23 citations · 43 across the 3 of their papers we have counts for
4 papers
Empower Distantly Supervised Relation Extraction with Collaborative Adversarial Training
Tao Chen, Haochen Shi, Liyuan Liu +4
With recent advances in distantly supervised (DS) relation extraction (RE), considerable attention is attracted to leverage multi-instance learning (MIL) to distill high-quality su…
Multi-head or Single-head? An Empirical Comparison for Transformer Training
Liyuan Liu, Jialu Liu, Jiawei Han
Multi-head attention plays a crucial role in the recent success of Transformer models, which leads to consistent performance improvements over conventional attention in various app…
UCPhrase: Unsupervised Context-aware Quality Phrase Tagging
Xiaotao Gu, Zihan Wang, Zhenyu Bi +4
Identifying and understanding quality phrases from context is a fundamental task in text mining. The most challenging part of this task arguably lies in uncommon, emerging, and dom…
Data Quality Matters For Adversarial Training: An Empirical Study
Chengyu Dong, Liyuan Liu, Jingbo Shang
Multiple intriguing problems are hovering in adversarial training, including robust overfitting, robustness overestimation, and robustness-accuracy trade-off. These problems pose g…