S3Eval: A Synthetic, Scalable, Systematic Evaluation Suite for Large Language Models¶
Arxiv Link - 2024-04-06 15:20:18
Abstract¶
The rapid development of Large Language Models (LLMs) has led to great strides in model capabilities like long-context understanding and reasoning. However, as LLMs are able to process longer contexts, it becomes more challenging to evaluate whether they have acquired certain capabilities, since the length of text (e.g., 200K tokens) they can process far exceeds what humans can reliably assess in a reasonable duration. In this paper, we propose using complex synthetic tasks as a proxy evaluation method, and present S3Eval, a Synthetic, Scalable, Systematic evaluation suite for LLMs evaluation. The synthetic nature of S3Eval provides users full control over the dataset, allowing them to systematically probe LLM capabilities by scaling text length and varying task difficulty across diverse scenarios. The strong correlation between S3Eval and real-world benchmarks demonstrates the soundness of using S3Eval for evaluation of LLMs. S3Eval provides a flexible and infinite long-context data generation method. We have generated a comprehensive dataset called S3Eval-Standard, and experimental results have shown that it poses significant challenges for all existing LLMs.
Socials¶
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| 🚀 Exciting developments in the field of Large Language Models (LLMs)! 🧠💡 As LLMs advance in their capabilities for long-context understanding and reasoning, evaluating their performance accurately becomes increasingly challenging due to their ability to process text far beyond human assessment limits. In a recent paper, researchers propose a groundbreaking solution - S3Eval, a Synthetic, Scalable, Systematic evaluation suite for LLMs. By leveraging complex synthetic tasks, S3Eval allows for the systematic probing of LLM capabilities by adjusting text length and task difficulty. The correlation between S3Eval and real-world benchmarks showcases its reliability for evaluating LLMs. Curious to learn more? Dive into the details here: Read the full paper 📚 #AI #NLP #LLMs #TechInnovation #ResearchPublication |
🚀 Exciting advancements in Large Language Models (LLMs)! A new evaluation method, S3Eval, offers a synthetic, scalable, systematic approach to assessing LLM capabilities. Learn more about this innovative evaluation suite and its impact on LLM development at: http://arxiv.org/abs/2310.15147v2 #AI #NLP #LLMs #TechInnovation 🤖📚 |