research
∙
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...
share
research
∙
07/03/2023
JourneyDB: A Benchmark for Generative Image Understanding
While recent advancements in vision-language models have revolutionized ...
research
∙
04/28/2023
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
How to efficiently transform large language models (LLMs) into instructi...
research
∙
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...
research
∙
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...
research
∙
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...
research
∙
09/16/2022
Omni-Dimensional Dynamic Convolution
Learning a single static convolutional kernel in each convolutional laye...
research
∙
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...
research
∙
01/11/2022
Pyramid Fusion Transformer for Semantic Segmentation
The recently proposed MaskFormer <cit.> gives a refreshed perspective on...
research
∙
03/22/2021
Incorporating Convolution Designs into Visual Transformers
Motivated by the success of Transformers in natural language processing ...
research
∙
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...
research
∙
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...
research
∙
08/31/2019
Towards Improving Generalization of Deep Networks via Consistent Normalization
Batch Normalization (BN) was shown to accelerate training and improve ge...
research
∙
08/11/2019
HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions
MobileNets, a class of top-performing convolutional neural network archi...
research
∙
06/03/2019
Deeply-supervised Knowledge Synergy
Convolutional Neural Networks (CNNs) have become deeper and more complic...
research
∙
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...
research
∙
03/06/2018
Deep Neural Network Compression with Single and Multiple Level Quantization
Network quantization is an effective solution to compress deep neural ne...
research
∙
02/10/2017