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Found 8 papers, 5 papers with code
A Practice of Tourism Knowledge Graph Construction based on Heterogeneous Information
So we develop two pipelines of processing methods for semi-structured data and unstructured data respectively.
AllTogether: Investigating the Efficacy of Spliced Prompt for Web Navigation using Large Language Models
Large Language Models (LLMs) have emerged as promising agents for web navigation tasks, interpreting objectives and interacting with web pages.
Cognition-Mode Aware Variational Representation Learning Framework for Knowledge Tracing
The Knowledge Tracing (KT) task plays a crucial role in personalized learning, and its purpose is to predict student responses based on their historical practice behavior sequence.
No Length Left Behind: Enhancing Knowledge Tracing for Modeling Sequences of Excessive or Insufficient Lengths
Knowledge tracing (KT) aims to predict students' responses to practices based on their historical question-answering behaviors.
Counterfactual Monotonic Knowledge Tracing for Assessing Students' Dynamic Mastery of Knowledge Concepts
Since students' mastery of knowledge concepts is often unlabeled, existing KT methods rely on the implicit paradigm of historical practice to mastery of knowledge concepts to students' responses to practices to address the challenge of unlabeled concept mastery.
Multi-source Education Knowledge Graph Construction and Fusion for College Curricula
The field of education has undergone a significant transformation due to the rapid advancements in Artificial Intelligence (AI).
A Chit-Chats Enhanced Task-Oriented Dialogue Corpora for Fuse-Motive Conversation Systems
The goal of building intelligent dialogue systems has largely been separately pursued under two motives: task-oriented dialogue (TOD) systems, and open-domain systems for chit-chat (CC).
Multi-Factors Aware Dual-Attentional Knowledge Tracing
In this paper, we propose Multi-Factors Aware Dual-Attentional model (MF-DAKT) which enriches question representations and utilizes multiple factors to model students' learning progress based on a dual-attentional mechanism.
