TW3Cast: A Frozen Router of Lightly Fine-Tuned Foundation Models for Time-Series Forecasting on GIFT-Eval, Selected Entirely on the Training Split
How a frozen routing architecture climbed the GIFT-Eval leaderboard using specialized foundation model selection.
TW3Cast is a time-series forecasting system that reaches position 3 of 130 entries on the GIFT-Eval benchmark by mean MASE rank, as of 2026-09-14. The two entries above it belong to the leaderboard's agentic category, multi-step systems that use agents or language models to reaso...
ArXiv CS.AI
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TW3Cast demonstrates that highly efficient, frozen routing mechanisms can compete with complex agentic architectures in time-series forecasting. By leveraging strategic selection from fine-tuned foundation models, this approach proves that specialized hardware orchestration can outperform monolithic models.
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