4 citations · 7 across the 4 of their papers we have counts for
7 papers
Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations
Kuan-Hao Huang, Varun Iyer, Anoop Kumar +3
Syntactically controlled paraphrase generation has become an emerging research direction in recent years. Most existing approaches require annotated paraphrase pairs for training a…
Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction
Kuan-Hao Huang, I-Hung Hsu, Premkumar Natarajan +2
We present a study on leveraging multilingual pre-trained generative language models for zero-shot cross-lingual event argument extraction (EAE). By formulating EAE as a language g…
Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models
James Y. Huang, Kuan-Hao Huang, Kai-Wei Chang
Pre-trained language models have achieved huge success on a wide range of NLP tasks. However, contextual representations from pre-trained models contain entangled semantic and synt…
Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training
Kuan-Hao Huang, Wasi Uddin Ahmad, Nanyun Peng +1
Pre-trained multilingual language encoders, such as multilingual BERT and XLM-R, show great potential for zero-shot cross-lingual transfer. However, these multilingual encoders do…
Generating Syntactically Controlled Paraphrases without Using Annotated Parallel Pairs
Kuan-Hao Huang, Kai-Wei Chang
Paraphrase generation plays an essential role in natural language process (NLP), and it has many downstream applications. However, training supervised paraphrase models requires ma…
Examining Gender Bias in Languages with Grammatical Gender
Pei Zhou, Weijia Shi, Jieyu Zhao +4
Recent studies have shown that word embeddings exhibit gender bias inherited from the training corpora. However, most studies to date have focused on quantifying and mitigating suc…