What type of study is this?

This is a Quantitative Study study.

October 20, 2025Open Access

Model Consistency as a Cheap yet Predictive Proxy for LLM Elo Scores

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Authors

ARAshwin RamaswamyMount Sinai Health System NDNestor Demeure ERErmal Rrapaj

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Implication

This analysis demonstrates model consistency as a cost-effective predictor of Elo scores for LLMs, highlighting its significant correlation with evaluations.

Key Points

Model consistency serves as a target metric for evaluating large language models effectively and cheaply.
The correlation between model consistency and human-generated Elo scores reaches 91%, confirming its predictive power.
This approach eliminates the need for human input in model evaluations, thus reducing associated costs.
The findings suggest that relying on model consistency can improve the efficiency of LLM assessments over traditional methods.

Cite This Study

Ramaswamy et al. (2025) studied this question.

synapsesocial.com/papers/68f6379bb481a140a36cf44e https://doi.org/10.48550/arxiv.2509.23510

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Implication

This analysis demonstrates model consistency as a cost-effective predictor of Elo scores for LLMs, highlighting its significant correlation with evaluations.

Model Consistency as a Cheap yet Predictive Proxy for LLM Elo Scores

Discussion

Member takes

Implication

Key Points

Cite This Study

Model Consistency as a Cheap yet Predictive Proxy for LLM Elo Scores

Discussion

Member takes

Implication

Key Points

Cite This Study

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Also Consider