Papers
1–3 of 3Research Paper·Jan 21, 2026
InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement
Most existing time series classification methods adopt a discriminative paradigm that maps input sequences directly to one-hot encoded class labels. While effective, this paradigm struggles to incorpo...
7.0 viability
Research Paper·Mar 2, 2026
UTICA: Multi-Objective Self-Distllation Foundation Model Pretraining for Time Series Classification
Self-supervised foundation models have achieved remarkable success across domains, including time series. However, the potential of non-contrastive methods, a paradigm that has driven significant adva...
4.0 viability
Research Paper·Feb 19, 2026
MantisV2: Closing the Zero-Shot Gap in Time Series Classification with Synthetic Data and Test-Time Strategies
Developing foundation models for time series classification is of high practical relevance, as such models can serve as universal feature extractors for diverse downstream tasks. Although early models...
4.0 viability