# Balancing Test Accuracy and Security in Computerized Adaptive Testing

arXiv: https://arxiv.org/abs/2305.18312 · HTML: https://mlsanity.com/paper/2305.18312/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 16 references that are in the map.
- First posted on arXiv 18 May 2023.

## Builds on (most cited first, 3 of 3)

- [Categorical Reparameterization with Gumbel-Softmax](https://mlsanity.com/paper/1611.01144/) (2016)
- [The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables](https://mlsanity.com/paper/1611.00712/) (2016)
- [BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing](https://mlsanity.com/paper/2108.07386/) (2021)

## Built on by (most cited first, 4 of 4)

- [Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs](https://mlsanity.com/paper/2503.08551/) (2025)
- [Efficient Lifelong Model Evaluation in an Era of Rapid Progress](https://mlsanity.com/paper/2402.19472/) (2024)
- [Survey of Computerized Adaptive Testing: A Machine Learning Perspective](https://mlsanity.com/paper/2404.00712/) (2024)
- [Vis-CoT: A Human-in-the-Loop Framework for Interactive Visualization and Intervention in LLM Chain-of-Thought Reasoning](https://mlsanity.com/paper/2509.01412/) (2025)

## Abstract (arXiv)

Computerized adaptive testing (CAT) is a form of personalized testing that accurately measures students' knowledge levels while reducing test length. Bilevel optimization-based CAT (BOBCAT) is a recent framework that learns a data-driven question selection algorithm to effectively reduce test length and improve test accuracy. However, it suffers from high question exposure and test overlap rates, which potentially affects test security. This paper introduces a constrained version of BOBCAT to address these problems by changing its optimization setup and enabling us to trade off test accuracy for question exposure and test overlap rates. We show that C-BOBCAT is effective through extensive experiments on two real-world adult testing datasets.