In-Context Learning
Evaluation complete
TIC-FM
A split-masked latent-memory framework for training-free time series in-context classification.
Method overview
A split-masked latent-memory framework for training-free time series in-context classification.
Evaluated configurations
Native in-context inference
Classifier heads are grouped on this page under their shared pretrained model. They remain separate leaderboard entries because they represent different experimental configurations.
- Organization
- GDUT · Huawei Noah’s Ark Lab · Université Paris Cité · MBZUAI
- Parameters
- Not reported by authors
- Checkpoint used
- TSEncoder_orion_icl_fullv1.0.pt
- Input Type
- Univariate time series
- Inference
- Training-free in-context classification
Reading this model's evaluation
The method catalog describes the pretrained model; leaderboard eligibility depends on the actual coverage of each experimental configuration. Catalog inclusion does not imply complete coverage of all 198 datasets.