Datasets:
task_categories:
- question-answering
tags:
- future
- prediction
- LLM
- Agents
size_categories:
- n<1K
dataset_info:
features:
- name: id
dtype: string
- name: prompt
dtype: string
- name: end_time
dtype: string
- name: level
dtype: int64
splits:
- name: train
num_bytes: 63348
num_examples: 83
download_size: 16266
dataset_size: 63348
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Submission Guidelines — Weekly Prediction Challenge
📄 Technical Report: https://arxiv.org/pdf/2508.11987
🌐 LeaderBoard: https://futurex-ai.github.io/
We run a weekly real-time prediction challenge. This repo always contains latest events.
1. Weekly Rules
- A new set of tasks is released every week.
- This week's tasks cover events with an end time between
2025-09-24, 24:00 (UTC+8)
and2025-09-30, 24:00 (UTC+8)
. - Option A: If you submit your API, we will automatically test your model.
- Option B: If you run locally, you must download the tasks, make predictions, and email us your results before Wednesday 24:00 (UTC+8) each week.
- Late submissions will not be counted.
- The leaderboard for this round will be updated by
2025-10-01, 24:00 (UTC+8, Beijing Time)
.
⚠️ Next submission deadline: September 24th, 24:00 (UTC+8, Beijing Time)
2. How to Participate?
Two ways:
2.1 Option A — Submit Your API
Send an email to [email protected] with your model’s API (OpenAI-compatible endpoint + key).
Email subject format:
FutureX Challenge Entry — [Your Model Name]
Email body should include:
- Model details (base model, parameters, safety settings)
- Any required headers or rate limits
2.2 Option B — Run Locally & Submit Predictions
Download the latest tasks from our dataset: https://huggingface.co/datasets/futurex-ai/Futurex-Online
Run your model on the tasks.
Email your predictions to [email protected] before the deadline.
Email subject format:
FutureX Challenge Submission — [Your Model Name][Date]
Submission requirements:
- File format: JSON (or JSONL)
- Include dataset commit/hash you used
- Required fields:
id
,prediction
Example (table view):
id | prediction |
---|---|
event_001 | Yes |
event_002 | No |
event_003 | Maybe |
Example (JSONL format):
{"id": "event_001", "prediction": "Yes"}
{"id": "event_002", "prediction": "No"}
{"id": "event_003", "prediction": "Maybe"}
3. Leaderboard and Privacy
- Once your model has been tested on 200+ events, it will appear on the overall leaderboard.
- Weekly results will be ranked and shown on a dynamic leaderboard.
- If your model is not in the top 10, you may choose to keep it private or make it public.
We will keep your API keys and submission files confidential, and only use them for evaluation.