datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
real-v-tsfm
REAL-V-TSFM Dataset
REAL-V-TSFM is a novel time series dataset derived entirely from real-world video data using optical flow methods. It was created to evaluate the generalization capabilities of Time Series Foundation Models (TSFMs) on realistic temporal dynamics, bridging the gap between synthetic benchmarks and real data.
Dataset Overview
Extraction Method: Uses the Lucas-Kanade optical flow algorithm to track pixel trajectories at detected keypoints in… See the full description on the dataset page: https://huggingface.co/datasets/Volavion/real-v-tsfm.tsfm-peft-bench
TSFM-PEFT-Bench
A cross-architecture benchmark for evaluating Parameter-Efficient Fine-Tuning
(PEFT) recommendation reliability in Time Series Foundation Models (TSFMs).
Companion code and artifacts for the paper "TSFM-PEFT-Bench: A
Cross-Architecture Benchmark for PEFT Selection in Time Series Foundation
Models" (under double-blind review at NeurIPS 2026 Datasets and Benchmarks
Track).
Quick metadata:
License: Apache-2.0 (LICENSE)
Croissant manifest: tsfm_peft_bench.croissant.json… See the full description on the dataset page: https://huggingface.co/datasets/EvalData/tsfm-peft-bench.TSFMI
TSFMI-Synthetic
Synthetic time-series datasets with mathematically exact ground-truth labels
for the TSFMI baseline-controlled probing protocol.
Companion data for the NeurIPS 2026 Evaluations & Datasets Track submission
"TSFMI: A Baseline-Controlled Evaluation Protocol for Time-Series Foundation
Model Representations." The code (anonymous) lives at
https://anonymous.4open.science/r/TSFMI.
Why this dataset exists
Probing time-series foundation models (TSFMs) is hard… See the full description on the dataset page: https://huggingface.co/datasets/EvalData/TSFMI.