activity
20182022
most citedOn the Importance of Subword Information for Morphological Tasks in Truly Low-Resource Languages

2 citations · 2 across the 4 of their papers we have counts for

collaborators

8 papers

eess.AS2022

Gated Multimodal Fusion with Contrastive Learning for Turn-taking Prediction in Human-robot Dialogue

Jiudong Yang, Peiying Wang, Yi Zhu +3

Turn-taking, aiming to decide when the next speaker can start talking, is an essential component in building human-robot spoken dialogue systems. Previous studies indicate that mul…

cs.CL2022

Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis

Zexun Wang, Yuquan Le, Yi Zhu +4

Building Spoken Language Understanding (SLU) robust to Automatic Speech Recognition (ASR) errors is an essential issue for various voice-enabled virtual assistants. Considering tha…

cs.CL2021

Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification

Yi Zhu, Ehsan Shareghi, Yingzhen Li +2

Semi-supervised learning through deep generative models and multi-lingual pretraining techniques have orchestrated tremendous success across different areas of NLP. Nonetheless, th…

cs.CL2020

A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters

Mengjie Zhao, Yi Zhu, Ehsan Shareghi +4

Few-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with pretrained encoders like multilingual BERT. Despite its growing popularity, little to no…

cs.CL2020

Generating Semantically Valid Adversarial Questions for TableQA

Yi Zhu, Yiwei Zhou, Menglin Xia

Adversarial attack on question answering systems over tabular data (TableQA) can help evaluate to what extent they can understand natural language questions and reason with tables.…

cs.CL20192 cited

On the Importance of Subword Information for Morphological Tasks in Truly Low-Resource Languages

Yi Zhu, Benjamin Heinzerling, Ivan Vulić +3

Recent work has validated the importance of subword information for word representation learning. Since subwords increase parameter sharing ability in neural models, their value sh…