b'Yiming Yang'

Improving Neural Model Performance through Natural Language Feedback on Their Explanations

A class of explainable NLP models for reasoning tasks support their deci...
04/18/2021 ∙ by Aman Madaan, et al. ∙ 0 ∙ share

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Improving Hyper-Relational Knowledge Graph Completion

Different from traditional knowledge graphs (KGs) where facts are repres...
04/16/2021 ∙ by Donghan Yu, et al. ∙ 0 ∙ share

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General Robot Dynamics Learning and Gen2Real

Acquiring dynamics is an essential topic in robot learning, but up-to-da...
04/06/2021 ∙ by Dengpeng Xing, et al. ∙ 0 ∙ share

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Meta Back-translation

Back-translation is an effective strategy to improve the performance of ...
02/15/2021 ∙ by Hieu Pham, et al. ∙ 0 ∙ share

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Handling Noisy Labels via One-Step Abductive Multi-Target Learning

Learning from noisy labels is an important concern because of the lack o...
11/25/2020 ∙ by Yongquan Yang, et al. ∙ 13 ∙ share

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Rethinking Transformer-based Set Prediction for Object Detection

DETR is a recently proposed Transformer-based method which views object ...
11/21/2020 ∙ by Zhiqing Sun, et al. ∙ 0 ∙ share

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On the Sentence Embeddings from Pre-trained Language Models

Pre-trained contextual representations like BERT have achieved great suc...
11/02/2020 ∙ by Bohan Li, et al. ∙ 0 ∙ share

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Neural Language Modeling for Contextualized Temporal Graph Generation

This paper presents the first study on using large-scale pre-trained lan...
10/20/2020 ∙ by Aman Madaan, et al. ∙ 0 ∙ share

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JAKET: Joint Pre-training of Knowledge Graph and Language Understanding

Knowledge graphs (KGs) contain rich information about world knowledge, e...
10/02/2020 ∙ by Donghan Yu, et al. ∙ 0 ∙ share

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Unsupervised Parallel Corpus Mining on Web Data

With a large amount of parallel data, neural machine translation systems...
09/18/2020 ∙ by Guokun Lai, et al. ∙ 0 ∙ share

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Kernel Stein Generative Modeling

We are interested in gradient-based Explicit Generative Modeling where s...
07/06/2020 ∙ by Wei-Cheng Chang, et al. ∙ 11 ∙ share

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An EM Approach to Non-autoregressive Conditional Sequence Generation

Autoregressive (AR) models have been the dominating approach to conditio...
06/29/2020 ∙ by Zhiqing Sun, et al. ∙ 0 ∙ share

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Generalized Multi-Relational Graph Convolution Network

Graph Convolutional Networks (GCNs) have received increasing attention i...
06/12/2020 ∙ by Donghan Yu, et al. ∙ 0 ∙ share

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Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing

With the success of language pretraining, it is highly desirable to deve...
06/05/2020 ∙ by Zihang Dai, et al. ∙ 0 ∙ share

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Predicting Performance for Natural Language Processing Tasks

Given the complexity of combinations of tasks, languages, and domains in...
05/02/2020 ∙ by Mengzhou Xia, et al. ∙ 0 ∙ share

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Politeness Transfer: A Tag and Generate Approach

This paper introduces a new task of politeness transfer which involves c...
04/29/2020 ∙ by Aman Madaan, et al. ∙ 0 ∙ share

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Practical Comparable Data Collection for Low-Resource Languages via Images

We propose a method of curating high-quality comparable training data fo...
04/24/2020 ∙ by Aman Madaan, et al. ∙ 0 ∙ share

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Explainable Unsupervised Change-point Detection via Graph Neural Networks

Change-point detection (CPD) aims at detecting the abrupt property chang...
04/24/2020 ∙ by Ruohong Zhang, et al. ∙ 14 ∙ share

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MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices

Natural Language Processing (NLP) has recently achieved great success by...
04/06/2020 ∙ by Zhiqing Sun, et al. ∙ 0 ∙ share

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VIOLIN: A Large-Scale Dataset for Video-and-Language Inference

We introduce a new task, Video-and-Language Inference, for joint multimo...
03/25/2020 ∙ by Jingzhou Liu, et al. ∙ 17 ∙ share

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An Algorithm for Computing a Minimal Comprehensive Gröbner Basis of a Parametric Polynomial System

An algorithm to generate a minimal comprehensive Gröbner basis of a par...
03/17/2020 ∙ by Deepak Kapur, et al. ∙ 0 ∙ share

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Pre-training Tasks for Embedding-based Large-scale Retrieval

We consider the large-scale query-document retrieval problem: given a qu...
02/10/2020 ∙ by Wei-Cheng Chang, et al. ∙ 4 ∙ share

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Graph-Revised Convolutional Network

Graph Convolutional Networks (GCNs) have received increasing attention i...
11/17/2019 ∙ by Donghan Yu, et al. ∙ 0 ∙ share

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A Re-evaluation of Knowledge Graph Completion Methods

Knowledge Graph Completion (KGC) aims at automatically predicting missin...
11/10/2019 ∙ by Zhiqing Sun, et al. ∙ 1 ∙ share

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XL-Editor: Post-editing Sentences with XLNet

While neural sequence generation models achieve initial success for many...
10/19/2019 ∙ by Yong-Siang Shih, et al. ∙ 0 ∙ share

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Active Learning for Graph Neural Networks via Node Feature Propagation

Graph Neural Networks (GNNs) for prediction tasks like node classificati...
10/16/2019 ∙ by Yuexin Wu, et al. ∙ 0 ∙ share

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Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework

Learning multilingual representations of text has proven a successful me...
10/10/2019 ∙ by Zirui Wang, et al. ∙ 0 ∙ share

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A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text

When trained effectively, the Variational Autoencoder (VAE) is both a po...
09/02/2019 ∙ by Bohan Li, et al. ∙ 22 ∙ share

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XLNet: Generalized Autoregressive Pretraining for Language Understanding

With the capability of modeling bidirectional contexts, denoising autoen...
06/19/2019 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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A Modular Deep Learning Approach for Extreme Multi-label Text Classification

Extreme multi-label classification (XMC) aims to assign to an instance t...
05/07/2019 ∙ by Wei-Cheng Chang, et al. ∙ 0 ∙ share

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Implicit Kernel Learning

Kernels are powerful and versatile tools in machine learning and statist...
02/26/2019 ∙ by Chun-Liang Li, et al. ∙ 0 ∙ share

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The ARIEL-CMU Systems for LoReHLT18

This paper describes the ARIEL-CMU submissions to the Low Resource Human...
02/24/2019 ∙ by Aditi Chaudhary, et al. ∙ 0 ∙ share

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Re-examination of the Role of Latent Variables in Sequence Modeling

With latent variables, stochastic recurrent models have achieved state-o...
02/04/2019 ∙ by Zihang Dai, et al. ∙ 0 ∙ share

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An Adversarial Approach to High-Quality, Sentiment-Controlled Neural Dialogue Generation

In this work, we propose a method for neural dialogue response generatio...
01/22/2019 ∙ by Xiang Kong, et al. ∙ 0 ∙ share

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Kernel Change-point Detection with Auxiliary Deep Generative Models

Detecting the emergence of abrupt property changes in time series is a c...
01/18/2019 ∙ by Wei-Cheng Chang, et al. ∙ 0 ∙ share

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Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Transformer networks have a potential of learning longer-term dependency...
01/09/2019 ∙ by Zihang Dai, et al. ∙ 2 ∙ share

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Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning

Training task-completion dialogue agents with reinforcement learning usu...
11/19/2018 ∙ by Yuexin Wu, et al. ∙ 0 ∙ share

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Unsupervised Cross-lingual Transfer of Word Embedding Spaces

Cross-lingual transfer of word embeddings aims to establish the semantic...
09/10/2018 ∙ by Ruochen Xu, et al. ∙ 0 ∙ share

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DARTS: Differentiable Architecture Search

This paper addresses the scalability challenge of architecture search by...
06/24/2018 ∙ by Hanxiao Liu, et al. ∙ 0 ∙ share

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Stochastic WaveNet: A Generative Latent Variable Model for Sequential Data

How to model distribution of sequential data, including but not limited ...
06/15/2018 ∙ by Guokun Lai, et al. ∙ 0 ∙ share

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Likelihood Almost Free Inference Networks

Variational inference for latent variable models is prevalent in various...
11/20/2017 ∙ by Guoqing Zheng, et al. ∙ 0 ∙ share

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Learning Graph Convolution Filters from Data Manifold

Convolution Neural Network (CNN) has gained tremendous success in comput...
10/31/2017 ∙ by Guokun Lai, et al. ∙ 0 ∙ share

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MMD GAN: Towards Deeper Understanding of Moment Matching Network

Generative moment matching network (GMMN) is a deep generative model tha...
05/24/2017 ∙ by Chun-Liang Li, et al. ∙ 0 ∙ share

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Data-driven Random Fourier Features using Stein Effect

Large-scale kernel approximation is an important problem in machine lear...
05/23/2017 ∙ by Wei-Cheng Chang, et al. ∙ 0 ∙ share

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Analogical Inference for Multi-Relational Embeddings

Large-scale multi-relational embedding refers to the task of learning th...
05/06/2017 ∙ by Hanxiao Liu, et al. ∙ 0 ∙ share

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Cross-lingual Distillation for Text Classification

Cross-lingual text classification(CLTC) is the task of classifying docum...
05/05/2017 ∙ by Ruochen Xu, et al. ∙ 0 ∙ share

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RACE: Large-scale ReAding Comprehension Dataset From Examinations

We present RACE, a new dataset for benchmark evaluation of methods in th...
04/15/2017 ∙ by Guokun Lai, et al. ∙ 0 ∙ share

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Co-Clustering for Multitask Learning

This paper presents a new multitask learning framework that learns a sha...
03/03/2017 ∙ by Keerthiram Murugesan, et al. ∙ 0 ∙ share

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Yiming Yang

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