136 citations · 231 across the 16 of their papers we have counts for
16 papers
CS-Mixer: A Cross-Scale Vision MLP Model with Spatial-Channel Mixing
Jonathan Cui, David A. Araujo, Suman Saha +1
Despite their simpler information fusion designs compared with Vision Transformers and Convolutional Neural Networks, Vision MLP architectures have demonstrated strong performance…
Learning towards Selective Data Augmentation for Dialogue Generation
Xiuying Chen, Mingzhe Li, Jiayi Zhang +6
As it is cumbersome and expensive to acquire a huge amount of data for training neural dialog models, data augmentation is proposed to effectively utilize existing training samples…
MoralDial: A Framework to Train and Evaluate Moral Dialogue Systems via Moral Discussions
Hao Sun, Zhexin Zhang, Fei Mi +6
Morality in dialogue systems has raised great attention in research recently. A moral dialogue system aligned with users' values could enhance conversation engagement and user conn…
C3KG: A Chinese Commonsense Conversation Knowledge Graph
Dawei Li, Yanran Li, Jiayi Zhang +4
Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational models to plan the next steps. To fill the gap,…
MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation
Quan Tu, Yanran Li, Jianwei Cui +3
Applying existing methods to emotional support conversation -- which provides valuable assistance to people who are in need -- has two major limitations: (a) they generally employ…
Whole Brain Segmentation with Full Volume Neural Network
Yeshu Li, Jonathan Cui, Yilun Sheng +4
Whole brain segmentation is an important neuroimaging task that segments the whole brain volume into anatomically labeled regions-of-interest. Convolutional neural networks have de…
Multi-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition
Pan Xie, Zhi Cui, Yao Du +4
Continuous sign language recognition (cSLR) is a public significant task that transcribes a sign language video into an ordered gloss sequence. It is important to capture the fine-…
Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning
Binbin Xie, Jinsong Su, Yubin Ge +4
Code generation aims to automatically generate a piece of code given an input natural language utterance. Currently, among dominant models, it is treated as a sequence-to-tree task…
Towards an Online Empathetic Chatbot with Emotion Causes
Yanran Li, Ke Li, Hongke Ning +5
Existing emotion-aware conversational models usually focus on controlling the response contents to align with a specific emotion class, whereas empathy is the ability to understand…
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng +4
Numerous task-specific variants of conditional generative adversarial networks have been developed for image completion. Yet, a serious limitation remains that all existing algorit…
Modeling Homophone Noise for Robust Neural Machine Translation
Wenjie Qin, Xiang Li, Yuhui Sun +3
In this paper, we propose a robust neural machine translation (NMT) framework. The framework consists of a homophone noise detector and a syllable-aware NMT model to homophone erro…
Writing Polishment with Simile: Task, Dataset and A Neural Approach
Jiayi Zhang, Zhi Cui, Xiaoqiang Xia +4
A simile is a figure of speech that directly makes a comparison, showing similarities between two different things, e.g. "Reading papers can be dull sometimes,like watching grass g…
Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension
Xiuying Chen, Zhi Cui, Jiayi Zhang +5
In multi-turn dialog, utterances do not always take the full form of sentences \cite{Carbonell1983DiscoursePA}, which naturally makes understanding the dialog context more difficul…
Infusing Sequential Information into Conditional Masked Translation Model with Self-Review Mechanism
Pan Xie, Zhi Cui, Xiuyin Chen +3
Non-autoregressive models generate target words in a parallel way, which achieve a faster decoding speed but at the sacrifice of translation accuracy. To remedy a flawed translatio…
Focus-Constrained Attention Mechanism for CVAE-based Response Generation
Zhi Cui, Yanran Li, Jiayi Zhang +3
To model diverse responses for a given post, one promising way is to introduce a latent variable into Seq2Seq models. The latent variable is supposed to capture the discourse-level…
Modeling Discourse Structure for Document-level Neural Machine Translation
Junxuan Chen, Xiang Li, Jiarui Zhang +4
Recently, document-level neural machine translation (NMT) has become a hot topic in the community of machine translation. Despite its success, most of existing studies ignored the…