Copertina

Disentangled Knowledge Tracing for Alleviating Cognitive Bias

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhou, Yiyun, Lv, Zheqi, Zhang, Shengyu, Chen, Jingyuan
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Cuff-KT: Tackling Learners' Real-time Learning Pattern Adjustment via Tuning-Free Knowledge State Guided Model Updating
di: Zhou, Yiyun, et al.
Pubblicazione: (2025)

DKT2: Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Data
di: Zhou, Yiyun, et al.
Pubblicazione: (2025)

A$_3$B$_2$: Adaptive Asymmetric Adapter for Alleviating Branch Bias in Vision-Language Image Classification with Few-Shot Learning
di: Zhou, Yiyun, et al.
Pubblicazione: (2026)

A Rolling Stone Gathers No Moss: Adaptive Policy Optimization for Stable Self-Evaluation in Large Multimodal Models
di: Wang, Wenkai, et al.
Pubblicazione: (2025)

AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation
di: Tang, Zihao, et al.
Pubblicazione: (2024)

ModelGPT: Unleashing LLM's Capabilities for Tailored Model Generation
di: Tang, Zihao, et al.
Pubblicazione: (2024)

Beyond Student: An Asymmetric Network for Neural Network Inheritance
di: Zhou, Yiyun, et al.
Pubblicazione: (2026)

Tackling Device Data Distribution Real-time Shift via Prototype-based Parameter Editing
di: Lv, Zheqi, et al.
Pubblicazione: (2025)

Enhancing Knowledge Tracing with Concept Map and Response Disentanglement
di: Park, Soonwook, et al.
Pubblicazione: (2024)

Optimize Incompatible Parameters through Compatibility-aware Knowledge Integration
di: Lv, Zheqi, et al.
Pubblicazione: (2025)

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

Disentangling Granularity: An Implicit Inductive Bias in Factorized VAEs
di: Chen, Zihao, et al.
Pubblicazione: (2025)

FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning
di: Jiang, Zhonghua, et al.
Pubblicazione: (2024)

DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation
di: Fu, Kairui, et al.
Pubblicazione: (2024)

Structural Disentanglement in Bilinear MLPs via Architectural Inductive Bias
di: Nema, Ojasva, et al.
Pubblicazione: (2026)

Disentangling Length Bias In Preference Learning Via Response-Conditioned Modeling
di: Cai, Jianfeng, et al.
Pubblicazione: (2025)

Disentangling Bias by Modeling Intra- and Inter-modal Causal Attention for Multimodal Sentiment Analysis
di: Jiang, Menghua, et al.
Pubblicazione: (2025)

A Closer Look at Knowledge Distillation in Spiking Neural Network Training
di: Liu, Xu, et al.
Pubblicazione: (2025)

Disentangled Representations for Causal Cognition
di: Torresan, Filippo, et al.
Pubblicazione: (2024)

Partial Knowledge Distillation for Alleviating the Inherent Inter-Class Discrepancy in Federated Learning
di: Gan, Xiaoyu, et al.
Pubblicazione: (2024)

Uncertainty-aware Knowledge Tracing
di: Cheng, Weihua, et al.
Pubblicazione: (2025)

Group Relative Knowledge Distillation: Learning from Teacher's Relational Inductive Bias
di: Li, Chao, et al.
Pubblicazione: (2025)

Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
di: Peleg, Amit, et al.
Pubblicazione: (2024)

Regularized Schrödinger Bridge: Alleviating Distortion and Exposure Bias in Solving Inverse Problems
di: Yao, Qing, et al.
Pubblicazione: (2025)

Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling
di: Gao, Weibo, et al.
Pubblicazione: (2024)

D-FaST: Cognitive Signal Decoding with Disentangled Frequency-Spatial-Temporal Attention
di: Chen, Weiguo, et al.
Pubblicazione: (2024)

AutoGeo: Automating Geometric Image Dataset Creation for Enhanced Geometry Understanding
di: Huang, Zihan, et al.
Pubblicazione: (2024)

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

Jellyfish: Zero-Shot Federated Unlearning Scheme with Knowledge Disentanglement
di: Wang, Houzhe, et al.
Pubblicazione: (2026)

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

Dual-State Personalized Knowledge Tracing with Emotional Incorporation
di: Wang, Shanshan, et al.
Pubblicazione: (2024)

AAKT: Enhancing Knowledge Tracing with Alternate Autoregressive Modeling
di: Zhou, Hao, et al.
Pubblicazione: (2025)

Survey of Loss Augmented Knowledge Tracing
di: Shukurlu, Altun
Pubblicazione: (2025)

Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem
di: Huang, Chen, et al.
Pubblicazione: (2024)

Enhancing Post-Training Quantization via Future Activation Awareness
di: Lv, Zheqi, et al.
Pubblicazione: (2026)

Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery
di: Li, Ruifeng, et al.
Pubblicazione: (2024)

Disentangled Representation Learning via Modular Compositional Bias
di: Jung, Whie, et al.
Pubblicazione: (2025)

FL-Sailer: Efficient and Privacy-Preserving Federated Learning for Scalable Single-Cell Epigenetic Data Analysis via Adaptive Sampling
di: Zhang, Guangyi, et al.
Pubblicazione: (2026)

Sparse Binary Representation Learning for Knowledge Tracing
di: Badran, Yahya, et al.
Pubblicazione: (2025)

MOSAIC: Minimax-Optimal Sparsity-Adaptive Inference for Change Points in Dynamic Networks
di: Fan, Yingying, et al.
Pubblicazione: (2025)