9 citations · 12 across the 5 of their papers we have counts for
3 papers · 1 filter
GRAFITE: Generative Regression Analysis Framework for Issue Tracking and Evaluation
Ja Young Lee, Mírian Silva, Mohamed Nasr +6
Large language models (LLMs) are largely motivated by their performance on popular topics and benchmarks at the time of their release. However, over time, contamination occurs due…
Efficient multi-prompt evaluation of LLMs
Felipe Maia Polo, Ronald Xu, Lucas Weber +6
Most popular benchmarks for comparing LLMs rely on a limited set of prompt templates, which may not fully capture the LLMs' abilities and can affect the reproducibility of results…
Large Language Model Routing with Benchmark Datasets
Tal Shnitzer, Anthony Ou, Mírian Silva +5
There is a rapidly growing number of open-source Large Language Models (LLMs) and benchmark datasets to compare them. While some models dominate these benchmarks, no single model t…