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08/21/2023
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection
Multi-view 3D detection based on BEV (bird-eye-view) has recently achiev...
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07/27/2023
NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection
We present NeRF-Det, a novel method for indoor 3D detection with posed R...
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06/13/2023
SqueezeLLM: Dense-and-Sparse Quantization
Generative Large Language Models (LLMs) have demonstrated remarkable res...
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06/01/2023
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Pre-trained machine learning (ML) models have shown great performance fo...
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05/24/2023
Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts
The explosive growth of language models and their applications have led ...
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04/27/2023
SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection
By identifying four important components of existing LiDAR-camera 3D obj...
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04/27/2023
Quadric Representations for LiDAR Odometry, Mapping and Localization
Current LiDAR odometry, mapping and localization methods leverage point-...
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04/03/2023
Open-Vocabulary Point-Cloud Object Detection without 3D Annotation
The goal of open-vocabulary detection is to identify novel objects based...
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03/13/2023
Scaling Vision-Language Models with Sparse Mixture of Experts
The field of natural language processing (NLP) has made significant stri...
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02/27/2023
Full Stack Optimization of Transformer Inference: a Survey
Recent advances in state-of-the-art DNN architecture design have been mo...
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02/15/2023
Big Little Transformer Decoder
The recent emergence of Large Language Models based on the Transformer a...
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02/08/2023
Q-Diffusion: Quantizing Diffusion Models
Diffusion models have achieved great success in synthesizing diverse and...
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12/30/2022
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
Remote sensing imagery provides comprehensive views of the Earth, where ...
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12/06/2022
CSQ: Growing Mixed-Precision Quantization Scheme with Bi-level Continuous Sparsification
Mixed-precision quantization has been widely applied on deep neural netw...
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11/29/2022
NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers
The complicated architecture and high training cost of vision transforme...
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11/21/2022
Multitask Vision-Language Prompt Tuning
Prompt Tuning, conditioning on task-specific learned prompt vectors, has...
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10/05/2022
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
While recent camera-only 3D detection methods leverage multiple timestep...
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09/14/2022
Analysis of Quantization on MLP-based Vision Models
Quantization is wildly taken as a model compression technique, which obt...
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09/07/2022
Prior Knowledge-Guided Attention in Self-Supervised Vision Transformers
Recent trends in self-supervised representation learning have focused on...
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07/05/2022
Open-Vocabulary 3D Detection via Image-level Class and Debiased Cross-modal Contrastive Learning
Current point-cloud detection methods have difficulty detecting the open...
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06/22/2022
The ArtBench Dataset: Benchmarking Generative Models with Artworks
We introduce ArtBench-10, the first class-balanced, high-quality, cleanl...
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06/20/2022
Domain-Adaptive Text Classification with Structured Knowledge from Unlabeled Data
Domain adaptive text classification is a challenging problem for the lar...
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06/02/2022
Squeezeformer: An Efficient Transformer for Automatic Speech Recognition
The recently proposed Conformer model has become the de facto backbone m...
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04/21/2022
PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map
Deep learning has recently achieved significant progress in trajectory f...
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04/20/2022
K-LITE: Learning Transferable Visual Models with External Knowledge
Recent state-of-the-art computer vision systems are trained from natural...
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03/11/2022
Staged Training for Transformer Language Models
The current standard approach to scaling transformer language models tra...
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10/25/2021
Differentiable NAS Framework and Application to Ads CTR Prediction
Neural architecture search (NAS) methods aim to automatically find the o...
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09/25/2021
Multi-source Few-shot Domain Adaptation
Multi-source Domain Adaptation (MDA) aims to transfer predictive models ...
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09/08/2021
What's Hidden in a One-layer Randomly Weighted Transformer?
We demonstrate that, hidden within one-layer randomly weighted neural ne...
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08/18/2021
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies
Humans are emotional creatures. Multiple modalities are often involved w...
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07/13/2021
How Much Can CLIP Benefit Vision-and-Language Tasks?
Most existing Vision-and-Language (V L) models rely on pre-trained vis...
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07/03/2021
Scene-aware Learning Network for Radar Object Detection
Object detection is essential to safe autonomous or assisted driving. Pr...
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07/02/2021
Learned Token Pruning for Transformers
A major challenge in deploying transformer models is their prohibitive i...
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06/30/2021
Affective Image Content Analysis: Two Decades Review and New Perspectives
Images can convey rich semantics and induce various emotions in viewers....
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06/11/2021
Invariant Information Bottleneck for Domain Generalization
The main challenge for domain generalization (DG) is to overcome the pot...
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06/08/2021
Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets
3D point-clouds and 2D images are different visual representations of th...
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05/30/2021
MLPruning: A Multilevel Structured Pruning Framework for Transformer-based Models
Pruning is an effective method to reduce the memory footprint and comput...
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04/26/2021
HAO: Hardware-aware neural Architecture Optimization for Efficient Inference
Automatic algorithm-hardware co-design for DNN has shown great success i...
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03/31/2021
Q-ASR: Integer-only Zero-shot Quantization for Efficient Speech Recognition
End-to-end neural network models achieve improved performance on various...
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03/25/2021
A Survey of Quantization Methods for Efficient Neural Network Inference
As soon as abstract mathematical computations were adapted to computatio...
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03/23/2021
Self-Supervised Pretraining Improves Self-Supervised Pretraining
While self-supervised pretraining has proven beneficial for many compute...
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03/18/2021
You Only Group Once: Efficient Point-Cloud Processing with Token Representation and Relation Inference Module
3D point-cloud-based perception is a challenging but crucial computer vi...
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01/22/2021
Hessian-Aware Pruning and Optimal Neural Implant
Pruning is an effective method to reduce the memory footprint and FLOPs ...
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01/05/2021
I-BERT: Integer-only BERT Quantization
Transformer based models, like BERT and RoBERTa, have achieved state-of-...
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12/30/2020
Reservoir Transformer
We demonstrate that transformers obtain impressive performance even when...
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12/05/2020
Cross-Domain Sentiment Classification with In-Domain Contrastive Learning
Contrastive learning (CL) has been successful as a powerful representati...
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11/30/2020
Annotation-Efficient Untrimmed Video Action Recognition
Deep learning has achieved great success in recognizing video actions, b...
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11/25/2020
FBWave: Efficient and Scalable Neural Vocoders for Streaming Text-To-Speech on the Edge
Nowadays more and more applications can benefit from edge-based text-to-...
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11/25/2020
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation
Thanks to large-scale labeled training data, deep neural networks (DNNs)...
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11/20/2020