# E-Scores for (In)Correctness Assessment of Generative Model Outputs

Source: [E-Scores for (In)Correctness Assessment of Generative Model Outputs](<https://www.sota2.com/research/paper/6902f1013ef7ccd74e5e4436>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-04-03T05:00:04.568Z

Authors: Guneet S. Dhillon, Javier Gonz\\'alez, Teodora Pandeva, Alicia Curth

Published: 2025-10-29T17:59:16.000Z

## Abstract

While generative models, especially large language models (LLMs), are ubiquitous in today's world, principled mechanisms to assess their (in)correctness are limited. Using the conformal prediction framework, previous works construct sets of LLM responses where the probability of including an incorrect response, or error, is capped at a user-defined tolerance level. However, since these methods are based on p-values, they are susceptible to p-hacking, i.e., choosing the tolerance level post-hoc can invalidate the guarantees. We therefore leverage e-values to complement generative model outputs with e-scores as measures of incorrectness. In addition to achieving the guarantees as before, e-scores further provide users with the flexibility of choosing data-dependent tolerance levels while upper bounding size distortion, a post-hoc notion of error. We experimentally demonstrate their efficacy in assessing LLM outputs under different forms of correctness: mathematical factuality and property constraints satisfaction.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Correctness Assessment on ProcessBench (test)](<https://www.sota2.com/research/sota/correctness-assessment-on-processbench-test.md>): Correctness Assessment; ProcessBench (test); Worst-case Size Distortion (QwenPRM): 0.79.

- [Correctness Assessment on UltraFeedback Property Constraints Satisfaction (test)](<https://www.sota2.com/research/sota/correctness-assessment-on-ultrafeedback-property-constraints-satisfaction-test.md>): Correctness Assessment; UltraFeedback Property Constraints Satisfaction (test); Worst-case Size Distortion (Helpfulness & Instruction-following): 0.8.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2510.25770>)

[PDF](<https://arxiv.org/pdf/2510.25770.pdf>)