b'Jingbo Shang'

research

∙ 05/25/2022

Intermediate Training on Question Answering Datasets Improves Generative Data Augmentation

Manually annotating datasets requires domain experts to read through man...

Dheeraj Mekala, et al. ∙

research

∙ 05/25/2022

LOPS: Learning Order Inspired Pseudo-Label Selection for Weakly Supervised Text Classification

Weakly supervised text classification methods typically train a deep neu...

Dheeraj Mekala, et al. ∙

research

∙ 05/25/2022

Fine-grained Contrastive Learning for Relation Extraction

Recent relation extraction (RE) works have shown encouraging improvement...

William Hogan, et al. ∙

research

∙ 05/24/2022

WeDef: Weakly Supervised Backdoor Defense for Text Classification

Existing backdoor defense methods are only effective for limited trigger...

Lesheng Jin, et al. ∙

research

∙ 05/24/2022

Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity Recognition

Fine-tuning pre-trained language models has recently become a common pra...

Zihan Wang, et al. ∙

research

∙ 04/29/2022

OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision

Automatic extraction of product attributes from their textual descriptio...

Xinyang Zhang, et al. ∙

research

∙ 02/27/2022

UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining

High-quality phrase representations are essential to finding topics and ...

Jiacheng Li, et al. ∙

research

∙ 10/07/2021

Double Descent in Adversarial Training: An Implicit Label Noise Perspective

Here, we show that the robust overfitting shall be viewed as the early p...

Chengyu Dong, et al. ∙

research

∙ 09/22/2021

Coarse2Fine: Fine-grained Text Classification on Coarsely-grained Annotated Data

Existing text classification methods mainly focus on a fixed label set, ...

Dheeraj Mekala, et al. ∙

research

∙ 09/22/2021

BFClass: A Backdoor-free Text Classification Framework

Backdoor attack introduces artificial vulnerabilities into the model by ...

Zichao Li, et al. ∙

research

∙ 08/26/2021

LayoutReader: Pre-training of Text and Layout for Reading Order Detection

Reading order detection is the cornerstone to understanding visually-ric...

Zilong Wang, et al. ∙

research

∙ 07/05/2021

Weakly Supervised Named Entity Tagging with Learnable Logical Rules

We study the problem of building entity tagging systems by using a few r...

Jiacheng Li, et al. ∙

research

∙ 05/28/2021

UCPhrase: Unsupervised Context-aware Quality Phrase Tagging

Identifying and understanding quality phrases from context is a fundamen...

Xiaotao Gu, et al. ∙

research

∙ 04/18/2021

Unsupervised Deep Keyphrase Generation

Keyphrase generation aims to summarize long documents with a collection ...

Xianjie Shen, et al. ∙

research

∙ 04/18/2021

News Meets Microblog: Hashtag Annotation via Retriever-Generator

Hashtag annotation for microblog posts has been recently formulated as a...

Xiuwen Zheng, et al. ∙

research

∙ 04/18/2021

"Average" Approximates "First Principal Component"? An Empirical Analysis on Representations from Neural Language Models

Contextualized representations based on neural language models have furt...

Zihan Wang, et al. ∙

research

∙ 02/23/2021

Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks

Text categorization is an essential task in Web content analysis. Consid...

Xinyang Zhang, et al. ∙

research

∙ 02/15/2021

Data Profiling for Adversarial Training: On the Ruin of Problematic Data

Multiple intriguing problems hover in adversarial training, including ro...

Chengyu Dong, et al. ∙

research

∙ 01/01/2021

Sensei: Self-Supervised Sensor Name Segmentation

A sensor name, typically an alphanumeric string, encodes the key context...

Jiaman Wu, et al. ∙

research

∙ 10/24/2020

X-Class: Text Classification with Extremely Weak Supervision

In this paper, we explore to conduct text classification with extremely ...

Zihan Wang, et al. ∙

research

∙ 10/15/2020

Overfitting or Underfitting? Understand Robustness Drop in Adversarial Training

Our goal is to understand why the robustness drops after conducting adve...

Zichao Li, et al. ∙

research

∙ 04/30/2020

User-Guided Aspect Classification for Domain-Specific Texts

Aspect classification, identifying aspects of text segments, facilitates...

Peiran Li, et al. ∙

research

∙ 10/17/2019

SetExpan: Corpus-Based Set Expansion via Context Feature Selection and Rank Ensemble

Corpus-based set expansion (i.e., finding the "complete" set of entities...

Jiaming Shen, et al. ∙

research

∙ 10/10/2019

FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams

Set expansion aims to expand a small set of seed entities into a complet...

Wanzheng Zhu, et al. ∙

research

∙ 09/03/2019

CrossWeigh: Training Named Entity Tagger from Imperfect Annotations

Everyone makes mistakes. So do human annotators when curating labels for...

Zihan Wang, et al. ∙

research

∙ 08/14/2019

Raw-to-End Name Entity Recognition in Social Media

Taking word sequences as the input, typical named entity recognition (NE...

Liyuan Liu, et al. ∙

research

∙ 09/10/2018

Learning Named Entity Tagger using Domain-Specific Dictionary

Recent advances in deep neural models allow us to build reliable named e...

Jingbo Shang, et al. ∙

research

∙ 04/29/2018

Entity Set Search of Scientific Literature: An Unsupervised Ranking Approach

Literature search is critical for any scientific research. Different fro...

Jiaming Shen, et al. ∙

research

∙ 04/26/2018

Open Information Extraction with Global Structure Constraints

Extracting entities and their relations from text is an important task f...

Qi Zhu, et al. ∙

research

∙ 04/26/2018

Integrating Local Context and Global Cohesiveness for Open Information Extraction

Extracting entities and their relations from text is an important task f...

Qi Zhu, et al. ∙

research

∙ 04/20/2018

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

Many efforts have been made to facilitate natural language processing ta...

Liyuan Liu, et al. ∙

research

∙ 02/21/2018

Investigating Rumor News Using Agreement-Aware Search

In recent years, rumor news has been generated by humans as well as robo...

Jingbo Shang, et al. ∙

research

∙ 01/30/2018

Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning

Motivation: Biomedical named entity recognition (BioNER) is the most fun...

Xuan Wang, et al. ∙

research

∙ 09/19/2017

An Attention-based Collaboration Framework for Multi-View Network Representation Learning

Learning distributed node representations in networks has been attractin...

Meng Qu, et al. ∙

research

∙ 09/13/2017

Empower Sequence Labeling with Task-Aware Neural Language Model

Linguistic sequence labeling is a general modeling approach that encompa...

Liyuan Liu, et al. ∙

research

∙ 03/13/2017

MetaPAD: Meta Pattern Discovery from Massive Text Corpora

Mining textual patterns in news, tweets, papers, and many other kinds of...

Meng Jiang, et al. ∙

research

∙ 02/15/2017

Automated Phrase Mining from Massive Text Corpora

As one of the fundamental tasks in text analysis, phrase mining aims at ...

Jingbo Shang, et al. ∙

research

∙ 10/31/2016

DPPred: An Effective Prediction Framework with Concise Discriminative Patterns

In the literature, two series of models have been proposed to address pr...

Jingbo Shang, et al. ∙

research

∙ 10/22/2014

A Parallel and Efficient Algorithm for Learning to Match

Many tasks in data mining and related fields can be formalized as matchi...

Jingbo Shang, et al. ∙

Jingbo Shang

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