15 citations · 20 across the 4 of their papers we have counts for
4 papers
Detecting Pretraining Data in Large Language Models from a Free-Energy Perspective
Chenye Ke, Zirui Liu, Qi Liu +4
Detecting pretraining data in large language models is challenging because high likelihood can reflect either training exposure or strong generalization. In the joint space of pred…
PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations
Jiatong Li, Renjun Hu, Kunzhe Huang +5
Expert-designed close-ended benchmarks are indispensable in assessing the knowledge capacity of large language models (LLMs). Despite their widespread use, concerns have mounted re…
Survey of Computerized Adaptive Testing: A Machine Learning Perspective
Yan Zhuang, Qi Liu, Haoyang Bi +12
Computerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual perfo…
Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary A. Pardos +5
As AI systems continue to evolve, their rigorous evaluation becomes crucial for their development and deployment. Researchers have constructed various large-scale benchmarks to det…