b'Shijin Wang'

research

∙ 06/19/2023

JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving

Although pre-trained language models (PLMs) have recently advanced the r...

0 Wayne Xin Zhao, et al. ∙

research

∙ 06/18/2023

Efficiently Measuring the Cognitive Ability of LLMs: An Adaptive Testing Perspective

Large language models (LLMs), like ChatGPT, have shown some human-like c...

0 Yan Zhuang, et al. ∙

research

∙ 06/04/2023

Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning

Chain-of-thought prompting (CoT) and tool augmentation have been validat...

0 Beichen Zhang, et al. ∙

research

∙ 05/09/2023

CSED: A Chinese Semantic Error Diagnosis Corpus

Recently, much Chinese text error correction work has focused on Chinese...

0 Bo Sun, et al. ∙

research

∙ 04/03/2023

MiniRBT: A Two-stage Distilled Small Chinese Pre-trained Model

In natural language processing, pre-trained language models have become ...

0 Xin Yao, et al. ∙

research

∙ 01/18/2023

Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training

Understanding mathematical questions effectively is a crucial task, whic...

0 Yuting Ning, et al. ∙

research

∙ 12/15/2022

Gradient-based Intra-attention Pruning on Pre-trained Language Models

Pre-trained language models achieve superior performance, but they are c...

0 Ziqing Yang, et al. ∙

research

∙ 11/10/2022

LERT: A Linguistically-motivated Pre-trained Language Model

Pre-trained Language Model (PLM) has become a representative foundation ...

0 Yiming Cui, et al. ∙

research

∙ 08/11/2022

Overview of CTC 2021: Chinese Text Correction for Native Speakers

In this paper, we present an overview of the CTC 2021, a Chinese text co...

0 Honghong Zhao, et al. ∙

research

∙ 06/13/2022

JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding

This paper aims to advance the mathematical intelligence of machines by ...

0 Wayne Xin Zhao, et al. ∙

research

∙ 02/28/2022

Cross-Lingual Text Classification with Multilingual Distillation and Zero-Shot-Aware Training

Multilingual pre-trained language models (MPLMs) not only can handle tas...

0 Ziqing Yang, et al. ∙

research

∙ 02/10/2022

InterHT: Knowledge Graph Embeddings by Interaction between Head and Tail Entities

Knowledge graph embedding (KGE) models learn the representation of entit...

0 Baoxin Wang, et al. ∙

research

∙ 06/08/2021

Adversarial Training for Machine Reading Comprehension with Virtual Embeddings

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

0 Ziqing Yang, et al. ∙

research

∙ 06/03/2021

Bilingual Alignment Pre-training for Zero-shot Cross-lingual Transfer

Multilingual pre-trained models have achieved remarkable transfer perfor...

0 Ziqing Yang, et al. ∙

research

∙ 05/10/2021

ExpMRC: Explainability Evaluation for Machine Reading Comprehension

Achieving human-level performance on some of Machine Reading Comprehensi...

0 Yiming Cui, et al. ∙

research

∙ 02/07/2021

Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering

Retrieving information from correlative paragraphs or documents to answe...

0 Nan Shao, et al. ∙

research

∙ 01/15/2021

Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing

Computerized Adaptive Testing (CAT) is emerging as a promising testing a...

11 Haoyang Bi, et al. ∙

research

∙ 11/13/2020

Unsupervised Explanation Generation for Machine Reading Comprehension

With the blooming of various Pre-trained Language Models (PLMs), Machine...

0 Yiming Cui, et al. ∙

research

∙ 11/03/2020

CharBERT: Character-aware Pre-trained Language Model

Most pre-trained language models (PLMs) construct word representations a...

0 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...

0 Chenglei Si, et al. ∙

research

∙ 04/29/2020

Revisiting Pre-Trained Models for Chinese Natural Language Processing

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

0 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, ...

0 Wentao Ma, 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...

0 Yiming Cui, 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...

0 Nan Shao, 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...

0 Ziqing Yang, 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...

0 Xingyi Duan, 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...

0 Yiming Cui, 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...

0 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...

0 Ziqing 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...

0 Wentao Ma, et al. ∙

research

∙ 09/01/2019

Cross-Lingual Machine Reading Comprehension

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

0 Yiming Cui, et al. ∙

research

∙ 06/19/2019

Pre-Training with Whole Word Masking for Chinese BERT

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

0 Yiming Cui, 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...

0 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...

0 Qi Liu, 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...

0 Zhipeng Chen, et al. ∙

research

∙ 10/17/2018

A Span-Extraction Dataset for Chinese Machine Reading Comprehension

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

0 Yiming Cui, 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...

0 Zhipeng 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...

0 Yiming Cui, et al. ∙

research

∙ 07/15/2016

Attention-over-Attention Neural Networks for Reading Comprehension

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

0 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...

0 Yiming Cui, 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...

0 Ting Liu, 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...

0 Yiming Cui, et al. ∙

Shijin Wang

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