36 citations · 71 across the 6 of their papers we have counts for
6 papers
Discovering Non-monotonic Autoregressive Orderings with Variational Inference
Xuanlin Li, Brandon Trabucco, Dong Huk Park +4
The predominant approach for language modeling is to process sequences from left to right, but this eliminates a source of information: the order by which the sequence was generate…
DAMSL: Domain Agnostic Meta Score-based Learning
John Cai, Bill Cai, Shengmei Shen
In this paper, we propose Domain Agnostic Meta Score-based Learning (DAMSL), a novel, versatile and highly effective solution that delivers significant out-performance over state-o…
SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning
John Cai, Bill Cai, Sheng Mei Shen
While many deep learning methods have seen significant success in tackling the problem of domain adaptation and few-shot learning separately, far fewer methods are able to jointly…
Noisy Self-Knowledge Distillation for Text Summarization
Yang Liu, Sheng Shen, Mirella Lapata
In this paper we apply self-knowledge distillation to text summarization which we argue can alleviate problems with maximum-likelihood training on single reference and noisy datase…
Cross-Domain Few-Shot Learning with Meta Fine-Tuning
John Cai, Sheng Mei Shen
In this paper, we tackle the new Cross-Domain Few-Shot Learning benchmark proposed by the CVPR 2020 Challenge. To this end, we build upon state-of-the-art methods in domain adaptat…
Anomaly Detection with Adversarial Dual Autoencoders
Ha Son Vu, Daisuke Ueta, Kiyoshi Hashimoto +3
Semi-supervised and unsupervised Generative Adversarial Networks (GAN)-based methods have been gaining popularity in anomaly detection task recently. However, GAN training is somew…