Search Results for author: Yuanxin Ouyang

Found 8 papers, 5 papers with code

Explainable Few-shot Knowledge Tracing

1 code implementation23 May 2024 Haoxuan Li, Jifan Yu, Yuanxin Ouyang, Zhuang Liu, Wenge Rong, Juanzi Li, Zhang Xiong

Knowledge tracing (KT), aiming to mine students' mastery of knowledge by their exercise records and predict their performance on future test questions, is a critical task in educational assessment.

Knowledge Tracing

Wasserstein Dependent Graph Attention Network for Collaborative Filtering with Uncertainty

no code implementations9 Apr 2024 Haoxuan Li, Yuanxin Ouyang, Zhuang Liu, Wenge Rong, Zhang Xiong

Collaborative filtering (CF) is an essential technique in recommender systems that provides personalized recommendations by only leveraging user-item interactions.

Collaborative Filtering Graph Attention +1

A Review of Data Mining in Personalized Education: Current Trends and Future Prospects

no code implementations27 Feb 2024 Zhang Xiong, Haoxuan Li, Zhuang Liu, Zhuofan Chen, Hao Zhou, Wenge Rong, Yuanxin Ouyang

Personalized education, tailored to individual student needs, leverages educational technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness.

cognitive diagnosis Knowledge Tracing

Revisiting Demonstration Selection Strategies in In-Context Learning

1 code implementation22 Jan 2024 Keqin Peng, Liang Ding, Yancheng Yuan, Xuebo Liu, Min Zhang, Yuanxin Ouyang, DaCheng Tao

In this work, we first revisit the factors contributing to this variance from both data and model aspects, and find that the choice of demonstration is both data- and model-dependent.

In-Context Learning

Towards Making the Most of ChatGPT for Machine Translation

1 code implementation24 Mar 2023 Keqin Peng, Liang Ding, Qihuang Zhong, Li Shen, Xuebo Liu, Min Zhang, Yuanxin Ouyang, DaCheng Tao

We show that: 1) The performance of ChatGPT depends largely on temperature, and a lower temperature usually can achieve better performance; 2) Emphasizing the task information can further improve ChatGPT's performance, particularly in complex MT tasks; 3) Introducing domain information can elicit ChatGPT's generalization ability and improve its performance in the specific domain; 4) ChatGPT tends to generate hallucinations for non-English-centric MT tasks, which can be partially addressed by our proposed prompts but still need to be highlighted for the MT/NLP community.

In-Context Learning Machine Translation +2

Contrastive Learning for Recommender System

no code implementations5 Jan 2021 Zhuang Liu, Yunpu Ma, Yuanxin Ouyang, Zhang Xiong

To solve this problem, we propose a graph contrastive learning module for a general recommender system that learns the embeddings in a self-supervised manner and reduces the randomness of message dropout.

Collaborative Filtering Contrastive Learning +3

Similarity Based Auxiliary Classifier for Named Entity Recognition

1 code implementation IJCNLP 2019 Shiyuan Xiao, Yuanxin Ouyang, Wenge Rong, Jianxin Yang, Zhang Xiong

The segmentation problem is one of the fundamental challenges associated with name entity recognition (NER) tasks that aim to reduce the boundary error when detecting a sequence of entity words.

named-entity-recognition Named Entity Recognition +3

Cannot find the paper you are looking for? You can Submit a new open access paper.