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07/19/2023
PreDiff: Precipitation Nowcasting with Latent Diffusion Models
Earth system forecasting has traditionally relied on complex physical mo...
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05/16/2023
Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation
It has been commonly observed that a teacher model with superior perform...
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05/10/2023
XTab: Cross-table Pretraining for Tabular Transformers
The success of self-supervised learning in computer vision and natural l...
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05/04/2023
Scanpath Prediction in Panoramic Videos via Expected Code Length Minimization
Predicting human scanpaths when exploring panoramic videos is a challeng...
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04/10/2023
A Cheaper and Better Diffusion Language Model with Soft-Masked Noise
Diffusion models that are based on iterative denoising have been recentl...
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04/10/2023
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
This work proposes POMP, a prompt pre-training method for vision-languag...
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03/08/2023
RAF: Holistic Compilation for Deep Learning Model Training
As deep learning is pervasive in modern applications, many deep learning...
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02/16/2023
LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation
Layout-to-image generation refers to the task of synthesizing photo-real...
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02/02/2023
Multimodal Chain-of-Thought Reasoning in Language Models
Large language models (LLMs) have shown impressive performance on comple...
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01/04/2023
Parameter-Efficient Fine-Tuning Design Spaces
Parameter-efficient fine-tuning aims to achieve performance comparable t...
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12/29/2022
Learning Multimodal Data Augmentation in Feature Space
The ability to jointly learn from multiple modalities, such as text, aud...
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12/21/2022
What Makes for Good Tokenizers in Vision Transformer?
The architecture of transformers, which recently witness booming applica...
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12/21/2022
SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning
Pre-trained large language models can efficiently interpolate human-writ...
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12/15/2022
Are Multimodal Models Robust to Image and Text Perturbations?
Multimodal image-text models have shown remarkable performance in the pa...
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10/10/2022
Visual Prompt Tuning for Test-time Domain Adaptation
Models should have the ability to adapt to unseen data during test-time ...
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10/07/2022
Automatic Chain of Thought Prompting in Large Language Models
Large language models (LLMs) can perform complex reasoning by generating...
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08/17/2022
An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework based on Semantic Blocks
Unsupervised summarization methods have achieved remarkable results by i...
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07/12/2022
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
Conventionally, Earth system (e.g., weather and climate) forecasting rel...
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07/04/2022
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition
Existing out-of-distribution (OOD) detection methods are typically bench...
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07/04/2022
Removing Batch Normalization Boosts Adversarial Training
Adversarial training (AT) defends deep neural networks against adversari...
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06/16/2022
MixGen: A New Multi-Modal Data Augmentation
Data augmentation is a necessity to enhance data efficiency in deep lear...
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04/30/2022
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud
Existing general purpose frameworks for gigantic model training, i.e., m...
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04/09/2022
Modeling Multi-Granularity Hierarchical Features for Relation Extraction
Relation extraction is a key task in Natural Language Processing (NLP), ...
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03/24/2022
BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training
Multiple datasets and open challenges for object detection have been int...
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03/22/2022
Task-guided Disentangled Tuning for Pretrained Language Models
Pretrained language models (PLMs) trained on large-scale unlabeled corpu...
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03/22/2022
Learning Confidence for Transformer-based Neural Machine Translation
Confidence estimation aims to quantify the confidence of the model predi...
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12/25/2021
Pseudocylindrical Convolutions for Learned Omnidirectional Image Compression
Although equirectangular projection (ERP) is a convenient form to store ...
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11/04/2021
Benchmarking Multimodal AutoML for Tabular Data with Text Fields
We consider the use of automated supervised learning systems for data ta...
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10/28/2021
Blending Anti-Aliasing into Vision Transformer
The transformer architectures, based on self-attention mechanism and con...
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09/23/2021
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing
We aim to identify how different components in the KD pipeline affect th...
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09/15/2021
Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Context
Embedding based methods are widely used for unsupervised keyphrase extra...
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08/12/2021
Progressive Coordinate Transforms for Monocular 3D Object Detection
Recognizing and localizing objects in the 3D space is a crucial ability ...
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07/29/2021
A Unified Efficient Pyramid Transformer for Semantic Segmentation
Semantic segmentation is a challenging problem due to difficulties in mo...
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06/21/2021
Dive into Deep Learning
This open-source book represents our attempt to make deep learning appro...
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02/04/2021
SelfNorm and CrossNorm for Out-of-Distribution Robustness
Normalization techniques are crucial in stabilizing and accelerating the...
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11/06/2020
Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning
Multi-choice Machine Reading Comprehension (MMRC) aims to select the cor...
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08/26/2020
FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems
Graph neural networks (GNNs) are gaining increasing popularity as a prom...
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07/26/2020
CSER: Communication-efficient SGD with Error Reset
The scalability of Distributed Stochastic Gradient Descent (SGD) is toda...
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06/24/2020
Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes
BERT has recently attracted a lot of attention in natural language under...
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06/04/2020
Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
Modern deep neural networks increasingly make use of features such as dy...
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05/10/2020
Learning Context-Based Non-local Entropy Modeling for Image Compression
The entropy of the codes usually serves as the rate loss in the recent l...
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04/30/2020
Improving Semantic Segmentation via Self-Training
Deep learning usually achieves the best results with complete supervisio...
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04/19/2020
ResNeSt: Split-Attention Networks
While image classification models have recently continued to advance, mo...
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03/13/2020
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data
We introduce AutoGluon-Tabular, an open-source AutoML framework that req...
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07/09/2019
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
We present GluonCV and GluonNLP, the deep learning toolkits for computer...
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07/03/2019
A Unified Optimization Approach for CNN Model Inference on Integrated GPUs
Modern deep learning applications urge to push the model inference takin...
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06/24/2019
Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression
It has long been understood that precisely estimating the probabilistic ...
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04/26/2019
Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources
With an increasing demand for training powers for deep learning algorith...
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04/20/2019
Language Models with Transformers
The Transformer architecture is superior to RNN-based models in computat...
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04/01/2019