KairosAgent fuses LLM semantic reasoning with TSFM numerical forecasting through dynamic tool use and RL-based multi-turn refinement to deliver superior zero-shot multimodal time series predictions.
Conversational time series foundation models: Towards explainable and effective forecasting
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
AME-TS is a structure-guided sparse MoE foundation model for time series that aligns expert routing with series-level temporal descriptors to achieve strong accuracy-efficiency tradeoffs on GIFT-Eval while improving specialization stability.
citing papers explorer
-
KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning
KairosAgent fuses LLM semantic reasoning with TSFM numerical forecasting through dynamic tool use and RL-based multi-turn refinement to deliver superior zero-shot multimodal time series predictions.