Search Results for author:
Found 8 papers, 4 papers with code
Learning to Fuse Sentences with Transformers for Summarization
The ability to fuse sentences is highly attractive for summarization systems because it is an essential step to produce succinct abstracts.
Bayesian Optimization for Selecting Efficient Machine Learning Models
The performance of many machine learning models depends on their hyper-parameter settings.
Understanding Points of Correspondence between Sentences for Abstractive Summarization
We create a dataset containing the documents, source and fusion sentences, and human annotations of points of correspondence between sentences.
Open-Domain Question Answering with Pre-Constructed Question Spaces
Our reader-retriever first uses an offline reader to read the corpus and generate collections of all answerable questions associated with their answers, and then uses an online retriever to respond to user queries by searching the pre-constructed question spaces for answers that are most likely to be asked in the given way.
High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks
To this end, we propose a novel synthesis framework called Photo-Sketch Synthesis using Multi-Adversarial Networks, (PS2-MAN) that iteratively generates low resolution to high resolution images in an adversarial way.
Ranked #2 on
Face Sketch Synthesis
on CUHK
FastHybrid: A Hybrid Model for Efficient Answer Selection
In this paper, we propose an extremely efficient hybrid model (FastHybrid) that tackles the problem from both an accuracy and scalability point of view.
Applying Deep Learning to Answer Selection: A Study and An Open Task
We apply a general deep learning framework to address the non-factoid question answering task.
