Law of the Weakest Link: Cross Capabilities of Large Language Models
Ming Zhong Aston Zhang Xuewei Wang Rui Hou Wenhan Xiong Chenguang Zhu Zhengxing Chen Liang Tan Chloe Bi Mike Lewis Sravya Popuri Sharan Narang Melanie Kambadur Dhruv Mahajan Sergey Edunov Jiawei Han Laurens van der Maaten
The development and evaluation of Large Language Models (LLMs) have largely focused on individual capabilities. However, this overlooks the intersection of multiple abilities across different types of expertise that are often required for real-world tasks, which we term **cross capabilities**. To systematically explore this concept, we first define seven core individual capabilities and then pair them to form seven common cross capabilities, each supported by a manually constructed taxonomy. Building on these definitions, we introduce *CrossEval*, a benchmark comprising 1,400 human-annotated prompts, with 100 prompts for each individual and cross capability. To ensure reliable evaluation, we involve expert annotators to assess 4,200 model responses, gathering 8,400 human ratings with detailed explanations to serve as reference examples. Our findings reveal that current LLMs consistently exhibit the ``Law of the Weakest Link,'' where cross-capability performance is significantly constrained by the weakest component. Across 58 cross-capability scores from 17 models, 38 scores are lower than all individual capabilities, while 20 fall between strong and weak, but closer to the weaker ability. These results highlight LLMs' underperformance in cross-capability tasks, emphasizing the need to identify and improve their weakest capabilities as a key research priority. The code, benchmarks, and evaluations are available on our [project website](https://www.llm-cross-capabilities.org).
Cross Capability, Law of the Weakest Link, Evaluation, Large Langauge Models, Benchmark
We define and benchmark cross capabilities in LLMs, revealing the "Law of the Weakest Link": collaborative performance is significantly constrained by the weakest individual capability.