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Add "agentic" model type to submission metadata & leaderboard (similar to GIFT-Eval) #153

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Description

@Jameswlepage

Add an agentic value to submission-level model-type metadata so agentic forecasting systems can self-declare and be filtered on the leaderboard. Metadata only. No change to tasks, metrics, EvaluationWindow, or aggregation.

Motivation
Agentic systems (tool-using, multi-step pipelines that produce forecasts) are now a distinct submission class, not plain pretrained or fine-tuned models. GIFT-Eval added an Agentic model type for this reason, and it gets used: the Moirai 2.0 paper filters out agentic solutions to get a clean foundation-model comparison. Without a tag, agentic submissions get excluded informally or silently skew a board readers assume is model v model.

Approach

  • Extend the submission-level model_type field with an agentic value, surfaced as a filterable leaderboard column.
  • Submission-level, not task-level, so it describes how the forecast was produced, orthogonal to the task taxonomy.
  • Same scoring and statistical treatment as everything else. The tag only enables include or exclude, not a separate ranking.

Happy to send a PR for this.

Activity

  1. shchur commented on Jun 18, 2026

    @shchur
    Contributor

    Hi @Jameswlepage, thanks for the suggestion. Agentic submissions are welcome, and I agree that we should make a separate category for them.

    Currently this metadata is stored ad-hoc in the leaderboard code at https://huggingface.co/spaces/autogluon/fev-bench/blob/main/src/utils.py#L27-L83. Therefore it's probably sufficient to just specify the submission type in the PR - we can then update the metadata on HF accordingly.

    One important detail: we should have clear instructions for authors of agentic submissions on how to disclose leakage on the benchmark tasks. I think a reasonable requirement will be "you should set trained_on_this_dataset=True if any of the base models used in the agentic system have seen this dataset during training". For example, if authors use TimesFM-2.5 within their system, they need to mark all of these datasets as leaky

    trained_on_datasets = [
    "favorita_transactions_1D",
    "favorita_transactions_1W",
    "fred_md_2025",
    "proenfo_gfc12",
    "proenfo_gfc14",
    "proenfo_gfc17",
    "kdd_cup_2022_10T",
    "m5_1D",
    "m5_1W",
    ]

    This puts more transparency requirements on the submissions - the authors need to disclose which models the system uses under the hood. Do you think it's a reasonable requirement?

  2. shchur commented on Oct 6, 2026

    @shchur
    Contributor

    Added a new submission type System which covers agentic systems. See https://github.com/autogluon/fev/tree/main/models#submit-results-to-the-fev-bench-leaderboard for more details.

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