mHUIMiner: A Fast High Utility Itemset Mining Algorithm for Sparse Datasets. - Alex Yuxuan Peng; Yun Sing Koh; Patricia Riddle (PAKDD (2), 2017)

Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems. - Alex Yuxuan Peng; Yun Sing Koh; Patricia Riddle; Bernhard Pfahringer (ECML/PKDD (1), 2018)

Investigating the effect of novel classes in semi-supervised learning. - Alex Yuxuan Peng; Yun Sing Koh; Patricia Riddle; Bernhard Pfahringer (ACML, 2019)

Multi-Step Deductive Reasoning Over Natural Language: An Empirical Study on Out-of-Distribution Generalisation. - Qiming Bao 001; Alex Yuxuan Peng; Tim Hartill; Neset Tan; Zhenyun Deng; Michael Witbrock; Jiamou Liu (NeSy, 2022)

Multi2Claim: Generating Scientific Claims from Multi-Choice Questions for Scientific Fact-Checking. - Neset Tan; Trung Nguyen; Joshua Bensemann; Alex Yuxuan Peng; Qiming Bao 001; Yang Chen 028; Mark Gahegan; Michael Witbrock (EACL, 2023)

A Dynamic Prompt-tuning Method for Data Augmentation with Associated Knowledge. - Qianqian Qi 001; Qiming Bao 001; Alex Yuxuan Peng; Jiamou Liu; Michael Witbrock (Tiny Papers @ ICLR, 2023)

Input-length-shortening and text generation via attention values. - Neset Özkan Tan; Alex Yuxuan Peng; Joshua Bensemann; Qiming Bao 001; Tim Hartill; Mark Gahegan; Michael Witbrock (CoRR, 2023)

Contrastive Learning with Logic-driven Data Augmentation for Logical Reasoning over Text. - Qiming Bao 001; Alex Yuxuan Peng; Zhenyun Deng; Wanjun Zhong; Neset Tan; Nathan Young; Yang Chen 028; Yonghua Zhu; Michael Witbrock; Jiamou Liu (CoRR, 2023)

Exploring Self-Reinforcement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models. - Qiming Bao 001; Juho Leinonen 001; Alex Yuxuan Peng; Wanjun Zhong; Tim Pistotti; Alice Huang; Paul Denny 001; Michael Witbrock; Jiamou Liu (CoRR, 2023)

A Systematic Evaluation of Large Language Models on Out-of-Distribution Logical Reasoning Tasks. - Qiming Bao 001; Gaël Gendron; Alex Yuxuan Peng; Wanjun Zhong; Neset Tan; Yang Chen 028; Michael Witbrock; Jiamou Liu (CoRR, 2023)

Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning. - Qiming Bao 001; Alex Yuxuan Peng; Zhenyun Deng; Wanjun Zhong; Gaël Gendron; Timothy Pistotti; Neset Tan; Nathan Young; Yang Chen 028; Yonghua Zhu; Paul Denny 001; Michael Witbrock; et al. (ACL (Findings), 2024)

Can Large Language Models Learn Independent Causal Mechanisms? - Gaël Gendron; Bao Trung Nguyen; Alex Yuxuan Peng; Michael J. Witbrock; Gillian Dobbie (EMNLP, 2024)

Assessing and Enhancing the Robustness of Large Language Models with Task Structure Variations for Logical Reasoning. - Qiming Bao 001; Gaël Gendron; Alex Yuxuan Peng; Wanjun Zhong; Neset Tan; Yang Chen 028; Michael Witbrock; Jiamou Liu (ICONIP (10), 2024)

Enhancing Data Augmentation with Knowledge-enriched Data Generation via Dynamic Prompt-tuning Method. - Qianqian Qi 001; Qiming Bao 001; Alex Yuxuan Peng; Jiamou Liu; Michael Witbrock (IJCNN, 2024)

Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models. - Qiming Bao 001; Juho Leinonen 001; Alex Yuxuan Peng; Wanjun Zhong; Gaël Gendron; Timothy Pistotti; Alice Huang; Paul Denny 001; Michael Witbrock; Jiamou Liu (AAAI, 2025)