When Does Longer Reasoning Help? Predicting Mathematical Reasoning Through Discovery and Execution
cs.LG, cs.CL
Submitted: 2026-10-04
Updated: 2026-10-04
Sources
- Give me a hint: Can LLMs take a hint to solve math problems?
- Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
- Understanding Performance Gap Between Parallel and Sequential Sampling in Large Reasoning Models
- Efficient Prediction of Pass@k Scaling in Large Language Models
- Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidance
- Self-Refine: Iterative Refinement with Self-Feedback
- More Bang for the Buck: Improving the Inference of Large Language Models at a Fixed Budget using Reset and Discard (ReD)
- Let Me Think! A Long Chain-of-Thought Can Be Worth Exponentially Many Short Ones
- e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs
- Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
- Planning In Natural Language Improves LLM Search For Code Generation
- Mitigating Strategy-Selection Bias in Reasoning for More Effective Test-Time Scaling
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