160 citations · 659 across the 33 of their papers we have counts for
8 papers · 1 filter
Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data
Stephen Obadinma, Hongyu Guo, Xiaodan Zhu
Recent work has demonstrated that using parameter efficient tuning techniques such as prefix tuning (or P-tuning) on pretrained language models can yield performance that is compar…
On SkipGram Word Embedding Models with Negative Sampling: Unified Framework and Impact of Noise Distributions
Dezhi Liu, Richong Zhang, Ziqiao Wang
SkipGram word embedding models with negative sampling, or SGN in short, is an elegant family of word embedding models. In this paper, we formulate a framework for word embedding, r…
Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework
Junfan Chen, Richong Zhang, Yongyi Mao +2
Distant supervision for relation extraction enables one to effectively acquire structured relations out of very large text corpora with less human efforts. Nevertheless, most of th…
Augmenting Data with Mixup for Sentence Classification: An Empirical Study
Hongyu Guo, Yongyi Mao, Richong Zhang
Mixup, a recent proposed data augmentation method through linearly interpolating inputs and modeling targets of random samples, has demonstrated its capability of significantly imp…
A Deep Network with Visual Text Composition Behavior
Hongyu Guo
While natural languages are compositional, how state-of-the-art neural models achieve compositionality is still unclear. We propose a deep network, which not only achieves competit…
End-to-End Multi-View Networks for Text Classification
Hongyu Guo, Colin Cherry, Jiang Su
We propose a multi-view network for text classification. Our method automatically creates various views of its input text, each taking the form of soft attention weights that distr…
Generating Text with Deep Reinforcement Learning
Hongyu Guo
We introduce a novel schema for sequence to sequence learning with a Deep Q-Network (DQN), which decodes the output sequence iteratively. The aim here is to enable the decoder to f…
Long Short-Term Memory Over Tree Structures
Xiaodan Zhu, Parinaz Sobhani, Hongyu Guo
The chain-structured long short-term memory (LSTM) has showed to be effective in a wide range of problems such as speech recognition and machine translation. In this paper, we prop…