119 citations · 262 across the 9 of their papers we have counts for
9 papers
NOAH: Learning Pairwise Object Category Attentions for Image Classification
Chao Li, Aojun Zhou, Anbang Yao
A modern deep neural network (DNN) for image classification tasks typically consists of two parts: a backbone for feature extraction, and a head for feature encoding and class pred…
NODI: Out-Of-Distribution Detection with Noise from Diffusion
Jingqiu Zhou, Aojun Zhou, Hongsheng Li
Out-of-distribution (OOD) detection is a crucial part of deploying machine learning models safely. It has been extensively studied with a plethora of methods developed in the liter…
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
Ke Wang, Houxing Ren, Aojun Zhou +7
The recently released GPT-4 Code Interpreter has demonstrated remarkable proficiency in solving challenging math problems, primarily attributed to its ability to seamlessly reason…
Efficient N:M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design
Chao Fang, Wei Sun, Aojun Zhou +1
Sparse training is one of the promising techniques to reduce the computational cost of DNNs while retaining high accuracy. In particular, N:M fine-grained structured sparsity, wher…
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
Aojun Zhou, Ke Wang, Zimu Lu +8
Recent progress in large language models (LLMs) like GPT-4 and PaLM-2 has brought significant advancements in addressing math reasoning problems. In particular, OpenAI's latest ver…
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
Peng Gao, Jiaming Han, Renrui Zhang +9
How to efficiently transform large language models (LLMs) into instruction followers is recently a popular research direction, while training LLM for multi-modal reasoning remains…