activity
20182026
most citedLearning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors

200 citations · 784 across the 50 of their papers we have counts for

collaborators
Showing cs.AIShow all

11 papers · 1 filter

cs.AI2026

Incorporating Cognitive Load and Knowledge Transfer for Multi-Domain Knowledge Tracing

Haotian Zhang, Shucun Wang, Jinze Wu +6

Knowledge Tracing (KT) aims to assess students' dynamic knowledge states from their learning histories. While most existing KT methods focus on single-domain learning with notable…

cs.AI2025

CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive Perspective

Jiayu Liu, Zhenya Huang, Wei Dai +7

Although large language models (LLMs) show promise in solving complex mathematical tasks, existing evaluation paradigms rely solely on a coarse measure of overall answer accuracy,…

cs.AI2025

TestAgent: An Adaptive and Intelligent Expert for Human Assessment

Junhao Yu, Yan Zhuang, YuXuan Sun +5

Accurately assessing internal human states is key to understanding preferences, offering personalized services, and identifying challenges in real-world applications. Originating f…

cs.AI2025

Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment

Yuze Zhao, Tianyun Ji, Wenjun Feng +6

The reasoning abilities are one of the most enigmatic and captivating aspects of large language models (LLMs). Numerous studies are dedicated to exploring and expanding the boundar…

cs.AI2024★ 5 cited

A Survey of Models for Cognitive Diagnosis: New Developments and Future Directions

Fei Wang, Weibo Gao, Qi Liu +8

Cognitive diagnosis has been developed for decades as an effective measurement tool to evaluate human cognitive status such as ability level and knowledge mastery. It has been appl…

cs.AI2024★ 1 cited

Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning Process

Tong Xiao, Jiayu Liu, Zhenya Huang +4

Geometry Problem Solving (GPS), which is a classic and challenging math problem, has attracted much attention in recent years. It requires a solver to comprehensively understand bo…

cs.AI2023

Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm

Jiatong Li, Qi Liu, Fei Wang +5

Personalized learner modeling using cognitive diagnosis (CD), which aims to model learners' cognitive states by diagnosing learner traits from behavioral data, is a fundamental yet…

cs.AI2023★ 2 cited

Quiz-based Knowledge Tracing

Shuanghong Shen, Enhong Chen, Bihan Xu +4

Knowledge tracing (KT) aims to assess individuals' evolving knowledge states according to their learning interactions with different exercises in online learning systems (OIS), whi…

cs.AI2023★ 1 cited

Learning by Applying: A General Framework for Mathematical Reasoning via Enhancing Explicit Knowledge Learning

Jiayu Liu, Zhenya Huang, Chengxiang Zhai +1

Mathematical reasoning is one of the crucial abilities of general artificial intelligence, which requires machines to master mathematical logic and knowledge from solving problems.…

cs.AI2021★ 2 cited

Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing

Haoyang Bi, Haiping Ma, Zhenya Huang +5

Computerized Adaptive Testing (CAT) is emerging as a promising testing application in many scenarios, such as education, game and recruitment, which targets at diagnosing the knowl…

cs.AI2019★ 83 cited

Enhancing Item Response Theory for Cognitive Diagnosis

Song Cheng, Qi Liu

Cognitive diagnosis is a fundamental and crucial task in many educational applications, e.g., computer adaptive test and cognitive assignments. Item Response Theory (IRT) is a clas…