OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoning
cs.LG
Submitted: 2026-09-30
Updated: 2026-10-07
Code: https://github.com/OpenTSLM/OpenTSLM-TeeMoE
Sources
- Reasoning-Aware Training for Time Series Forecasting
- GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
- Chronos-2: From Univariate to Universal Forecasting
- Beyond Na\"ive Prompting: Strategies for Improved Context-aided Forecasting with LLMs
- TimeSeriesExam: A time series understanding exam
- Toto: Time Series Optimized Transformer for Observability
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
- A decoder-only foundation model for time-series forecasting
- UniTS: A Unified Multi-Task Time Series Model
- MOMENT: A Family of Open Time-series Foundation Models
- FlowState: Sampling-Rate-Equivariant Time-Series Forecasting
- The Llama 3 Herd of Models
- Large Language Models Are Zero-Shot Time Series Forecasters
- What if Tomorrow is the World Cup Final? Counterfactual Time Series Forecasting with Textual Conditions
- TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models
- TimeOmni-VL: Unified Models for Time Series Understanding and Generation
- Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
- Toto 2.0: Time Series Forecasting Enters the Scaling Era
- Harnessing Generalist Agents for Contextualized Time Series
- Moirai 2.0: When Less Is More for Time Series Forecasting
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