Label Confusion Learning to Enhance Text Classification Models. - Biyang Guo; Songqiao Han; Xiao Han 001; Hailiang Huang; Ting Lu (AAAI, 2021)

What Have Been Learned & What Should Be Learned? An Empirical Study of How to Selectively Augment Text for Classification. - Biyang Guo; Songqiao Han; Hailiang Huang (CoRR, 2021)

Selective Text Augmentation with Word Roles for Low-Resource Text Classification. - Biyang Guo; Songqiao Han; Hailiang Huang (CoRR, 2022)

GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation. - Biyang Guo; Yeyun Gong; Yelong Shen; Songqiao Han; Hailiang Huang; Nan Duan; Weizhu Chen (CoRR, 2022)

How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection. - Biyang Guo; Xin Zhang; Ziyuan Wang; Minqi Jiang; Jinran Nie; Yuxuan Ding; Jianwei Yue; Yupeng Wu (CoRR, 2023)

Sample Design Engineering: An Empirical Study on Designing Better Fine-Tuning Samples for Information Extraction with LLMs. - Biyang Guo; He Wang; Wenyilin Xiao; Hong Chen; Zhuxin Lee; Songqiao Han; Hailiang Huang (EMNLP (Industry Track), 2024)

Sample Design Engineering: An Empirical Study of What Makes Good Downstream Fine-Tuning Samples for LLMs. - Biyang Guo; He Wang; Wenyilin Xiao; Hong Chen; Zhuxin Lee; Songqiao Han; Hailiang Huang (CoRR, 2024)