3 papers
cs.CL2025
LITE: LLM-Impelled efficient Taxonomy Evaluation
Lin Zhang, Zhouhong Gu, Suhang Zheng +4
This paper presents LITE, an LLM-based evaluation method designed for efficient and flexible assessment of taxonomy quality. To address challenges in large-scale taxonomy evaluatio…
cs.CL2025
RECKON: Large-scale Reference-based Efficient Knowledge Evaluation for Large Language Model
Lin Zhang, Zhouhong Gu, Xiaoran Shi +2
As large language models (LLMs) advance, efficient knowledge evaluation becomes crucial to verifying their capabilities. Traditional methods, relying on benchmarks, face limitation…
cs.CL2024
DetectBench: Can Large Language Model Detect and Piece Together Implicit Evidence?
Zhouhong Gu, Lin Zhang, Xiaoxuan Zhu +8
Detecting evidence within the context is a key step in the process of reasoning task. Evaluating and enhancing the capabilities of LLMs in evidence detection will strengthen contex…