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2020 – today
- 2024
[c15]Qinjin Jia, Jialin Cui, Haoze Du, M. Parvez Rashid, Ruijie Xi, Ruochi Li, Edward F. Gehringer:
LLM-generated Feedback in Real Classes and Beyond: Perspectives from Students and Instructors. EDM 2024- [c14]Qinjin Jia, Jialin Cui, Ruijie Xi, Chengyuan Liu, M. Parvez Rashid, Ruochi Li, Edward F. Gehringer:
On Assessing the Faithfulness of LLM-generated Feedback on Student Assignments. EDM 2024 - [c13]Chengyuan Liu, Jialin Cui, Ruixuan Shang, Qinjin Jia, M. Parvez Rashid, Edward F. Gehringer:
Generative AI for Peer Assessment Helpfulness Evaluation. EDM 2024 - [c12]Jialin Cui
, Fangtong Zhou, Chengyuan Liu, Qinjin Jia, Yang Song, Edward F. Gehringer:
Utilizing the Constrained K-Means Algorithm and Pre-Class GitHub Contribution Statistics for Forming Student Teams. ITiCSE (1) 2024 - 2023
- [c11]Qinjin Jia, Yang Liu, Daoping Wu, Shaoyuan Xu, Huidong Liu, Jinmiao Fu, Roland Vollgraf, Bryan Wang:
KG-FLIP: Knowledge-guided Fashion-domain Language-Image Pre-training for E-commerce. ACL (industry) 2023: 81-88 - [c10]M. Parvez Rashid, Divyang Doshi, Sai Venkata Vinay, Qinjin Jia, Edward F. Gehringer:
"Can we reach agreement?": A context- and semantic-based clustering approach with semi-supervised text-feature extraction for finding disagreement in peer-assessment formative feedback. EDM 2023 - [c9]Kylie Griep, Leah Stone, Stephen Edwards, Malik Hill, Jialin Cui, Chengyuan Liu, Qinjin Jia, Yang Song:
Ensuring Ethical, Transparent, and Auditable Use of Education Data and Algorithms on AutoML. MLNLP 2023: 66-72 - 2022
- [c8]Qinjin Jia, Mitchell Young, Yunkai Xiao, Jialin Cui, Chengyuan Liu, M. Parvez Rashid, Edward F. Gehringer:
Insta-Reviewer: A Data-Driven Approach for Generating Instant Feedback on Students' Project Reports. EDM 2022 - [c7]Chengyuan Liu, Jialin Cui, Ruixuan Shang, Yunkai Xiao, Qinjin Jia, Edward F. Gehringer:
Improving problem detection in peer assessment through pseudo-labeling using semi-supervised learning. EDM 2022 - [c6]Jialin Cui, Ruochi Li, Kaida Lou, Chengyuan Liu, Yunkai Xiao, Qinjin Jia, Edward F. Gehringer, Runqiu Zhang:
Can Pre-class GitHub Contributions Predict Success by Student Teams? ICSE (SEET) 2022: 40-49 - [c5]Yunkai Xiao, Tianle Wang, Xinhua Sun, Yicong Li, Yang Song, Jialin Cui, Qinjin Jia, Chengyuan Liu, Edward F. Gehringer:
Modeling review helpfulness with augmented transformer neural networks. ICSC 2022: 83-90 - 2021
- [c4]Qinjin Jia, Jialin Cui, Yunkai Xiao, Chengyuan Liu, M. Parvez Rashid, Edward F. Gehringer:
ALL-IN-ONE: Multi-Task Learning BERT models for Evaluating Peer Assessments. EDM 2021 - [c3]M. Parvez Rashid, Edward F. Gehringer, Mitchell Young, Divyang Doshi, Qinjin Jia, Yunkai Xiao:
Peer Assessment Rubric Analyzer: An NLP approach to analyzing rubric items for better peer-review. ITHET 2021: 1-9 - [i2]Qinjin Jia, Jialin Cui, Yunkai Xiao, Chengyuan Liu, M. Parvez Rashid, Edward F. Gehringer:
ALL-IN-ONE: Multi-Task Learning BERT models for Evaluating Peer Assessments. CoRR abs/2110.03895 (2021) - 2020
- [c2]Yunkai Xiao, Gabriel Zingle, Qinjin Jia, Shoaib Akbar, Song Yang, Muyao Dong, Li Qi, Edward F. Gehringer:
Problem detection in peer assessments between subjects by effective transfer learning and active learning. EDM 2020 - [c1]Yunkai Xiao, Gabriel Zingle, Qinjin Jia, Harsh R. Shah, Yi Zhang, Tianyi Li, Mohsin Karovaliya, Weixiang Zhao, Yang Song, Jie Ji, Ashwin Balasubramaniam, Harshit Patel, Priyankha Bhalasubbramanian, Vikram Patel, Edward F. Gehringer:
Detecting Problem Statements in Peer Assessments. EDM 2020 - [i1]Yunkai Xiao, Gabriel Zingle, Qinjin Jia, Harsh R. Shah, Yi Zhang, Tianyi Li, Mohsin Karovaliya, Weixiang Zhao, Yang Song, Jie Ji, Ashwin Balasubramaniam, Harshit Patel, Priyankha Bhalasubbramanian, Vikram Patel, Edward F. Gehringer:
Detecting Problem Statements in Peer Assessments. CoRR abs/2006.04532 (2020)
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