have attracted significant attention. However, challenges such as training data scarcity and imbalance continue to hinder their dev…
Fine Tuning Methods for Low-resource Languages
Tim Bakkenes, Daniel Wang, Anton Johansson
The rise of Large Language Models has not been inclusive of all cultures. The models are mostly trained on English texts and culture which makes them underperform in other language…
Driving Accurate Allergen Prediction with Protein Language Models and Generalization-Focused Evaluation
Brian Shing-Hei Wong, Joshua Mincheol Kim, Sin-Hang Fung +11
Allergens, typically proteins capable of triggering adverse immune responses, represent a significant public health challenge. To accurately identify allergen proteins, we introduc…
KG2QA: Knowledge Graph-enhanced Retrieval-augmented Generation for Communication Standards Question Answering
Zhongze Luo, Weixuan Wan, Tianya Zhang +2
The rapid evolution of communication technologies has led to an explosion of standards, rendering traditional expert-dependent consultation methods inefficient and slow. To address…
Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation
Wenxuan Wang, Kai Wu, Yujian Betterest Li +3
Foundation models for time series analysis (TSA) have attracted significant attention. However, challenges such as data scarcity and data imbalance continue to hinder their develop…
Comparing Fairness of Generative Mobility Models
Daniel Wang, Jack McFarland, Afra Mashhadi +1
This work examines the fairness of generative mobility models, addressing the often overlooked dimension of equity in model performance across geographic regions. Predictive models…