b'Pengfei Liu'

SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization

In this paper, we present a conceptually simple while empirically powerf...
06/03/2021 ∙ by Yixin Liu, et al. ∙ 0 ∙ share

read it
CitationIE: Leveraging the Citation Graph for Scientific Information Extraction

Automatically extracting key information from scientific documents has t...
06/03/2021 ∙ by Vijay Viswanathan, et al. ∙ 0 ∙ share

read it
SpanNER: Named Entity Re-/Recognition as Span Prediction

Recent years have seen the paradigm shift of Named Entity Recognition (N...
06/01/2021 ∙ by Jinlan Fu, et al. ∙ 0 ∙ share

read it
Hierarchical Modeling for Out-of-Scope Domain and Intent Classification

User queries for a real-world dialog system may sometimes fall outside t...
04/30/2021 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Open Intent Discovery through Unsupervised Semantic Clustering and Dependency Parsing

Intent understanding plays an important role in dialog systems, and is t...
04/25/2021 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation

Machine learning has brought striking advances in multilingual natural l...
04/15/2021 ∙ by Sebastian Ruder, et al. ∙ 0 ∙ share

read it
RefSum: Refactoring Neural Summarization

Although some recent works show potential complementarity among differen...
04/15/2021 ∙ by Yixin Liu, et al. ∙ 0 ∙ share

read it
EXPLAINABOARD: An Explainable Leaderboard for NLP

With the rapid development of NLP research, leaderboards have emerged as...
04/13/2021 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa

Aspect-based Sentiment Analysis (ABSA), aiming at predicting the polarit...
04/11/2021 ∙ by Junqi Dai, et al. ∙ 0 ∙ share

read it
Larger-Context Tagging: When and Why Does It Work?

The development of neural networks and pretraining techniques has spawne...
04/09/2021 ∙ by Jinlan Fu, et al. ∙ 0 ∙ share

read it
Coining goldMEDAL: A New Contribution to Data Lake Generic Metadata Modeling

The rise of big data has revolutionized data exploitation practices and ...
03/24/2021 ∙ by Etienne Scholly, et al. ∙ 0 ∙ share

read it
Towards More Fine-grained and Reliable NLP Performance Prediction

Performance prediction, the task of estimating a system's performance wi...
02/10/2021 ∙ by Zihuiwen Ye, et al. ∙ 0 ∙ share

read it
Can We Automate Scientific Reviewing?

The rapid development of science and technology has been accompanied by ...
01/30/2021 ∙ by Weizhe Yuan, et al. ∙ 0 ∙ share

read it
RethinkCWS: Is Chinese Word Segmentation a Solved Task?

The performance of the Chinese Word Segmentation (CWS) systems has gradu...
11/13/2020 ∙ by Jinlan Fu, et al. ∙ 0 ∙ share

read it
Interpretable Multi-dataset Evaluation for Named Entity Recognition

With the proliferation of models for natural language processing tasks, ...
11/13/2020 ∙ by Jinlan Fu, et al. ∙ 0 ∙ share

read it
Metrics also Disagree in the Low Scoring Range: Revisiting Summarization Evaluation Metrics

In text summarization, evaluating the efficacy of automatic metrics with...
11/08/2020 ∙ by Manik Bhandari, et al. ∙ 0 ∙ share

read it
GSum: A General Framework for Guided Neural Abstractive Summarization

Neural abstractive summarization models are flexible and can produce coh...
10/15/2020 ∙ by Zi-Yi Dou, et al. ∙ 0 ∙ share

read it
Re-evaluating Evaluation in Text Summarization

Automated evaluation metrics as a stand-in for manual evaluation are an ...
10/14/2020 ∙ by Manik Bhandari, et al. ∙ 0 ∙ share

read it
CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems

Neural network-based models augmented with unsupervised pre-trained know...
10/11/2020 ∙ by Yiran Chen, et al. ∙ 0 ∙ share

read it
Heterogeneous Graph Neural Networks for Extractive Document Summarization

As a crucial step in extractive document summarization, learning cross-s...
04/26/2020 ∙ by Danqing Wang, et al. ∙ 0 ∙ share

read it
Robust Covariance Estimation for High-dimensional Compositional Data with Application to Microbial Communities Analysis

Microbial communities analysis is drawing growing attention due to the r...
04/20/2020 ∙ by Yong He, et al. ∙ 0 ∙ share

read it
Extractive Summarization as Text Matching

This paper creates a paradigm shift with regard to the way we build neur...
04/19/2020 ∙ by Ming Zhong, et al. ∙ 0 ∙ share

read it
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study

While neural network-based models have achieved impressive performance o...
01/12/2020 ∙ by Jinlan Fu, et al. ∙ 0 ∙ share

read it
RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving

In this work, we propose an efficient and accurate monocular 3D detectio...
01/10/2020 ∙ by Peixuan Li, et al. ∙ 14 ∙ share

read it
Multi-Scale Self-Attention for Text Classification

In this paper, we introduce the prior knowledge, multi-scale structure, ...
12/02/2019 ∙ by Qipeng Guo, et al. ∙ 0 ∙ share

read it
Learning Sparse Sharing Architectures for Multiple Tasks

Most existing deep multi-task learning models are based on parameter sha...
11/12/2019 ∙ by Tianxiang Sun, et al. ∙ 0 ∙ share

read it
A Closer Look at Data Bias in Neural Extractive Summarization Models

In this paper, we take stock of the current state of summarization datas...
09/30/2019 ∙ by Ming Zhong, et al. ∙ 0 ∙ share

read it
Exploring Domain Shift in Extractive Text Summarization

Although domain shift has been well explored in many NLP applications, i...
08/30/2019 ∙ by Danqing Wang, et al. ∙ 0 ∙ share

read it
Zero-shot Text-to-SQL Learning with Auxiliary Task

Recent years have seen great success in the use of neural seq2seq models...
08/29/2019 ∙ by Shuaichen Chang, et al. ∙ 0 ∙ share

read it
DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks

Variants dropout methods have been designed for the fully-connected laye...
07/25/2019 ∙ by Lin Zehui, et al. ∙ 0 ∙ share

read it
Searching for Effective Neural Extractive Summarization: What Works and What's Next

The recent years have seen remarkable success in the use of deep neural ...
07/08/2019 ∙ by Ming Zhong, et al. ∙ 0 ∙ share

read it
TIGS: An Inference Algorithm for Text Infilling with Gradient Search

Text infilling is defined as a task for filling in the missing part of a...
05/26/2019 ∙ by Dayiheng Liu, et al. ∙ 0 ∙ share

read it
A Combinatorial Algorithm for the Multi-commodity Flow Problem

This paper researches combinatorial algorithms for the multi-commodity f...
04/20/2019 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Star-Transformer

Although the fully-connected attention-based model Transformer has achie...
02/25/2019 ∙ by Qipeng Guo, et al. ∙ 0 ∙ share

read it
Drug cell line interaction prediction

Understanding the phenotypic drug response on cancer cell lines plays a ...
12/28/2018 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Multi-task Learning over Graph Structures

We present two architectures for multi-task learning with neural sequenc...
11/26/2018 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Contextualized Non-local Neural Networks for Sequence Learning

Recently, a large number of neural mechanisms and models have been propo...
11/21/2018 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Meta-Learning Multi-task Communication

In this paper, we describe a general framework: Parameters Read-Write Ne...
10/23/2018 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Exploiting Effective Representations for Chinese Sentiment Analysis Using a Multi-Channel Convolutional Neural Network

Effective representation of a text is critical for various natural langu...
08/08/2018 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Meta Multi-Task Learning for Sequence Modeling

Semantic composition functions have been playing a pivotal role in neura...
02/25/2018 ∙ by Junkun Chen, et al. ∙ 0 ∙ share

read it
Dynamic Compositional Neural Networks over Tree Structure

Tree-structured neural networks have proven to be effective in learning ...
05/11/2017 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Adversarial Multi-task Learning for Text Classification

Neural network models have shown their promising opportunities for multi...
04/19/2017 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Syntax-based Attention Model for Natural Language Inference

Introducing attentional mechanism in neural network is a powerful concep...
07/22/2016 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Modelling Interaction of Sentence Pair with coupled-LSTMs

Recently, there is rising interest in modelling the interactions of two ...
05/18/2016 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it
Recurrent Neural Network for Text Classification with Multi-Task Learning

Neural network based methods have obtained great progress on a variety o...
05/17/2016 ∙ by Pengfei Liu, et al. ∙ 0 ∙ share

read it

Pengfei Liu

Featured Co-authors