Aojun Zhou | DeepAI

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∙ 08/15/2023

Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification

Recent progress in large language models (LLMs) like GPT-4 and PaLM-2 ha...

0 Aojun Zhou, et al. ∙

∙ 07/03/2023

JourneyDB: A Benchmark for Generative Image Understanding

While recent advancements in vision-language models have revolutionized ...

0 Junting Pan, et al. ∙

∙ 04/28/2023

LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

How to efficiently transform large language models (LLMs) into instructi...

1 Peng Gao, et al. ∙

∙ 04/03/2023

Not All Features Matter: Enhancing Few-shot CLIP with Adaptive Prior Refinement

The popularity of Contrastive Language-Image Pre-training (CLIP) has pro...

0 Xiangyang Zhu, et al. ∙

∙ 03/28/2023

LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

We present LLaMA-Adapter, a lightweight adaption method to efficiently f...

1 Renrui Zhang, et al. ∙

∙ 03/02/2023

FeatAug-DETR: Enriching One-to-Many Matching for DETRs with Feature Augmentation

One-to-one matching is a crucial design in DETR-like object detection fr...

0 Rongyao Fang, et al. ∙

∙ 09/16/2022

Omni-Dimensional Dynamic Convolution

Learning a single static convolutional kernel in each convolutional laye...

0 Chao Li, et al. ∙

∙ 08/12/2022

An Algorithm-Hardware Co-Optimized Framework for Accelerating N:M Sparse Transformers

The Transformer has been an indispensable staple in deep learning. Howev...

0 Chao Fang, et al. ∙

∙ 01/11/2022

Pyramid Fusion Transformer for Semantic Segmentation

The recently proposed MaskFormer <cit.> gives a refreshed perspective on...

0 Zipeng Qin, et al. ∙

∙ 03/22/2021

Incorporating Convolution Designs into Visual Transformers

Motivated by the success of Transformers in natural language processing ...

0 Kun Yuan, et al. ∙

∙ 02/08/2021

Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Sparsity in Deep Neural Networks (DNNs) has been widely studied to compr...

0 Aojun Zhou, et al. ∙

∙ 10/02/2020

Dynamic Graph: Learning Instance-aware Connectivity for Neural Networks

One practice of employing deep neural networks is to apply the same arch...

1 Kun Yuan, et al. ∙

∙ 08/31/2019

Towards Improving Generalization of Deep Networks via Consistent Normalization

Batch Normalization (BN) was shown to accelerate training and improve ge...

0 Aojun Zhou, et al. ∙

∙ 08/11/2019

HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions

MobileNets, a class of top-performing convolutional neural network archi...

0 Duo Li, et al. ∙

∙ 06/03/2019

Deeply-supervised Knowledge Synergy

Convolutional Neural Networks (CNNs) have become deeper and more complic...

0 Dawei Sun, et al. ∙

∙ 03/29/2019

Second Rethinking of Network Pruning in the Adversarial Setting

It is well known that deep neural networks (DNNs) are vulnerable to adve...

6 Shaokai Ye, et al. ∙

∙ 03/06/2018

Deep Neural Network Compression with Single and Multiple Level Quantization

Network quantization is an effective solution to compress deep neural ne...

0 Yuhui Xu, et al. ∙

∙ 02/10/2017

Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights

This paper presents incremental network quantization (INQ), a novel meth...

0 Aojun Zhou, et al. ∙

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