1 citations · 1 across the 3 of their papers we have counts for
5 papers
GIFT-Eval-CTX: A Benchmark For Contextual Forecasting Model Evaluation
Xu Liu, Hanshu Yan, Taha Aksu +6
Contextual forecasting seeks to improve time series forecasting by incorporating forward-looking information, such as planned events, external conditions, and expert expectations.…
It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
Zhongzheng Qiao, Sheng Pan, Anni Wang +7
Time series foundation models (TSFMs) are revolutionizing the forecasting landscape from specific dataset modeling to generalizable task evaluation. However, we contend that existi…
Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
Zhongzheng Qiao, Chenghao Liu, Yiming Zhang +6
Time series foundation models (TSFMs) demonstrate impressive zero-shot performance for time series forecasting. However, an important yet underexplored challenge is how to effectiv…
Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing
Zhongzheng Qiao, Xuan Huy Pham, Savitha Ramasamy +3
In autonomous and mobile robotics, a principal challenge is resilient real-time environmental perception, particularly in situations characterized by unknown and dynamic elements,…
Class-incremental Learning for Time Series: Benchmark and Evaluation
Zhongzheng Qiao, Quang Pham, Zhen Cao +4
Real-world environments are inherently non-stationary, frequently introducing new classes over time. This is especially common in time series classification, such as the emergence…