Anhui USTC iFLYTEK Co

research

∙ 08/28/2019

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Traffic Light Control

The development of intelligent traffic light control systems is essentia...

Yanan Wang, et al. ∙

research

∙ 01/31/2019

Episodic Training for Domain Generalization

Domain generalization (DG) is the challenging and topical problem of lea...

Da Li, et al. ∙

research

∙ 04/13/2019

Improving Distantly-supervised Entity Typing with Compact Latent Space Clustering

Recently, distant supervision has gained great success on Fine-grained E...

Bo Chen, et al. ∙

research

∙ 03/25/2022

Multimodal Pre-training Based on Graph Attention Network for Document Understanding

Document intelligence as a relatively new research topic supports many b...

Zhenrong Zhang, et al. ∙

research

∙ 06/13/2019

KCAT: A Knowledge-Constraint Typing Annotation Tool

Fine-grained Entity Typing is a tough task which suffers from noise samp...

Sheng Lin, et al. ∙

research

∙ 02/17/2022

A Study of Designing Compact Audio-Visual Wake Word Spotting System Based on Iterative Fine-Tuning in Neural Network Pruning

Audio-only-based wake word spotting (WWS) is challenging under noisy con...

Hengshun Zhou, et al. ∙

research

∙ 11/11/2016

Neural Networks Models for Entity Discovery and Linking

This paper describes the USTC_NELSLIP systems submitted to the Trilingua...

Dan Liu, et al. ∙

research

∙ 03/24/2016

Probabilistic Reasoning via Deep Learning: Neural Association Models

In this paper, we propose a new deep learning approach, called neural as...

Quan Liu, et al. ∙

research

∙ 07/15/2016

Attention-over-Attention Neural Networks for Reading Comprehension

Cloze-style queries are representative problems in reading comprehension...

Yiming Cui, et al. ∙

research

∙ 07/08/2016

Consensus Attention-based Neural Networks for Chinese Reading Comprehension

Reading comprehension has embraced a booming in recent NLP research. Sev...

Yiming Cui, et al. ∙

research

∙ 12/01/2015

LSTM Neural Reordering Feature for Statistical Machine Translation

Artificial neural networks are powerful models, which have been widely a...

Yiming Cui, et al. ∙

research

∙ 10/09/2015

Feedforward Sequential Memory Neural Networks without Recurrent Feedback

We introduce a new structure for memory neural networks, called feedforw...

Shiliang Zhang, et al. ∙

research

∙ 11/13/2016

Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge

In this paper, we propose commonsense knowledge enhanced embeddings (KEE...

Quan Liu, et al. ∙

research

∙ 11/12/2017

Natural Language Inference with External Knowledge

Modeling informal inference in natural language is very challenging. Wit...

Qian Chen, et al. ∙

research

∙ 09/25/2017

Dataset for the First Evaluation on Chinese Machine Reading Comprehension

Machine Reading Comprehension (MRC) has become enormously popular recent...

Yiming Cui, et al. ∙

research

∙ 08/04/2017

Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference

The RepEval 2017 Shared Task aims to evaluate natural language understan...

Qian Chen, et al. ∙

research

∙ 03/14/2017

Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering

The last several years have seen intensive interest in exploring neural-...

Junbei Zhang, et al. ∙

research

∙ 10/26/2016

Distraction-Based Neural Networks for Document Summarization

Distributed representation learned with neural networks has recently sho...

Qian Chen, et al. ∙

research

∙ 06/06/2016

Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution

Most existing approaches for zero pronoun resolution are heavily relying...

Ting Liu, et al. ∙

research

∙ 03/24/2016

Part-of-Speech Relevance Weights for Learning Word Embeddings

This paper proposes a model to learn word embeddings with weighted conte...

Quan Liu, et al. ∙

research

∙ 03/15/2018

HFL-RC System at SemEval-2018 Task 11: Hybrid Multi-Aspects Model for Commonsense Reading Comprehension

This paper describes the system which got the state-of-the-art results a...

Zhipeng Chen, et al. ∙

research

∙ 10/16/2018

Sequence-to-Sequence Acoustic Modeling for Voice Conversion

In this paper, a neural network named Sequence-to- sequence ConvErsion N...

Jing-Xuan Zhang, et al. ∙

research

∙ 10/17/2018

A Span-Extraction Dataset for Chinese Machine Reading Comprehension

Machine Reading Comprehension (MRC) has become enormously popular recent...

Yiming Cui, et al. ∙

research

∙ 11/01/2018

Spelling Error Correction Using a Nested RNN Model and Pseudo Training Data

We propose a nested recurrent neural network (nested RNN) model for Engl...

Hao Li, et al. ∙

research

∙ 11/20/2018

Improving Sequence-to-Sequence Acoustic Modeling by Adding Text-Supervision

This paper presents methods of making using of text supervision to impro...

Jing-Xuan Zhang, et al. ∙

research

∙ 11/21/2018

Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions

Machine Reading Comprehension (MRC) with multiple-choice questions requi...

Zhipeng Chen, et al. ∙

research

∙ 12/06/2018

The USTC-NEL Speech Translation system at IWSLT 2018

This paper describes the USTC-NEL system to the speech translation task ...

Dan Liu, et al. ∙

research

∙ 01/31/2019

Learning Efficient Lexically-Constrained Neural Machine Translation with External Memory

Recent years has witnessed dramatic progress of neural machine translati...

Ya Li, et al. ∙

research

∙ 04/22/2019

Exploring Unsupervised Pretraining and Sentence Structure Modelling for Winograd Schema Challenge

Winograd Schema Challenge (WSC) was proposed as an AI-hard problem in te...

Yu-Ping Ruan, et al. ∙

research

∙ 04/24/2019

Condition-Transforming Variational AutoEncoder for Conversation Response Generation

This paper proposes a new model, called condition-transforming variation...

Yu-Ping Ruan, et al. ∙

research

∙ 04/27/2019

Several Experiments on Investigating Pretraining and Knowledge-Enhanced Models for Natural Language Inference

Natural language inference (NLI) is among the most challenging tasks in ...

Tianda Li, et al. ∙

research

∙ 05/27/2019

QuesNet: A Unified Representation for Heterogeneous Test Questions

Understanding learning materials (e.g. test questions) is a crucial issu...

Yu Yin, et al. ∙

research

∙ 05/23/2019

Exploiting Cognitive Structure for Adaptive Learning

Adaptive learning, also known as adaptive teaching, relies on learning p...

Qi Liu, et al. ∙

research

∙ 06/19/2019

Pre-Training with Whole Word Masking for Chinese BERT

Bidirectional Encoder Representations from Transformers (BERT) has shown...

Yiming Cui, et al. ∙

research

∙ 09/01/2019

Cross-Lingual Machine Reading Comprehension

Though the community has made great progress on Machine Reading Comprehe...

Yiming Cui, et al. ∙

research

∙ 09/04/2019

Learning Dynamic Context Augmentation for Global Entity Linking

Despite of the recent success of collective entity linking (EL) methods,...

Xiyuan Yang, et al. ∙

research

∙ 09/24/2019

TripleNet: Triple Attention Network for Multi-Turn Response Selection in Retrieval-based Chatbots

We consider the importance of different utterances in the context for se...

Wentao Ma, et al. ∙

research

∙ 11/14/2019

Contextual Recurrent Units for Cloze-style Reading Comprehension

Recurrent Neural Networks (RNN) are known as powerful models for handlin...

Yiming Cui, et al. ∙

research

∙ 11/09/2019

Improving Machine Reading Comprehension via Adversarial Training

Adversarial training (AT) as a regularization method has proved its effe...

Ziqing Yang, et al. ∙

research

∙ 11/16/2019

Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots

This paper proposes an utterance-to-utterance interactive matching netwo...

Jia-Chen Gu, et al. ∙

research

∙ 12/19/2019

Discriminative Sentence Modeling for Story Ending Prediction

Story Ending Prediction is a task that needs to select an appropriate en...

Yiming Cui, et al. ∙

research

∙ 12/19/2019

CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension

We present a Chinese judicial reading comprehension (CJRC) dataset which...

Xingyi Duan, et al. ∙

research

∙ 02/28/2020

TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing

In this paper, we introduce TextBrewer, an open-source knowledge distill...

Ziqing Yang, et al. ∙

research

∙ 04/07/2020

Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots

In this paper, we study the problem of employing pre-trained language mo...

Jia-Chen Gu, et al. ∙

research

∙ 04/08/2020

DialBERT: A Hierarchical Pre-Trained Model for Conversation Disentanglement

Disentanglement is a problem in which multiple conversations occur in th...

Tianda Li, et al. ∙

research

∙ 04/07/2020

Is Graph Structure Necessary for Multi-hop Reasoning?

Recently, many works attempt to model texts as graph structure and intro...

Nan Shao, et al. ∙

research

∙ 04/07/2020

A Sentence Cloze Dataset for Chinese Machine Reading Comprehension

Owing to the continuous contributions by the Chinese NLP community, more...

Yiming Cui, et al. ∙

research

∙ 04/28/2020

Conversational Word Embedding for Retrieval-Based Dialog System

Human conversations contain many types of information, e.g., knowledge, ...

Wentao Ma, et al. ∙

research

∙ 04/29/2020

Benchmarking Robustness of Machine Reading Comprehension Models

Machine Reading Comprehension (MRC) is an important testbed for evaluati...

Chenglei Si, et al. ∙

research

∙ 04/30/2020

Filtering before Iteratively Referring for Knowledge-Grounded Response Selection in Retrieval-Based Chatbots

The challenges of building knowledge-grounded retrieval-based chatbots l...

Jia-Chen Gu, et al. ∙

Anhui USTC iFLYTEK Co

Featured Researchers