Cover Image

ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Yunfei, Qin, Chuan, Shen, Dazhong, Ma, Haiping, Zhang, Le, Zhang, Xingyi, Zhu, Hengshu
Format:	Preprint
Published:	2023
Subjects:	Computers and Society Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FedCD: A Fairness-aware Federated Cognitive Diagnosis Framework
by: Yang, Shangshang, et al.
Published: (2025)

DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis
by: Yang, Shangshang, et al.
Published: (2024)

RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes
by: Yu, Xiaoshan, et al.
Published: (2024)

DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation
by: Yu, Xiaoshan, et al.
Published: (2024)

Diffusion-Inspired Cold Start with Sufficient Prior in Computerized Adaptive Testing
by: Ma, Haiping, et al.
Published: (2024)

Prompt Transfer for Dual-Aspect Cross Domain Cognitive Diagnosis
by: Liu, Fei, et al.
Published: (2024)

PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing
by: Yu, Xiaoshan, et al.
Published: (2025)

Symbolic Cognitive Diagnosis via Hybrid Optimization for Intelligent Education Systems
by: Shen, Junhao, et al.
Published: (2023)

Towards Efficient Resume Understanding: A Multi-Granularity Multi-Modal Pre-Training Approach
by: Jiang, Feihu, et al.
Published: (2024)

Exploring Heterogeneity and Uncertainty for Graph-based Cognitive Diagnosis Models in Intelligent Education
by: Shao, Pengyang, et al.
Published: (2024)

A Comprehensive Survey on Self-Interpretable Neural Networks
by: Ji, Yang, et al.
Published: (2025)

A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics
by: Qin, Chuan, et al.
Published: (2023)

Disentangling Heterogeneous Knowledge Concept Embedding for Cognitive Diagnosis on Untested Knowledge
by: Zhang, Miao, et al.
Published: (2024)

Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation
by: Wang, Janet, et al.
Published: (2023)

Convergence-aware Clustered Federated Graph Learning Framework for Collaborative Inter-company Labor Market Forecasting
by: Guo, Zhuoning, et al.
Published: (2024)

CALM: Culturally Self-Aware Language Models
by: Shen, Lingzhi, et al.
Published: (2026)

Language Representation Favored Zero-Shot Cross-Domain Cognitive Diagnosis
by: Liu, Shuo, et al.
Published: (2025)

Endowing Interpretability for Neural Cognitive Diagnosis by Efficient Kolmogorov-Arnold Networks
by: Yang, Shangshang, et al.
Published: (2024)

Unified Uncertainty Estimation for Cognitive Diagnosis Models
by: Wang, Fei, et al.
Published: (2024)

Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulations
by: Maksimovic, Milan, et al.
Published: (2024)

Bias and Identifiability in the Bounded Confidence Model
by: Borile, Claudio, et al.
Published: (2025)

End-to-end Graph Learning Approach for Cognitive Diagnosis of Student Tutorial
by: Yang, Fulai, et al.
Published: (2024)

Labor Migration Modeling through Large-scale Job Query Data
by: Guo, Zhuoning, et al.
Published: (2024)

Is Your Explanation Reliable: Confidence-Aware Explanation on Graph Neural Networks
by: Zhang, Jiaxing, et al.
Published: (2025)

Carbon Emission Prediction in China Considering New Quality Productive Forces Using a Deep & Corss Learning Modeling Framework
by: Xie, Haijin, et al.
Published: (2025)

A Computational Approach to Improving Fairness in K-means Clustering
by: Zhou, Guancheng, et al.
Published: (2025)

Fairness-Aware Graph Representation Learning with Limited Demographic Information
by: Wang, Zichong, et al.
Published: (2025)

Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
by: Han, Xiao, et al.
Published: (2024)

Geometry of Relaxed Fair Regression: A Unified Framework for Aware and Unaware Settings
by: Lince, M. Generali, et al.
Published: (2026)

Mining Voter Behaviour and Confidence: A Rule-Based Analysis of the 2022 U.S. Elections
by: Jubair, Md Al, et al.
Published: (2025)

Concept-Aware Latent and Explicit Knowledge Integration for Enhanced Cognitive Diagnosis
by: Chen, Yawen, et al.
Published: (2025)

Trajectory-Aware Reliability Modeling of Democratic Systems
by: Zaytsev, Dmitry, et al.
Published: (2026)

Confidence-Aware Multi-Field Model Calibration
by: Zhao, Yuang, et al.
Published: (2024)

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization
by: Teng, Yunfei, et al.
Published: (2025)

MetaCD: A Meta Learning Framework for Cognitive Diagnosis based on Continual Learning
by: Wu, Jin, et al.
Published: (2025)

BamaER: A Behavior-Aware Memory-Augmented Model for Exercise Recommendation
by: Yang, Qing, et al.
Published: (2026)

Can Domain Experts Rely on AI Appropriately? A Case Study on AI-Assisted Prostate Cancer MRI Diagnosis
by: Chen, Chacha, et al.
Published: (2025)

Gated Multimodal Learning for Interpretable Property Energy Performance Prediction and Retrofit Scenario Analysis
by: Bai, Yunfei, et al.
Published: (2026)

An Event-centric Framework for Predicting Crime Hotspots with Flexible Time Intervals
by: Jin, Jiahui, et al.
Published: (2024)

Game-Theoretic Machine Unlearning: Mitigating Extra Privacy Leakage
by: Liu, Hengzhu, et al.
Published: (2024)