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07/12/2023
Unified Molecular Modeling via Modality Blending
Self-supervised molecular representation learning is critical for molecu...
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07/11/2023
Generative Pretraining in Multimodality
We present Emu, a Transformer-based multimodal foundation model, which c...
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05/25/2023
PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning
Offline-to-online reinforcement learning (RL), by combining the benefits...
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04/17/2023
K-means Clustering Based Feature Consistency Alignment for Label-free Model Evaluation
The label-free model evaluation aims to predict the model performance on...
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03/15/2023
SpiderMesh: Spatial-aware Demand-guided Recursive Meshing for RGB-T Semantic Segmentation
For semantic segmentation in urban scene understanding, RGB cameras alon...
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03/07/2023
Calibration-free BEV Representation for Infrastructure Perception
Effective BEV object detection on infrastructure can greatly improve tra...
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02/20/2023
Metropolis Theorem and Its Applications in Single Image Detail Enhancement
Traditional image detail enhancement is local filter-based or global fil...
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02/03/2023
Mind the Gap: Offline Policy Optimization for Imperfect Rewards
Reward function is essential in reinforcement learning (RL), serving as ...
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12/29/2022
OrthoGAN:High-Precision Image Generation for Teeth Orthodontic Visualization
Patients take care of what their teeth will be like after the orthodonti...
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05/23/2022
Distance-Sensitive Offline Reinforcement Learning
In offline reinforcement learning (RL), one detrimental issue to policy ...
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08/12/2021
TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims to transfer the knowledge lear...
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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...
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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...
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04/23/2021
Playing Lottery Tickets with Vision and Language
Large-scale transformer-based pre-training has recently revolutionized v...
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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...
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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...
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03/30/2021
The Elastic Lottery Ticket Hypothesis
Lottery Ticket Hypothesis raises keen attention to identifying sparse tr...
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03/22/2021
Adversarial Feature Augmentation and Normalization for Visual Recognition
Recent advances in computer vision take advantage of adversarial data au...
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03/22/2021
Space Mapping of Spline Spaces over Hierarchical T-meshes
In this paper, we construct a bijective mapping between a biquadratic sp...
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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...
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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...
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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...
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12/31/2020
EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets
Deep, heavily overparameterized language models such as BERT, XLNet and ...
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12/15/2020
Wasserstein Contrastive Representation Distillation
The primary goal of knowledge distillation (KD) is to encapsulate the in...
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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...
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10/07/2020
Cross-Thought for Sentence Encoder Pre-training
In this paper, we propose Cross-Thought, a novel approach to pre-trainin...
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10/06/2020
Multi-Fact Correction in Abstractive Text Summarization
Pre-trained neural abstractive summarization systems have dominated extr...
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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 ...
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10/03/2020
Efficient Robust Training via Backward Smoothing
Adversarial training is so far the most effective strategy in defending ...
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09/29/2020
Contrastive Distillation on Intermediate Representations for Language Model Compression
Existing language model compression methods mostly use a simple L2 loss ...
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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...
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09/10/2020
Accelerating Real-Time Question Answering via Question Generation
Existing approaches to real-time question answering (RTQA) rely on learn...
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09/10/2020
FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding
Large-scale cross-lingual language models (LM), such as mBERT, Unicoder ...
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06/26/2020
Graph Optimal Transport for Cross-Domain Alignment
Cross-domain alignment between two sets of entities (e.g., objects in an...
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06/21/2020
Adaptive Learning Rates with Maximum Variation Averaging
Adaptive gradient methods such as RMSProp and Adam use exponential movin...
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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...
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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...
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05/01/2020
HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training
We present HERO, a Hierarchical EncodeR for Omni-representation learning...
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04/30/2020
Contextual Text Style Transfer
We introduce a new task, Contextual Text Style Transfer - translating a ...
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04/30/2020
APo-VAE: Text Generation in Hyperbolic Space
Natural language often exhibits inherent hierarchical structure ingraine...
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03/26/2020
BachGAN: High-Resolution Image Synthesis from Salient Object Layout
We propose a new task towards more practical application for image gener...
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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...
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03/19/2020
Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection
Unsupervised domain adaptation (UDA) has achieved unprecedented success ...
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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...
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11/10/2019
Distilling the Knowledge of BERT for Text Generation
Large-scale pre-trained language model, such as BERT, has recently achie...
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11/09/2019
Hierarchical Graph Network for Multi-hop Question Answering
In this paper, we present Hierarchical Graph Network (HGN) for multi-hop...
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11/01/2019
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
We present a large, tunable neural conversational response generation mo...
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10/30/2019
Discourse-Aware Neural Extractive Model for Text Summarization
Recently BERT has been adopted in state-of-the-art text summarization mo...
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10/08/2019
Meta Module Network for Compositional Visual Reasoning
There are two main lines of research on visual reasoning: neural module ...
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09/25/2019
