345 citations · 719 across the 23 of their papers we have counts for
6 papers · 1 filter
LLaSM: Large Language and Speech Model
Yu Shu, Siwei Dong, Guangyao Chen +5
Multi-modal large language models have garnered significant interest recently. Though, most of the works focus on vision-language multi-modal models providing strong capabilities i…
AutoAgents: A Framework for Automatic Agent Generation
Guangyao Chen, Siwei Dong, Yu Shu +5
Large language models (LLMs) have enabled remarkable advances in automated task-solving with multi-agent systems. However, most existing LLM-based multi-agent approaches rely on pr…
Learning Sparse Neural Networks with Identity Layers
Mingjian Ni, Guangyao Chen, Xiawu Zheng +3
The sparsity of Deep Neural Networks is well investigated to maximize the performance and reduce the size of overparameterized networks as possible. Existing methods focus on pruni…
Picking Up Quantization Steps for Compressed Image Classification
Li Ma, Peixi Peng, Guangyao Chen +3
The sensitivity of deep neural networks to compressed images hinders their usage in many real applications, which means classification networks may fail just after taking a screens…
Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey
Xiao Wang, Guangyao Chen, Guangwu Qian +5
With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as BERT, ViT, GPT, etc. Inspired by the success of these models in single domains…
Training Full Spike Neural Networks via Auxiliary Accumulation Pathway
Guangyao Chen, Peixi Peng, Guoqi Li +1
Due to the binary spike signals making converting the traditional high-power multiply-accumulation (MAC) into a low-power accumulation (AC) available, the brain-inspired Spiking Ne…