research
∙
01/31/2023
Dynamic Scheduled Sampling with Imitation Loss for Neural Text Generation
State-of-the-art neural text generation models are typically trained to ...
share
research
∙
03/12/2022
Chart-to-Text: A Large-Scale Benchmark for Chart Summarization
Charts are commonly used for exploring data and communicating insights. ...
research
∙
10/14/2021
Rethinking Self-Supervision Objectives for Generalizable Coherence Modeling
Although large-scale pre-trained neural models have shown impressive per...
research
∙
06/14/2021
Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation
Advanced large-scale neural language models have led to significant succ...
research
∙
02/24/2021
Graphfool: Targeted Label Adversarial Attack on Graph Embedding
Deep learning is effective in graph analysis. It is widely applied in ma...
research
∙
09/19/2020
EI-MTD:Moving Target Defense for Edge Intelligence against Adversarial Attacks
With the boom of edge intelligence, its vulnerability to adversarial att...
research
∙
04/30/2020
CohEval: Benchmarking Coherence Models
Although coherence modeling has come a long way in developing novel mode...
research
∙
11/08/2019
Resurrecting Submodularity in Neural Abstractive Summarization
Submodularity is a desirable property for a variety of objectives in sum...
research
∙
09/17/2019
Fiber Nonlinearity Mitigation via the Parzen Window Classifier for Dispersion Managed and Unmanaged Links
Machine learning techniques have recently received significant attention...
research
∙
08/30/2019
Hierarchical Pointer Net Parsing
Transition-based top-down parsing with pointer networks has achieved sta...
research
∙
05/14/2019
A Unified Linear-Time Framework for Sentence-Level Discourse Parsing
We propose an efficient neural framework for sentence-level discourse an...
research
∙
04/12/2019
N2VSCDNNR: A Local Recommender System Based on Node2vec and Rich Information Network
Recommender systems are becoming more and more important in our daily li...
research
∙
02/27/2019
