19 citations · 41 across the 7 of their papers we have counts for
7 papers
Improving Image Captioning with Control Signal of Sentence Quality
Zhangzi Zhu, Hong Qu
In the dataset of image captioning, each image is aligned with several descriptions. Despite the fact that the quality of these descriptions varies, existing captioning models trea…
Self-Annotated Training for Controllable Image Captioning
Zhangzi Zhu, Tianlei Wang, Hong Qu
The Controllable Image Captioning (CIC) task aims to generate captions conditioned on designated control signals. Several structure-related control signals are proposed to control…
DPGNN: Dual-Perception Graph Neural Network for Representation Learning
Li Zhou, Wenyu Chen, Dingyi Zeng +4
Graph neural networks (GNNs) have drawn increasing attention in recent years and achieved remarkable performance in many graph-based tasks, especially in semi-supervised learning o…
Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model
Junwei Liao, Yu Shi, Ming Gong +5
Modern Automatic Speech Recognition (ASR) systems can achieve high performance in terms of recognition accuracy. However, a perfectly accurate transcript still can be challenging t…
Improving Zero-shot Neural Machine Translation on Language-specific Encoders-Decoders
Junwei Liao, Yu Shi, Ming Gong +3
Recently, universal neural machine translation (NMT) with shared encoder-decoder gained good performance on zero-shot translation. Unlike universal NMT, jointly trained language-sp…
Macroscopic Control of Text Generation for Image Captioning
Zhangzi Zhu, Tianlei Wang, Hong Qu
Despite the fact that image captioning models have been able to generate impressive descriptions for a given image, challenges remain: (1) the controllability and diversity of exis…
Improving Readability for Automatic Speech Recognition Transcription
Junwei Liao, Sefik Emre Eskimez, Liyang Lu +5
Modern Automatic Speech Recognition (ASR) systems can achieve high performance in terms of recognition accuracy. However, a perfectly accurate transcript still can be challenging t…