| --- |
| license: apache-2.0 |
| pretty_name: FUTURE-TS |
| tags: |
| - time-series |
| - forecasting |
| - benchmark |
| - evaluation |
| - foundation-models |
| - leaderboard |
| task_categories: |
| - time-series-forecasting |
| --- |
| |
| # FUTURE-TS |
|
|
| ## Summary |
|
|
| FUTURE-TS v0.1.0 is a public-preview benchmark for time-series foundation |
| models. It treats evaluation as an executable protocol: task cards declare |
| issue times, horizons, available history, delayed labels, adaptation budgets, |
| resource limits, and metrics; submissions are validated, scored, and audited |
| against those contracts. |
|
|
| The core rule is future-only ranking: a submission is only ranked on labels |
| that were not available when the model was frozen. |
|
|
| ## Benchmark Surface |
|
|
| - Release: `v0.1.0` |
| - Strict surface: `benchmarks/v1/benchmark.json` |
| - Surface identifier: `future-ts-v1` |
| - Tasks: 25 |
| - Tiers: `public_dev`, `blind_archive`, `live` |
| - Tracks: forecasting core, covariate-aware, multivariate relational, data |
| quality, event, transfer, multimodal context |
| - Required manifest: `require_pretraining_manifest=true` |
| - Headline score: `tier_weighted_score` |
| - Additional views: capability vector `(F, U, R, A, E, D)`, Pareto flag, |
| rank-based mean-of-ranks aggregate with bootstrap CI |
|
|
| The strict surface rejects manifestless submissions so "clean" and |
| "undeclared" are not conflated. |
|
|
| ## Current Empirical Run |
|
|
| The current canonical empirical artifacts are in: |
|
|
| ```text |
| reports/tsfm_ai_empirical_v2_multi_budget/ |
| ``` |
|
|
| This run is the `future-ts-empirical-v2` hosted TSFM.ai slice used by the |
| empirical paper. It exercises 15 real-data tasks across three context budgets: |
|
|
| | Budget | Context length | |
| |--------|----------------| |
| | `zero_shot` | 96 | |
| | `few_shot` | 192 | |
| | `s16` | 288 | |
|
|
| Current result snapshot: |
|
|
| - Surfaced public catalog entries: 52 |
| - Merged public submissions: 51 |
| - Scored public models: 47 |
| - Positive overall scores: 30 |
| - Current winner: `Datadog/Toto-2.0-1B` |
| - Winner score: `0.2369` |
| - Rank-consistency leader by mean rank: `amazon/chronos-2` |
|
|
| Top five by tier-weighted score: |
|
|
| | Rank | Model | Score | |
| |------|-------|-------| |
| | 1 | `Datadog/Toto-2.0-1B` | 0.2369 | |
| | 2 | `Datadog/Toto-2.0-313m` | 0.2214 | |
| | 3 | `NX-AI/TiRex` | 0.2024 | |
| | 4 | `Salesforce/moirai-2.0-R-small` | 0.1860 | |
| | 5 | `amazon/chronos-2` | 0.1851 | |
|
|
| ## How To Submit A Model Entry |
|
|
| Submit a pull request under: |
|
|
| ```text |
| submissions/community/<org>_<model>/ |
| ``` |
|
|
| Each submission directory must contain: |
|
|
| - `script.py`: sealed-runner entry point |
| - `declaration.json`: metadata, declarations, artifact URI, and pretraining |
| manifest |
| - `README.md`: short model description and links |
|
|
| CI validates the directory structure and smoke-runs `script.py` through the |
| sealed runner. After review, the evaluator runs the full benchmark and can |
| publish the resulting `BenchmarkReport`. |
|
|
| See [submission-guide.md](submission-guide.md) for the full process. |
|
|
| ## What This Does Not Yet Claim |
|
|
| The v0.1.0 release is a local benchmark package plus sealed-runner MVP. It is |
| not yet a fully hosted, externally attested live benchmark service. |
|
|
| Do not read the current empirical run as a permanent universal TSFM ranking. |
| It is a first real-data slice over 15 tasks and one materialized wave. Wider |
| task coverage, repeated waves, hosted attestation, immutable submission |
| windows, and stronger manifest evidence are the next steps. |
|
|
| See [validity-envelope.md](validity-envelope.md) for the precise claim |
| boundary. |
|
|
| ## Local Commands |
|
|
| Validate the strict benchmark: |
|
|
| ```bash |
| python3 -m future_ts.cli validate-benchmark benchmarks/v1/benchmark.json |
| ``` |
|
|
| Run the sealed reference submission: |
|
|
| ```bash |
| python3 -m future_ts.cli run-sealed \ |
| examples/submissions/reference_seasonal_naive.py \ |
| .tmp/task_windows.json \ |
| --output .tmp/submission.json \ |
| --submission-id local::reference_seasonal_naive \ |
| --model-name "Reference Seasonal Naive" |
| ``` |
|
|
| Build a leaderboard from saved reports: |
|
|
| ```bash |
| python3 -m future_ts.cli leaderboard reports/tsfm_ai_empirical_v2_multi_budget/*.report.json |
| ``` |
|
|
| These core workflows do not require TSFM.ai. A TSFM.ai API key is only needed |
| to run the optional hosted-catalog evaluation commands that invoke hosted |
| models. |
|
|
| ## More Detail |
|
|
| - Design paper: `paper/future_ts_design.pdf` |
| - Empirical paper: `paper/future_ts_empirical.pdf` |
| - Benchmark design notes: [benchmark-design.md](benchmark-design.md) |
| - Submission guide: [submission-guide.md](submission-guide.md) |
| - Sealed runner: [sealed-runner.md](sealed-runner.md) |
| - Validity envelope: [validity-envelope.md](validity-envelope.md) |
|
|
|
|
| ## Repository Contents |
|
|
| - `benchmarks/`: public benchmark surfaces and task-card references. |
| - `schemas/`: JSON Schemas for benchmark, task, submission, and actual records. |
| - `docs/`: benchmark card, submission guide, sealed-runner notes, and validity envelope. |
| - `reports/tsfm_ai_empirical_v2_multi_budget/`: canonical public empirical reports. |
| - `paper/`: design and empirical PDFs. |
|
|
