Papers by Xerxes Dotiwalla
Chatbot Arena Estimate: towards a generalized performance benchmark for LLM capabilities (2025.naacl-industry)
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Lucas Spangher, Tianle Li, William F. Arnold, Nick Masiewicki, Xerxes Dotiwalla, Rama Kumar Pasumarthi, Peter Grabowski, Eugene Ie, Daniel Gruhl
| Challenge: | Existing benchmark aggregation methods, such as Elo-based systems, can be resource-intensive, public facing, and time-consuming. |
| Approach: | They propose a framework for aggregating performance across diverse benchmarks that generates a “Goodness” and a ‘Fastness” score. |
| Outcome: | The proposed framework achieves higher Pearson correlation with Chatbot Arena Elo scores than MMLU’s correlation with chatbot Arena scores, validating its reliability for real-world LLM evaluation. |