activity
20242026
most citedSurvey of Computerized Adaptive Testing: A Machine Learning Perspective

5 citations · 5 across the 1 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

Jingyu Peng, Maolin Wang, Nan Wang +7

Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to jailbreak attacks. We hypothesize that…

cs.LG2026

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…

cs.CL2026

Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts?

Qingchuan Li, Jiatong Li, Zirui Liu +4

Logical reasoning with large language models (LLMs) has received growing attention. One mainstream approach translates natural language into formal logic and then applies symbolic…

cs.LG2025

Generative Cognitive Diagnosis

Jiatong Li, Qi Liu, Mengxiao Zhu

Cognitive diagnosis (CD) models latent cognitive states of human learners by analyzing their response patterns on diagnostic tests, serving as a crucial machine learning technique…

cs.AI2025

am-ELO: A Stable Framework for Arena-based LLM Evaluation

Zirui Liu, Jiatong Li, Yan Zhuang +5

Arena-based evaluation is a fundamental yet significant evaluation paradigm for modern AI models, especially large language models (LLMs). Existing framework based on ELO rating sy…

cs.CL2024

Leveraging LLMs for Hypothetical Deduction in Logical Inference: A Neuro-Symbolic Approach

Qingchuan Li, Jiatong Li, Tongxuan Liu +4

Large Language Models (LLMs) have exhibited remarkable potential across a wide array of reasoning tasks, including logical reasoning. Although massive efforts have been made to emp…