Peer Assessment Rubric Analyzer: An NLP approach to analyzing rubric items for better peer-review. - M. Parvez Rashid; Edward F. Gehringer; Mitchell Young; Divyang Doshi; Qinjin Jia; Yunkai Xiao (ITHET, 2021)

Labels are not necessary: Assessing peer-review helpfulness using domain adaptation based on self-training. - Chengyuan Liu; Divyang Doshi; Muskaan Bhargava; Ruixuan Shang; Jialin Cui; Dongkuan Xu; Edward F. Gehringer (BEA@ACL, 2023)

"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. - M. Parvez Rashid; Divyang Doshi; Sai Venkata Vinay; Qinjin Jia; Edward F. Gehringer (EDM, 2023)

ReffAKD: Resource-efficient Autoencoder-based Knowledge Distillation. - Divyang Doshi; Jung-Eun Kim (CoRR, 2024)