Papers with forstandard chain-of-thought
FROST: Factual Reasoning via Optimized Stochastic Trajectories in Large Language Models during Inference (2026.acl-industry)
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| Challenge: | Existing mitigation strategies are needed to improve large language models' reliability and efficiency. |
| Approach: | They propose an inference-time framework that balances exploration andexploitation without additional training or context augmentation. |
| Outcome: | FROST achieves 2–5 percentage point improvements over standard chain-of-thoughtprompting and reduces unsupported outputs by 40% relative to Standard CoT. |