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Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives

This repository contains the implementation for the paper titled Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives, published at AAAI 2024 [Paper].

Authors: Weibo Gao, Qi Liu, Hao Wang, et al.

Email: weibogao@mail.ustc.edu.cn

Environment Settings

We use Torch and DGL as the backend.

  • Torch version: '1.7.1'

Codes & Datasets

Details about the codes and datasets will be provided soon.

Related Works

  • RCD: Relation Map Driven Cognitive Diagnosis for Intelligent Education Systems (SIGIR'2021) [Paper] [Code] [Presentation Video]

  • Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis (SIGIR'2023) [Paper] [Code] [Presentation Video]

  • FedJudge: Federated Legal Large Language Model [Paper] [Code]

Last Update Date: March 14, 2024