97 citations · 264 across the 25 of their papers we have counts for
25 papers
SAM Struggles in Concealed Scenes -- Empirical Study on Segment Anything
Ge-Peng Ji, Deng-Ping Fan, Peng Xu +3
Segmenting anything is a ground-breaking step toward artificial general intelligence, and the Segment Anything Model (SAM) greatly fosters the foundation models for computer vision…
Trustworthy AI: From Principles to Practices
Bo Li, Peng Qi, Bo Liu +5
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment of various systems based on it. However, many current AI systems are found vulnerable to…
The JDDC 2.0 Corpus: A Large-Scale Multimodal Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service
Nan Zhao, Haoran Li, Youzheng Wu +2
With the development of the Internet, more and more people get accustomed to online shopping. When communicating with customer service, users may express their requirements by mean…
RoR: Read-over-Read for Long Document Machine Reading Comprehension
Jing Zhao, Junwei Bao, Yifan Wang +4
Transformer-based pre-trained models, such as BERT, have achieved remarkable results on machine reading comprehension. However, due to the constraint of encoding length (e.g., 512…
CUSTOM: Aspect-Oriented Product Summarization for E-Commerce
Jiahui Liang, Junwei Bao, Yifan Wang +3
Product summarization aims to automatically generate product descriptions, which is of great commercial potential. Considering the customer preferences on different product aspects…
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading Comprehension
Yongwei Zhou, Junwei Bao, Haipeng Sun +5
Reasoning machine reading comprehension (R-MRC) aims to answer complex questions that require discrete reasoning based on text. To support discrete reasoning, evidence, typically t…
Augmentation Pathways Network for Visual Recognition
Yalong Bai, Mohan Zhou, Wei Zhang +2
Data augmentation is practically helpful for visual recognition, especially at the time of data scarcity. However, such success is only limited to quite a few light augmentations (…
Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System
Zichuan Lin, Jing Huang, Bowen Zhou +2
Recent work (Takanobu et al., 2020) proposed the system-wise evaluation on dialog systems and found that improvement on individual components (e.g., NLU, policy) in prior work may…
Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation
Guangyi Liu, Zichao Yang, Tianhua Tao +6
Neural text generation models are typically trained by maximizing log-likelihood with the sequence cross entropy (CE) loss, which encourages an exact token-by-token match between a…
Conversational AI Systems for Social Good: Opportunities and Challenges
Peng Qi, Jing Huang, Youzheng Wu +2
Conversational artificial intelligence (ConvAI) systems have attracted much academic and commercial attention recently, making significant progress on both fronts. However, little…
SGG: Learning to Select, Guide, and Generate for Keyphrase Generation
Jing Zhao, Junwei Bao, Yifan Wang +3
Keyphrases, that concisely summarize the high-level topics discussed in a document, can be categorized into present keyphrase which explicitly appears in the source text, and absen…
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce
Song Xu, Haoran Li, Peng Yuan +5
Existing pre-trained language models (PLMs) have demonstrated the effectiveness of self-supervised learning for a broad range of natural language processing (NLP) tasks. However, m…
Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification
Xiaochen Hou, Peng Qi, Guangtao Wang +4
Recent work on aspect-level sentiment classification has demonstrated the efficacy of incorporating syntactic structures such as dependency trees with graph neural networks(GNN), b…
HAIR: Head-mounted AR Intention Recognition
David Puljiz, Bowen Zhou, Ke Ma +1
Human teams exhibit both implicit and explicit intention sharing. To further development of human-robot collaboration, intention recognition is crucial on both sides. Present appro…
Conversational Query Rewriting with Self-supervised Learning
Hang Liu, Meng Chen, Youzheng Wu +2
Context modeling plays a critical role in building multi-turn dialogue systems. Conversational Query Rewriting (CQR) aims to simplify the multi-turn dialogue modeling into a single…
Neural Kalman Filtering for Speech Enhancement
Wei Xue, Gang Quan, Chao Zhang +3
Statistical signal processing based speech enhancement methods adopt expert knowledge to design the statistical models and linear filters, which is complementary to the deep neural…
Incremental Learning for End-to-End Automatic Speech Recognition
Li Fu, Xiaoxiao Li, Libo Zi +4
In this paper, we propose an incremental learning method for end-to-end Automatic Speech Recognition (ASR) which enables an ASR system to perform well on new tasks while maintainin…
Speaker Diarization with Lexical Information
Tae Jin Park, Kyu J. Han, Jing Huang +4
This work presents a novel approach for speaker diarization to leverage lexical information provided by automatic speech recognition. We propose a speaker diarization system that c…
Graph Sequential Network for Reasoning over Sequences
Ming Tu, Jing Huang, Xiaodong He +1
Recently Graph Neural Network (GNN) has been applied successfully to various NLP tasks that require reasoning, such as multi-hop machine reading comprehension. In this paper, we co…
The JDDC Corpus: A Large-Scale Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service
Meng Chen, Ruixue Liu, Lei Shen +5
Human conversations are complicated and building a human-like dialogue agent is an extremely challenging task. With the rapid development of deep learning techniques, data-driven m…
Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding
Yun Tang, Jing Huang, Guangtao Wang +2
Translational distance-based knowledge graph embedding has shown progressive improvements on the link prediction task, from TransE to the latest state-of-the-art RotatE. However, N…
Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents
Ming Tu, Kevin Huang, Guangtao Wang +3
Interpretable multi-hop reading comprehension (RC) over multiple documents is a challenging problem because it demands reasoning over multiple information sources and explaining th…
Relation Module for Non-answerable Prediction on Question Answering
Kevin Huang, Yun Tang, Jing Huang +2
Machine reading comprehension(MRC) has attracted significant amounts of research attention recently, due to an increase of challenging reading comprehension datasets. In this paper…
SenGen: Sentence Generating Neural Variational Topic Model
Ramesh Nallapati, Igor Melnyk, Abhishek Kumar +1
We present a new topic model that generates documents by sampling a topic for one whole sentence at a time, and generating the words in the sentence using an RNN decoder that is co…