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Martingale Score: An Unsupervised Metric for Bayesian Rationality in LLM Reasoning

NeurIPS 2025 · Large language models › Language, safety and interpretability · approach: Statistical frameworks for LLM evaluation

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Proposes the Martingale Score, an unsupervised regression-based metric (OLS slope of belief update on prior belief) to quantify belief entrenchment in LLM reasoning, applied across forecasting, r/ChangeMyView, and OpenReview with CoT and debate.

Problem

LLM reasoning may entrench prior beliefs (confirmation bias) rather than update rationally on new evidence, and existing measures need ground truth or synthetic setups, so open-ended reasoning failures are hard to detect.

Approach

Operationalizes belief entrenchment as a violation of the Martingale property: the OLS slope of belief update (posterior minus prior) on prior belief, which should be zero under rational Bayesian updating; the score is unsupervised and domain-agnostic, and is validated against Brier score where ground truth exists.

Key results

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use debate instead of CoTLLMs across evaluated models and domains · Forecasting, ChangeMyView, and OpenReviewMartingale ScoreHelped
Use a prior-conforming prompt instead of no system prompt (ablation)LLMs · ForecastingMartingale Score: 0.075 \pm0.014 -> 0.082 \pm0.018Hurt
Use a critical-thinking prompt instead of no system prompt (ablation)LLMs · ForecastingMartingale Score: 0.075 \pm0.014 -> 0.072 \pm0.018Helped
Use a critical-thinking prompt instead of no system prompt (ablation)LLMs · ChangeMyView and OpenReviewMartingale ScoreNo clear effect
Add a prior-conforming prompt (ablation)GPT-4o (May 7), CoT · ForecastingMartingale Score: +0.0018 -> +0.0896^{\ast}Hurt
Add a prior-conforming prompt (ablation)DeepSeek R1, CoT · ForecastingMartingale Score: +0.0207^{\ast} -> +0.0450^{\ast}Hurt
Evaluate in ChangeMyView rather than Forecastingsame model, prompt, and CoT setup · ChangeMyView vs ForecastingMartingale Score: 0.037 \pm0.011 -> 0.103 \pm0.013Hurt
Evaluate in OpenReview rather than ForecastingLLMs · OpenReview vs ForecastingMartingale ScoreHurt
Increase the absolute value of the Martingale Scorereasoning setups · ForecastingBrier Score: Martingale Score 0.0: Brier Score <0.25; Martingale Score 0.04: worse than 0.250Hurt
Use DeepSeek R1 rather than the other tested modelsLLMs · Across evaluated domainsMartingale ScoreHelped
Use a prior-conforming prompt rather than no prompt (ablation)LLMs · Across evaluated setupsMartingale Score: \overline{M}_{\text{No-prompt}}=0.075 \pm0.014 -> \overline{M}_{\text{Prior-conforming}}=0.082 \pm0.018Hurt
Switch from GPT-4o (Apr 30) no-prompt CoT to prior-conforming CoT (ablation)GPT-4o (Apr 30) · ForecastingMartingale Score: +0.016 -> +0.080Hurt

Surprising findings

Limitations

Experimental setup

Datasets: Metaculus forecasting questions Polymarket forecasting questions r/ChangeMyView posts ICLR OpenReview submissions

Benchmarks: Metaculus Polymarket r/ChangeMyView OpenReview ICLR

Metrics: Martingale Score Brier score Pearson correlation Spearman correlation

Baselines: GPT-4o DeepSeek R1 DeepSeek V3 Gemini 2.0 Flash Llama 4 Scout Llama 4 Maverick

Builds on: chain-of-thought prompting debate

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