b'Jingjing Liu'

research

∙ 05/23/2022

Distance-Sensitive Offline Reinforcement Learning

In offline reinforcement learning (RL), one detrimental issue to policy ...

Jianxiong Li, et al. ∙

research

∙ 08/12/2021

TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation

Unsupervised domain adaptation (UDA) aims to transfer the knowledge lear...

Jinyu Yang, et al. ∙

research

∙ 06/08/2021

VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation

Most existing video-and-language (VidL) research focuses on a single dat...

Linjie Li, et al. ∙

research

∙ 06/01/2021

Adversarial VQA: A New Benchmark for Evaluating the Robustness of VQA Models

With large-scale pre-training, the past two years have witnessed signifi...

Linjie Li, et al. ∙

research

∙ 04/23/2021

Playing Lottery Tickets with Vision and Language

Large-scale transformer-based pre-training has recently revolutionized v...

Zhe Gan, et al. ∙

research

∙ 04/01/2021

UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training

Vision-and-language pre-training has achieved impressive success in lear...

Mingyang Zhou, et al. ∙

research

∙ 04/01/2021

CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning

This work concerns video-language pre-training and representation learni...

Luowei Zhou, et al. ∙

research

∙ 03/30/2021

The Elastic Lottery Ticket Hypothesis

Lottery Ticket Hypothesis raises keen attention to identifying sparse tr...

Xiaohan Chen, et al. ∙

research

∙ 03/22/2021

Adversarial Feature Augmentation and Normalization for Visual Recognition

Recent advances in computer vision take advantage of adversarial data au...

Tianlong Chen, et al. ∙

research

∙ 03/22/2021

Space Mapping of Spline Spaces over Hierarchical T-meshes

In this paper, we construct a bijective mapping between a biquadratic sp...

Jingjing Liu, et al. ∙

research

∙ 03/16/2021

LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval

Multimodal pre-training has propelled great advancement in vision-and-la...

Siqi Sun, et al. ∙

research

∙ 02/28/2021

Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly

Training generative adversarial networks (GANs) with limited data genera...

Tianlong Chen, et al. ∙

research

∙ 02/11/2021

Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling

The canonical approach to video-and-language learning (e.g., video quest...

Jie Lei, et al. ∙

research

∙ 12/31/2020

EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets

Deep, heavily overparameterized language models such as BERT, XLNet and ...

Xiaohan Chen, et al. ∙

research

∙ 12/15/2020

Wasserstein Contrastive Representation Distillation

The primary goal of knowledge distillation (KD) is to encapsulate the in...

Liqun Chen, et al. ∙

research

∙ 12/15/2020

A Closer Look at the Robustness of Vision-and-Language Pre-trained Models

Large-scale pre-trained multimodal transformers, such as ViLBERT and UNI...

Linjie Li, et al. ∙

research

∙ 10/07/2020

Cross-Thought for Sentence Encoder Pre-training

In this paper, we propose Cross-Thought, a novel approach to pre-trainin...

Shuohang Wang, et al. ∙

research

∙ 10/06/2020

Multi-Fact Correction in Abstractive Text Summarization

Pre-trained neural abstractive summarization systems have dominated extr...

Yue Dong, et al. ∙

research

∙ 10/05/2020

InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective

Large-scale language models such as BERT have achieved state-of-the-art ...

Boxin Wang, et al. ∙

research

∙ 10/03/2020

Efficient Robust Training via Backward Smoothing

Adversarial training is so far the most effective strategy in defending ...

Jinghui Chen, et al. ∙

research

∙ 09/29/2020

Contrastive Distillation on Intermediate Representations for Language Model Compression

Existing language model compression methods mostly use a simple L2 loss ...

Siqi Sun, et al. ∙

research

∙ 09/13/2020

Cluster-Former: Clustering-based Sparse Transformer for Long-Range Dependency Encoding

Transformer has become ubiquitous in the deep learning field. One of the...

Shuohang Wang, et al. ∙

research

∙ 09/10/2020

Accelerating Real-Time Question Answering via Question Generation

Existing approaches to real-time question answering (RTQA) rely on learn...

Yuwei Fang, et al. ∙

research

∙ 09/10/2020

FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding

Large-scale cross-lingual language models (LM), such as mBERT, Unicoder ...

Yuwei Fang, et al. ∙

research

∙ 06/26/2020

Graph Optimal Transport for Cross-Domain Alignment

Cross-domain alignment between two sets of entities (e.g., objects in an...

Liqun Chen, et al. ∙

research

∙ 06/21/2020

Adaptive Learning Rates with Maximum Variation Averaging

Adaptive gradient methods such as RMSProp and Adam use exponential movin...

Chen Zhu, et al. ∙

research

∙ 06/11/2020

Large-Scale Adversarial Training for Vision-and-Language Representation Learning

We present VILLA, the first known effort on large-scale adversarial trai...

Zhe Gan, et al. ∙

research

∙ 05/15/2020

Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models

Recent Transformer-based large-scale pre-trained models have revolutioni...

Jize Cao, et al. ∙

research

∙ 05/01/2020

HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training

We present HERO, a Hierarchical EncodeR for Omni-representation learning...

Linjie Li, et al. ∙

research

∙ 04/30/2020

Contextual Text Style Transfer

We introduce a new task, Contextual Text Style Transfer - translating a ...

Yu Cheng, et al. ∙

research

∙ 04/30/2020

APo-VAE: Text Generation in Hyperbolic Space

Natural language often exhibits inherent hierarchical structure ingraine...

Shuyang Dai, et al. ∙

research

∙ 03/26/2020

BachGAN: High-Resolution Image Synthesis from Salient Object Layout

We propose a new task towards more practical application for image gener...

Yandong Li, et al. ∙

research

∙ 03/25/2020

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

We introduce a new task, Video-and-Language Inference, for joint multimo...

Jingzhou Liu, et al. ∙

research

∙ 03/19/2020

Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection

Unsupervised domain adaptation (UDA) has achieved unprecedented success ...

Zongxian Li, et al. ∙

research

∙ 01/20/2020

Multi-level Head-wise Match and Aggregation in Transformer for Textual Sequence Matching

Transformer has been successfully applied to many natural language proce...

Shuohang Wang, et al. ∙

research

∙ 11/10/2019

Distilling the Knowledge of BERT for Text Generation

Large-scale pre-trained language model, such as BERT, has recently achie...

Yen-Chun Chen, et al. ∙

research

∙ 11/09/2019

Hierarchical Graph Network for Multi-hop Question Answering

In this paper, we present Hierarchical Graph Network (HGN) for multi-hop...

Yuwei Fang, et al. ∙

research

∙ 11/01/2019

DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation

We present a large, tunable neural conversational response generation mo...

Yizhe Zhang, et al. ∙

research

∙ 10/30/2019

Discourse-Aware Neural Extractive Model for Text Summarization

Recently BERT has been adopted in state-of-the-art text summarization mo...

Jiacheng Xu, et al. ∙

research

∙ 10/08/2019

Meta Module Network for Compositional Visual Reasoning

There are two main lines of research on visual reasoning: neural module ...

Wenhu Chen, et al. ∙

research

∙ 09/25/2019

FreeLB: Enhanced Adversarial Training for Language Understanding

Adversarial training, which minimizes the maximal risk for label-preserv...

Chen Zhu, et al. ∙

research

∙ 09/25/2019

UNITER: Learning UNiversal Image-TExt Representations

Joint image-text embedding is the bedrock for most Vision-and-Language (...

Yen-Chun Chen, et al. ∙

research

∙ 09/11/2019

What Makes A Good Story? Designing Composite Rewards for Visual Storytelling

Previous storytelling approaches mostly focused on optimizing traditiona...

Junjie Hu, et al. ∙

research

∙ 09/11/2019

Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation

Recent unsupervised approaches to domain adaptation primarily focus on m...

Shuyang Dai, et al. ∙

research

∙ 08/25/2019

Patient Knowledge Distillation for BERT Model Compression

Pre-trained language models such as BERT have proven to be highly effect...

Siqi Sun, et al. ∙

research

∙ 08/24/2019

Adversarial Domain Adaptation for Machine Reading Comprehension

In this paper, we focus on unsupervised domain adaptation for Machine Re...

Huazheng Wang, et al. ∙

research

∙ 04/19/2019

A Hybrid Retrieval-Generation Neural Conversation Model

Intelligent personal assistant systems, with either text-based or voice-...

Liu Yang, et al. ∙

research

∙ 04/03/2019

Unsupervised Deep Structured Semantic Models for Commonsense Reasoning

Commonsense reasoning is fundamental to natural language understanding. ...

Shuohang Wang, et al. ∙

research

∙ 03/29/2019

Relation-aware Graph Attention Network for Visual Question Answering

In order to answer semantically-complicated questions about an image, a ...

Linjie Li, et al. ∙

research

∙ 03/06/2019

Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation

We present FAST NAVIGATOR, a general framework for action decoding, whic...

Liyiming Ke, et al. ∙

Jingjing Liu

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