25 citations · 44 across the 9 of their papers we have counts for
10 papers
Cross-Modal Generative Augmentation for Visual Question Answering
Zixu Wang, Yishu Miao, Lucia Specia
Data augmentation has been shown to effectively improve the performance of multimodal machine learning models. This paper introduces a generative model for data augmentation by lev…
Exploiting Multimodal Reinforcement Learning for Simultaneous Machine Translation
Julia Ive, Andy Mingren Li, Yishu Miao +3
This paper addresses the problem of simultaneous machine translation (SiMT) by exploring two main concepts: (a) adaptive policies to learn a good trade-off between high translation…
Latent Variable Models for Visual Question Answering
Zixu Wang, Yishu Miao, Lucia Specia
Current work on Visual Question Answering (VQA) explore deterministic approaches conditioned on various types of image and question features. We posit that, in addition to image an…
Watch and Learn: Mapping Language and Noisy Real-world Videos with Self-supervision
Yujie Zhong, Linhai Xie, Sen Wang +2
In this paper, we teach machines to understand visuals and natural language by learning the mapping between sentences and noisy video snippets without explicit annotations. Firstly…
Selective Sensor Fusion for Neural Visual-Inertial Odometry
Changhao Chen, Stefano Rosa, Yishu Miao +4
Deep learning approaches for Visual-Inertial Odometry (VIO) have proven successful, but they rarely focus on incorporating robust fusion strategies for dealing with imperfect input…
Learning with Stochastic Guidance for Navigation
Linhai Xie, Yishu Miao, Sen Wang +5
Due to the sparse rewards and high degree of environment variation, reinforcement learning approaches such as Deep Deterministic Policy Gradient (DDPG) are plagued by issues of hig…