TW3Cast: frozen router of lightly fine-tuned foundation models ranks #3 on GIFT‑Eval; artifacts released
TW3Cast is a time-series forecasting system that reached rank 3 of 130 on the GIFT‑Eval benchmark by mean MASE as of 2026‑09‑14. It uses no agents or language models: a routing table computed once on the training split (and then frozen) selects among four modes per dataset/configuration — specialists (LoRA or full fine-tunes of Chronos‑2, TiRex or Toto), quantile blends, blends of base models, or a selection tournament run on a backtest — with every decision taken on that training-split backtest. Three guard mechanisms (accuracy+calibration criterion, asymmetric margin for candidates that saw the series in training, and conservative per-window gates) limit selection bias. Reported mean MASE ranks: best base model 33.8, tournament 38.0, full router 19.4. The paper (arXiv:2609.28506v1) releases the routing table, expert index, pinned base-model revisions, score file and a dated snapshot of public scores plus a script to regenerate the leaderboard numbers.