Scaling Open-Ended Reasoning to Predict the Future
In brief:
High-stakes decision making involves reasoning under uncertainty about the future.
Why this matters
New research could change how AI systems work.
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Major industry investment.
In this work, we train language models to make predictions on open-ended forecasting questions.
Open receipts to verify and go deeper.
About this source
- Source
- arXiv cs.CL
- Type
- Research Preprint
- Published
- Credibility
- Peer-submitted research paper on arXiv
Always verify with the primary source before acting on this information.
arXiv cs.CL
·
Research Preprint
·
Primary Source
·
Scaling Open-Ended Reasoning to Predict the Future
TL;DR
High-stakes decision making involves reasoning under uncertainty about the future.
Quick Data
- Type
- Research Preprint
- Credibility
- Peer-submitted research paper on arXiv
- Published
Builder Context
Scan abstract → experiments → limitations. Also: verify benchmark methodology; check LICENSE and dependencies.
Full Analysis
Major industry investment.
In this work, we train language models to make predictions on open-ended forecasting questions.
Open receipts to verify and go deeper.
Source Verification
| Source |
arXiv cs.CL |
| Type |
Research Preprint |
| Tier |
Primary Source |
| Assessment |
Peer-submitted research paper on arXiv |
| URL |
https://arxiv.org/abs/2512.25070v1
|
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