Do Your Own Research: Learning to Forecast by Learning to Search
cs.LG
Submitted: 2026-10-01
Updated: 2026-10-01
Code: https://github.com/afifi-yusuf/prime-forecast
Sources
- Chronos: Learning the Language of Time Series
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Approaching Human-Level Forecasting with Language Models
- Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
- Agentic Forecasting with Structured Linguistic Beliefs
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Outcome-based Reinforcement Learning to Predict the Future
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks