b'Yu Meng'

research

∙ 05/20/2023

Patton: Language Model Pretraining on Text-Rich Networks

A real-world text corpus sometimes comprises not only text documents but...

0 Bowen Jin, et al. ∙

research

∙ 02/21/2023

Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks

Edges in many real-world social/information networks are associated with...

0 Bowen Jin, et al. ∙

research

∙ 02/07/2023

The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study

Due to the exponential growth of scientific publications on the Web, the...

0 Yu Zhang, et al. ∙

research

∙ 02/04/2023

Representation Deficiency in Masked Language Modeling

Masked Language Modeling (MLM) has been one of the most prominent approa...

0 Yu Meng, et al. ∙

research

∙ 12/12/2022

Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts

Instead of mining coherent topics from a given text corpus in a complete...

0 Yu Zhang, et al. ∙

research

∙ 11/06/2022

Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning

Recent studies have revealed the intriguing few-shot learning ability of...

0 Yu Meng, et al. ∙

research

∙ 06/28/2022

Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation

We study the problem of few-shot Fine-grained Entity Typing (FET), where...

0 Jiaxin Huang, et al. ∙

research

∙ 05/04/2022

Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds

Discovering latent topics from text corpora has been studied for decades...

0 Yu Zhang, et al. ∙

research

∙ 04/07/2022

Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators

We present a new framework AMOS that pretrains text encoders with an Adv...

0 Yu Meng, et al. ∙

research

∙ 02/09/2022

Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations

Topic models have been the prominent tools for automatic topic discovery...

0 Yu Meng, et al. ∙

research

∙ 02/09/2022

Generating Training Data with Language Models: Towards Zero-Shot Language Understanding

Pretrained language models (PLMs) have demonstrated remarkable performan...

0 Yu Meng, et al. ∙

research

∙ 12/13/2021

Pedestrian Trajectory Prediction via Spatial Interaction Transformer Network

As a core technology of the autonomous driving system, pedestrian trajec...

0 Tong Su, et al. ∙

research

∙ 11/07/2021

MotifClass: Weakly Supervised Text Classification with Higher-order Metadata Information

We study the problem of weakly supervised text classification, which aim...

0 Yu Zhang, et al. ∙

research

∙ 10/17/2021

Fine-Grained Opinion Summarization with Minimal Supervision

Opinion summarization aims to profile a target by extracting opinions fr...

0 Suyu Ge, et al. ∙

research

∙ 09/10/2021

Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

We study the problem of training named entity recognition (NER) models u...

0 Yu Meng, et al. ∙

research

∙ 05/28/2021

UCPhrase: Unsupervised Context-aware Quality Phrase Tagging

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

0 Xiaotao Gu, et al. ∙

research

∙ 02/16/2021

COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

We present COCO-LM, a new self-supervised learning framework that pretra...

0 Yu Meng, et al. ∙

research

∙ 10/26/2020

Hierarchical Metadata-Aware Document Categorization under Weak Supervision

Categorizing documents into a given label hierarchy is intuitively appea...

0 Yu Zhang, et al. ∙

research

∙ 10/14/2020

Text Classification Using Label Names Only: A Language Model Self-Training Approach

Current text classification methods typically require a good number of h...

0 Yu Meng, et al. ∙

research

∙ 10/13/2020

CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring

Taxonomy is not only a fundamental form of knowledge representation, but...

0 Jiaxin Huang, et al. ∙

research

∙ 10/13/2020

Weakly-Supervised Aspect-Based Sentiment Analysis via Joint Aspect-Sentiment Topic Embedding

Aspect-based sentiment analysis of review texts is of great value for un...

0 Jiaxin Huang, et al. ∙

research

∙ 07/18/2020

Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding

Mining a set of meaningful topics organized into a hierarchy is intuitiv...

1 Yu Meng, et al. ∙

research

∙ 05/01/2020

Minimally Supervised Categorization of Text with Metadata

Document categorization, which aims to assign a topic label to each docu...

0 Yu Zhang, et al. ∙

research

∙ 11/21/2019

Separate and Attend in Personal Email Search

In personal email search, user queries often impose different requiremen...

0 Yu Meng, et al. ∙

research

∙ 11/04/2019

Spherical Text Embedding

Unsupervised text embedding has shown great power in a wide range of NLP...

0 Yu Meng, et al. ∙

research

∙ 10/16/2019

HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories

GitHub has become an important platform for code sharing and scientific ...

11 Yu Zhang, et al. ∙

research

∙ 09/17/2019

A Data-Center FPGA Acceleration Platform for Convolutional Neural Networks

Intensive computation is entering data centers with multiple workloads o...

10 Xiaoyu Yu, et al. ∙

research

∙ 08/20/2019

CatE: Category-Name GuidedWord Embedding

Unsupervised word embedding has benefited a wide spectrum of NLP tasks d...

0 Yu Meng, et al. ∙

research

∙ 12/29/2018

Weakly-Supervised Hierarchical Text Classification

Hierarchical text classification, which aims to classify text documents ...

0 Yu Meng, et al. ∙

research

∙ 09/02/2018

Weakly-Supervised Neural Text Classification

Deep neural networks are gaining increasing popularity for the classic t...

0 Yu Meng, et al. ∙

research

∙ 04/21/2018

Monocular Vision-based Vehicle Localization Aided by Fine-grained Classification

Monocular camera systems are prevailing in intelligent transportation sy...

0 Shuaijun Li, et al. ∙

Yu Meng

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