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09/10/2023
Boosting Unsupervised Contrastive Learning Using Diffusion-Based Data Augmentation From Scratch
Unsupervised contrastive learning methods have recently seen significant...
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08/30/2023
Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency
Large-scale language models have become increasingly challenging and exp...
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08/21/2023
Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification
Unsupervised domain adaptive person re-identification (Re-ID) methods al...
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08/21/2023
Dataset Quantization
State-of-the-art deep neural networks are trained with large amounts (mi...
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07/05/2023
CAME: Confidence-guided Adaptive Memory Efficient Optimization
Adaptive gradient methods, such as Adam and LAMB, have demonstrated exce...
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05/26/2023
Summarizing Stream Data for Memory-Restricted Online Continual Learning
Replay-based methods have proved their effectiveness on online continual...
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05/22/2023
Are Large Language Models Good Evaluators for Abstractive Summarization?
Human evaluations are often required for abstractive summary evaluations...
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05/19/2023
Monte-Carlo Search for an Equilibrium in Dec-POMDPs
Decentralized partially observable Markov decision processes (Dec-POMDPs...
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05/15/2023
A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document Summarization
Pre-trained language models (PLMs) have accomplished impressive achievem...
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03/22/2023
BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistency
As one of the most fundamental techniques in multimodal learning, cross-...
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03/12/2023
Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models
Continual learning (CL) can help pre-trained vision-language models effi...
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03/08/2023
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
Data pruning aims to obtain lossless performances as training on the ori...
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03/08/2023
DiM: Distilling Dataset into Generative Model
Dataset distillation reduces the network training cost by synthesizing s...
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03/06/2023
CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame
Various recent methods attempt to implement rotation-invariant 3D deep l...
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02/28/2023
DREAM: Efficient Dataset Distillation by Representative Matching
Dataset distillation aims to generate small datasets with little informa...
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02/27/2023
Robust Robot Planning for Human-Robot Collaboration
In human-robot collaboration, the objectives of the human are often unkn...
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02/06/2023
Colossal-Auto: Unified Automation of Parallelization and Activation Checkpoint for Large-scale Models
In recent years, large-scale models have demonstrated state-of-the-art p...
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01/20/2023
ATP: Adaptive Tensor Parallelism for Foundation Models
Foundation models have impressive performance and generalization capabil...
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01/01/2023
MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
New architecture GPUs like A100 are now equipped with multi-instance GPU...
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12/30/2022
On the Inconsistencies of Conditionals Learned by Masked Language Models
Learning to predict masked tokens in a sequence has been shown to be a p...
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12/29/2022
GPTR: Gestalt-Perception Transformer for Diagram Object Detection
Diagram object detection is the key basis of practical applications such...
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12/10/2022
Elixir: Train a Large Language Model on a Small GPU Cluster
In recent years, the number of parameters of one deep learning (DL) mode...
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11/24/2022
Go Beyond Point Pairs: A General and Accurate Sim2Real Object Pose Voting Method with Efficient Online Synthetic Training
Object pose estimation is an important topic in 3D vision. Though most c...
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11/24/2022
One-Shot General Object Localization
This paper presents a general one-shot object localization algorithm cal...
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10/26/2022
SentBS: Sentence-level Beam Search for Controllable Summarization
A wide range of control perspectives have been explored in controllable ...
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09/06/2022
EnergonAI: An Inference System for 10-100 Billion Parameter Transformer Models
Large transformer models display promising performance on a wide range o...
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08/18/2022
Prompt Vision Transformer for Domain Generalization
Though vision transformers (ViTs) have exhibited impressive ability for ...
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08/08/2022
A Frequency-aware Software Cache for Large Recommendation System Embeddings
Deep learning recommendation models (DLRMs) have been widely applied in ...
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07/19/2022
Active-Learning-as-a-Service: An Efficient MLOps System for Data-Centric AI
The success of today's AI applications requires not only model training ...
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05/28/2022
Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors
Domain Adaptation of Black-box Predictors (DABP) aims to learn a model o...
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05/23/2022
FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders
Face recognition, as one of the most successful applications in artifici...
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04/30/2022
Reliable Label Correction is a Good Booster When Learning with Extremely Noisy Labels
Learning with noisy labels has aroused much research interest since data...
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03/07/2022
CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild
In this paper, we tackle the problem of category-level 9D pose estimatio...
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03/05/2022
Towards Efficient and Scalable Sharpness-Aware Minimization
Recently, Sharpness-Aware Minimization (SAM), which connects the geometr...
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03/03/2022
CAFE: Learning to Condense Dataset by Aligning Features
Dataset condensation aims at reducing the network training effort throug...
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03/02/2022
FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours
Protein structure prediction is an important method for understanding ge...
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02/07/2022
Crafting Better Contrastive Views for Siamese Representation Learning
Recent self-supervised contrastive learning methods greatly benefit from...
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11/21/2021
Understanding Pixel-level 2D Image Semantics with 3D Keypoint Knowledge Engine
Pixel-level 2D object semantic understanding is an important topic in co...
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10/28/2021
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
The Transformer architecture has improved the performance of deep learni...
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10/14/2021
MReD: A Meta-Review Dataset for Controllable Text Generation
When directly using existing text generation datasets for controllable g...
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09/17/2021
Solving infinite-horizon Dec-POMDPs using Finite State Controllers within JESP
This paper looks at solving collaborative planning problems formalized a...
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08/12/2021
PatrickStar: Parallel Training of Pre-trained Models via a Chunk-based Memory Management
The pre-trained model (PTM) is revolutionizing Artificial intelligence (...
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08/08/2021
Online Evolutionary Batch Size Orchestration for Scheduling Deep Learning Workloads in GPU Clusters
Efficient GPU resource scheduling is essential to maximize resource util...
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06/01/2021
Concurrent Adversarial Learning for Large-Batch Training
Large-batch training has become a commonly used technique when training ...
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05/30/2021
2.5-dimensional distributed model training
Data parallelism does a good job in speeding up the training. However, w...
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05/30/2021
Maximizing Parallelism in Distributed Training for Huge Neural Networks
The recent Natural Language Processing techniques have been refreshing t...
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05/21/2021
An Efficient Training Approach for Very Large Scale Face Recognition
Face recognition has achieved significant progress in deep-learning era ...
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04/12/2021
An Efficient 2D Method for Training Super-Large Deep Learning Models
Huge neural network models have shown unprecedented performance in real-...
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03/19/2021
Skeleton Merger: an Unsupervised Aligned Keypoint Detector
Detecting aligned 3D keypoints is essential under many scenarios such as...
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02/24/2021
