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TransGAN: Two Transformers Can Make One Strong GAN
The recent explosive interest on transformers has suggested their potent...
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Self-Progressing Robust Training
Enhancing model robustness under new and even adversarial environments i...
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The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models
The computer vision world has been re-gaining enthusiasm in various pre-...
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Training Stronger Baselines for Learning to Optimize
Learning to optimize (L2O) has gained increasing attention since classic...
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Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning
Interactive Fiction (IF) games with real human-written natural language ...
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Lifelong Object Detection
Recent advances in object detection have benefited significantly from ra...
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The Lottery Ticket Hypothesis for Pre-trained BERT Networks
In natural language processing (NLP), enormous pre-trained models like B...
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Proper Network Interpretability Helps Adversarial Robustness in Classification
Recent works have empirically shown that there exist adversarial example...
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Can 3D Adversarial Logos Cloak Humans?
With the trend of adversarial attacks, researchers attempt to fool train...
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Unsupervised Speech Decomposition via Triple Information Bottleneck
Speech information can be roughly decomposed into four components: langu...
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Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games
We propose the new problem of learning to recover reasoning chains from ...
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Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Pretrained models from self-supervision are prevalently used in fine-tun...
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Invariant Rationalization
Selective rationalization improves neural network interpretability by id...
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Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control
Selective rationalization has become a common mechanism to ensure that p...
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A Game Theoretic Approach to Class-wise Selective Rationalization
Selection of input features such as relevant pieces of text has become a...
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An Efficient and Margin-Approaching Zero-Confidence Adversarial Attack
There are two major paradigms of white-box adversarial attacks that atte...
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Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering
A key challenge of multi-hop question answering (QA) in the open-domain ...
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Few-shot Text Classification with Distributional Signatures
In this paper, we explore meta-learning for few-shot text classification...
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Meta Reasoning over Knowledge Graphs
The ability to reason over learned knowledge is an innate ability for hu...
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AutoGAN: Neural Architecture Search for Generative Adversarial Networks
Neural architecture search (NAS) has witnessed prevailing success in ima...
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TWEETQA: A Social Media Focused Question Answering Dataset
With social media becoming increasingly pop-ular on which lots of news a...
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A Stratified Approach to Robustness for Randomly Smoothed Classifiers
Strong theoretical guarantees of robustness can be given for ensembles o...
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Self-Supervised Learning for Contextualized Extractive Summarization
Existing models for extractive summarization are usually trained from sc...
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Coupled Variational Recurrent Collaborative Filtering
We focus on the problem of streaming recommender system and explore nove...
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Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader
We propose a new end-to-end question answering model, which learns to ag...
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Additive Adversarial Learning for Unbiased Authentication
Authentication is a task aiming to confirm the truth between data instan...
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Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
Natural Language Sentence Matching (NLSM) has gained substantial attenti...
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Zero-Shot Voice Style Transfer with Only Autoencoder Loss
Non-parallel many-to-many voice conversion, as well as zero-shot voice c...
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AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
Non-parallel many-to-many voice conversion, as well as zero-shot voice c...
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Hybrid Reinforcement Learning with Expert State Sequences
Existing imitation learning approaches often require that the complete d...
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Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
Existing entity typing systems usually exploit the type hierarchy provid...
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Sentence Embedding Alignment for Lifelong Relation Extraction
Conventional approaches to relation extraction usually require a fixed s...
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Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers
Most approaches to extraction multiple relations from a paragraph requir...
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Revisiting Pre-training: An Efficient Training Method for Image Classification
The training method of repetitively feeding all samples into a pre-defin...
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Improving Reinforcement Learning Based Image Captioning with Natural Language Prior
Recently, Reinforcement Learning (RL) approaches have demonstrated advan...
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Deriving Machine Attention from Human Rationales
Attention-based models are successful when trained on large amounts of d...
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One-Shot Relational Learning for Knowledge Graphs
Knowledge graphs (KGs) are the key components of various natural languag...
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Matrix Factorization on GPUs with Memory Optimization and Approximate Computing
Matrix factorization (MF) discovers latent features from observations, w...
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Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents
We investigate the task of learning to follow natural language instructi...
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A Co-Matching Model for Multi-choice Reading Comprehension
Multi-choice reading comprehension is a challenging task, which involves...
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Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
As application demands for zeroth-order (gradient-free) optimization acc...
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Diverse Few-Shot Text Classification with Multiple Metrics
We study few-shot learning in natural language domains. Compared to many...
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Image Super-Resolution via Dual-State Recurrent Networks
Advances in image super-resolution (SR) have recently benefited signific...
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Deep Learning Based Speech Beamforming
Multi-channel speech enhancement with ad-hoc sensors has been a challeng...
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Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
A popular recent approach to answering open-domain questions is to first...
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Dilated Recurrent Neural Networks
Learning with recurrent neural networks (RNNs) on long sequences is a no...
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R^3: Reinforced Reader-Ranker for Open-Domain Question Answering
In recent years researchers have achieved considerable success applying ...
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Robust Task Clustering for Deep Many-Task Learning
We investigate task clustering for deep-learning based multi-task and fe...
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Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification
Person Re-Identification (person re-id) is a crucial task as its applica...
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Fast Generation for Convolutional Autoregressive Models
Convolutional autoregressive models have recently demonstrated state-of-...
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