The article discusses the need for a systematic and multifaceted evaluation approach to assess the proficiency of Large Language Models (LLMs). Conventional benchmarks often use general criteria that are imprecise, leading to incomplete evaluations. To address this, researchers have developed the BIGGEN BENCH, a comprehensive benchmark with 77 tasks to evaluate nine different language model capabilities. This benchmark uses instance-specific evaluation criteria to provide a more accurate understanding of LLM performance. The team evaluated 103 frontier LMs using the BIGGEN BENCH, demonstrating consistent performance gains with model size scaling. They also compared evaluator LMs with human evaluations and found substantial correlations. The team’s primary contributions include describing the building and evaluation process of the BIGGEN BENCH, reporting evaluation findings for 103 LMs, and exploring approaches to improving open-source evaluator LMs. Overall, the BIGGEN BENCH provides a nuanced approach to evaluating LLMs and offers a more accurate understanding of their strengths and weaknesses.
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Source link: https://www.marktechpost.com/2024/06/16/biggen-bench-a-benchmark-designed-to-evaluate-nine-core-capabilities-of-language-models/?amp
#BiGGen Bench evaluates nine core language model capabilities.
