b'Wenpeng Yin'

research

∙ 09/07/2023

All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm

In intent detection tasks, leveraging meaningful semantic information fr...

0 Jiangshu Du, et al. ∙

research

∙ 08/04/2023

Forget Demonstrations, Focus on Learning from Textual Instructions

This work studies a challenging yet more realistic setting for zero-shot...

0 Renze Lou, et al. ∙

research

∙ 03/18/2023

Is Prompt All You Need? No. A Comprehensive and Broader View of Instruction Learning

Task semantics can be expressed by a set of input-to-output examples or ...

0 Renze Lou, et al. ∙

research

∙ 12/07/2022

Robustness of Learning from Task Instructions

Traditional supervised learning mostly works on individual tasks and req...

0 Jiasheng Gu, et al. ∙

research

∙ 12/01/2022

Learning to Select from Multiple Options

Many NLP tasks can be regarded as a selection problem from a set of opti...

0 Jiangshu Du, et al. ∙

research

∙ 10/25/2022

OpenStance: Real-world Zero-shot Stance Detection

Prior studies of zero-shot stance detection identify the attitude of tex...

1 Hanzi Xu, et al. ∙

research

∙ 07/24/2022

Anti-Overestimation Dialogue Policy Learning for Task-Completion Dialogue System

A dialogue policy module is an essential part of task-completion dialogu...

0 Chang Tian, et al. ∙

research

∙ 03/16/2022

ConTinTin: Continual Learning from Task Instructions

The mainstream machine learning paradigms for NLP often work with two un...

0 Wenpeng Yin, et al. ∙

research

∙ 02/12/2022

Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference

The task of ultra-fine entity typing (UFET) seeks to predict diverse and...

0 Bangzheng Li, et al. ∙

research

∙ 12/15/2021

Event Linking: Grounding Event Mentions to Wikipedia

Comprehending an article requires understanding its constituent events. ...

0 Xiaodong Yu, et al. ∙

research

∙ 11/20/2021

Combining Data-driven Supervision with Human-in-the-loop Feedback for Entity Resolution

The distribution gap between training datasets and data encountered in p...

0 Wenpeng Yin, et al. ∙

research

∙ 06/17/2021

DocNLI: A Large-scale Dataset for Document-level Natural Language Inference

Natural language inference (NLI) is formulated as a unified framework fo...

0 Wenpeng Yin, et al. ∙

research

∙ 04/24/2021

Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System

Text classification is usually studied by labeling natural language text...

0 Congying Xia, et al. ∙

research

∙ 04/12/2021

Learning to Synthesize Data for Semantic Parsing

Synthesizing data for semantic parsing has gained increasing attention r...

0 Bailin Wang, et al. ∙

research

∙ 10/24/2020

Paired Representation Learning for Event and Entity Coreference

Co-reference of Events and of Entities are commonly formulated as binary...

0 Xiaodong Yu, et al. ∙

research

∙ 10/06/2020

Universal Natural Language Processing with Limited Annotations: Try Few-shot Textual Entailment as a Start

A standard way to address different NLP problems is by first constructin...

0 Wenpeng Yin, et al. ∙

research

∙ 10/05/2020

Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks

Mixup is the latest data augmentation technique that linearly interpolat...

0 Lichao Sun, et al. ∙

research

∙ 07/19/2020

Meta-learning for Few-shot Natural Language Processing: A Survey

Few-shot natural language processing (NLP) refers to NLP tasks that are ...

0 Wenpeng Yin, et al. ∙

research

∙ 06/17/2020

CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization

The COVID-19 global pandemic has resulted in international efforts to un...

11 Andre Esteva, et al. ∙

research

∙ 02/27/2020

Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT

There is an increasing amount of literature that claims the brittleness ...

0 Lichao Sun, et al. ∙

research

∙ 08/31/2019

Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach

Zero-shot text classification (0Shot-TC) is a challenging NLU problem to...

0 Wenpeng Yin, et al. ∙

research

∙ 08/16/2019

An Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing

Multi-Task Learning (MTL) aims at boosting the overall performance of ea...

0 Jianquan Li, et al. ∙

research

∙ 06/08/2019

Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims

One key consequence of the information revolution is a significant incre...

0 Sihao Chen, et al. ∙

research

∙ 08/10/2018

TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification

Determining whether a given claim is supported by evidence is a fundamen...

0 Wenpeng Yin, et al. ∙

research

∙ 06/12/2018

Term Definitions Help Hypernymy Detection

Existing methods of hypernymy detection mainly rely on statistics over a...

0 Wenpeng Yin, et al. ∙

research

∙ 06/12/2018

Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs

Large scale knowledge graphs (KGs) such as Freebase are generally incomp...

0 Wenpeng Yin, et al. ∙

research

∙ 04/24/2018

End-Task Oriented Textual Entailment via Deep Explorations of Inter-Sentence Interactions

This work deals with SciTail, a natural entailment challenge derived fro...

0 Wenpeng Yin, et al. ∙

research

∙ 04/24/2018

End-Task Oriented Textual Entailment via Deep Exploring Inter-Sentence Interactions

This work deals with SciTail, a natural entailment problem derived from ...

0 Wenpeng Yin, et al. ∙

research

∙ 10/02/2017

Attentive Convolution

In NLP, convolution neural networks (CNNs) have benefited less than recu...

0 Wenpeng Yin, et al. ∙

research

∙ 04/20/2017

Improved Neural Relation Detection for Knowledge Base Question Answering

Relation detection is a core component for many NLP applications includi...

0 Mo Yu, et al. ∙

research

∙ 02/07/2017

Comparative Study of CNN and RNN for Natural Language Processing

Deep neural networks (DNN) have revolutionized the field of natural lang...

0 Wenpeng Yin, et al. ∙

research

∙ 01/09/2017

Task-Specific Attentive Pooling of Phrase Alignments Contributes to Sentence Matching

This work studies comparatively two typical sentence matching tasks: tex...

0 Wenpeng Yin, et al. ∙

research

∙ 06/10/2016

Simple Question Answering by Attentive Convolutional Neural Network

This work focuses on answering single-relation factoid questions over Fr...

0 Wenpeng Yin, et al. ∙

research

∙ 04/23/2016

Why and How to Pay Different Attention to Phrase Alignments of Different Intensities

This work studies comparatively two typical sentence pair classification...

0 Wenpeng Yin, et al. ∙

research

∙ 04/02/2016

Discriminative Phrase Embedding for Paraphrase Identification

This work, concerning paraphrase identification task, on one hand contri...

0 Wenpeng Yin, et al. ∙

research

∙ 04/02/2016

Online Updating of Word Representations for Part-of-Speech Tagging

We propose online unsupervised domain adaptation (DA), which is performe...

0 Wenpeng Yin, et al. ∙

research

∙ 03/15/2016

Multichannel Variable-Size Convolution for Sentence Classification

We propose MVCNN, a convolution neural network (CNN) architecture for se...

0 Wenpeng Yin, et al. ∙

research

∙ 02/13/2016

Attention-Based Convolutional Neural Network for Machine Comprehension

Understanding open-domain text is one of the primary challenges in natur...

0 Wenpeng Yin, et al. ∙

research

∙ 12/16/2015

ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

How to model a pair of sentences is a critical issue in many NLP tasks s...

0 Wenpeng Yin, et al. ∙

research

∙ 08/18/2015

Learning Meta-Embeddings by Using Ensembles of Embedding Sets

Word embeddings -- distributed representations of words -- in deep learn...

0 Wenpeng Yin, et al. ∙

Wenpeng Yin

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