8 papers
MERIT: Memory-Enhanced Retrieval for Interpretable Knowledge Tracing
Runze Li, Kedi Chen, Guwei Feng +3
Knowledge Tracing (KT) models students' evolving knowledge states to predict future performance, serving as a foundation for personalized education. While traditional deep learning…
Markovian Pre-Trained Transformer for Next-Item Recommendation
Cong Xu, Guoliang Li, Jun Wang +1
We introduce the Markovian Pre-trained Transformer (MPT) for next-item recommendation, a transferable model fully pre-trained on synthetic Markov chains, yet capable of achieving s…
Attention Residual Fusion Network with Contrast for Source-free Domain Adaptation
Renrong Shao, Wei Zhang, Jun Wang
Source-free domain adaptation (SFDA) involves training a model on source domain and then applying it to a related target domain without access to the source data and labels during…
ColorAgent: Building A Robust, Personalized, and Interactive OS Agent
Ning Li, Qiqiang Lin, Zheng Wu +19
With the advancements in hardware, software, and large language model technologies, the interaction between humans and operating systems has evolved from the command-line interface…
Consistent Assistant Domains Transformer for Source-free Domain Adaptation
Renrong Shao, Wei Zhang, Kangyang Luo +2
Source-free domain adaptation (SFDA) aims to address the challenge of adapting to a target domain without accessing the source domain directly. However, due to the inaccessibility…
CIKT: A Collaborative and Iterative Knowledge Tracing Framework with Large Language Models
Runze Li, Siyu Wu, Jun Wang +1
Knowledge Tracing (KT) aims to model a student's learning state over time and predict their future performance. However, traditional KT methods often face challenges in explainabil…