Rewarding Doubt: Calibrated Confidence Expression of LLMs — interactive visual explainer | Rudrite Research

Researchers Stangel et al. published a paper on arXiv 2025 demonstrating that reinforcement learning on a proper scoring rule can teach large language models to express calibrated confidence in their answers. An interactive visual explainer of the paper is now available, featuring computed exhibits and verbatim quotes from the source.

Rewarding Doubt: Calibrated Confidence Expression of LLMs RL on a proper scoring rule teaches an LLM to express calibrated confidence in its answers. Stangel et al. · arXiv 2025 · Reasoning & RL. Read the paper ↗ https://arxiv.org/abs/2503.02623 A free, interactive, animated visual explainer of Rewarding Doubt: Calibrated Confidence Expression of LLMs — every exhibit computed from the real formulas, with verbatim quotes from the source. Questions - What is Rewarding Doubt: Calibrated Confidence Expression of LLMs? - RL on a proper scoring rule teaches an LLM to express calibrated confidence in its answers. - Who published Rewarding Doubt: Calibrated Confidence Expression of LLMs, and where? - Stangel et al. — arXiv 2025 arXiv:2503.02623 . - Where can I find a visual explainer of Rewarding Doubt: Calibrated Confidence Expression of LLMs? - Right here — a free, interactive, animated walkthrough of the whole paper, with exhibits computed from the real formulas and verbatim quotes from the source. Related explainers DeepSeek-R1 /deepseek-r1 Chain-of-Thought Prompting Elicits Reasoning in Large Language Models /chain-of-thought Training language models to follow instructions with human feedback /instructgpt Direct Preference Optimization: Your Language Model is Secretly a Reward Model /dpo DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models /deepseekmath Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters /test-time-compute Constitutional AI: Harmlessness from AI Feedback /constitutional-ai DAPO: An Open-Source LLM Reinforcement Learning System at Scale /dapo