Chain-of-thought reasoning improves LLM accuracy by 18% by 2027
Resolves: Average accuracy improvement of LLM models on GSM8K and MMLU-Pro benchmarks exceeds 18% compared to their 2025 baseline scores by December 31, 2027.
user-generated· tech_stocks
Chain-of-thought reasoning improves LLM accuracy by 18% by 2027
Market overview
By 2027, major large language models (LLMs) will demonstrate an 18% improvement in factual accuracy on complex reasoning tasks due to advancements in chain-of-thought prompting and enhanced training datasets. This will be validated by standardized benchmarks like GSM8K and MMLU-Pro.
tech_stocks prediction market
- Implied probability (Yes)
- 78%
- Closes
- 2027-12-31
About this prediction
Resolution criteria
Average accuracy improvement of LLM models on GSM8K and MMLU-Pro benchmarks exceeds 18% compared to their 2025 baseline scores by December 31, 2027.
Source: user-generated
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