9 citations · 21 across the 5 of their papers we have counts for
7 papers
ChainPrune: Evaluating and Reducing Redundancy in Long Chain-of-Thought Reasoning
Weihang Pan, Zhengxu Yu, Yuxiang Zhang +5
Chain-of-Thought (CoT) reasoning has significantly enhanced the multi-step problem-solving capabilities of large language models (LLMs) by introducing explicit intermediate reasoni…
TokenSqueeze: Performance-Preserving Compression for Reasoning LLMs
Yuxiang Zhang, Zhengxu Yu, Weihang Pan +5
Emerging reasoning LLMs such as OpenAI-o1 and DeepSeek-R1 have achieved strong performance on complex reasoning tasks by generating long chain-of-thought (CoT) traces. However, the…
Lidar Point Cloud Guided Monocular 3D Object Detection
Liang Peng, Fei Liu, Zhengxu Yu +5
Monocular 3D object detection is a challenging task in the self-driving and computer vision community. As a common practice, most previous works use manually annotated 3D box label…
Apparel-invariant Feature Learning for Apparel-changed Person Re-identification
Zhengxu Yu, Yilun Zhao, Bin Hong +5
With the rise of deep learning methods, person Re-Identification (ReID) performance has been improved tremendously in many public datasets. However, most public ReID datasets are c…
Out-of-distribution Generalization via Partial Feature Decorrelation
Xin Guo, Zhengxu Yu, Chao Xiang +5
Most deep-learning-based image classification methods assume that all samples are generated under an independent and identically distributed (IID) setting. However, out-of-distribu…
PI-RCNN: An Efficient Multi-sensor 3D Object Detector with Point-based Attentive Cont-conv Fusion Module
Liang Xie, Chao Xiang, Zhengxu Yu +4
LIDAR point clouds and RGB-images are both extremely essential for 3D object detection. So many state-of-the-art 3D detection algorithms dedicate in fusing these two types of data…
Progressive Transfer Learning
Zhengxu Yu, Dong Shen, Zhongming Jin +3
Model fine-tuning is a widely used transfer learning approach in person Re-identification (ReID) applications, which fine-tuning a pre-trained feature extraction model into the tar…