ChorusTIC: Training-Free Multivariate Time Series Classification via Chorus In-Context Learning
cs.LG, cs.AI, stat.ML
Submitted: 2026-08-25
Updated: 2026-09-30
Code: https://github.com/fangjuntao/ChorusTIC
Terminology
Sources
- Chronos-2: From Univariate to Universal Forecasting
- The UEA multivariate time series classification archive, 2018
- Toto: Time Series Optimized Transformer for Observability
- A decoder-only foundation model for time-series forecasting
- Rethinking Zero-Shot Time Series Classification: From Task-specific Classifiers to In-Context Inference
- Mantis: Lightweight Foundation Model for Time Series Classification
- MantisV2: Closing the Zero-Shot Gap in Time Series Classification with Synthetic Data and Test-Time Strategies
- Improving Position Encoding of Transformers for Multivariate Time Series Classification
- UniTS: A Unified Multi-Task Time Series Model
- MOMENT: A Family of Open Time-series Foundation Models
- NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining
- TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
- A Causal DAG Prior for Synthetic Time-Series Classification Datasets
- RocketPFN: Accurate Time Series Classification via In-Context Learning
- TabICLv2: A better, faster, scalable, and open tabular foundation model
- TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
- Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
- A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks
- Training-Free Time Series Classification via In-Context Reasoning with LLM Agents
- Unified Training of Universal Time Series Forecasting Transformers
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