Search Results for author: Wen Shen

Found 16 papers, 3 papers with code

Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models

no code implementations3 May 2023 Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang

This paper aims to prove the emergence of symbolic concepts in well-trained AI models.

Can the Inference Logic of Large Language Models be Disentangled into Symbolic Concepts?

no code implementations3 Apr 2023 Wen Shen, Lei Cheng, Yuxiao Yang, Mingjie Li, Quanshi Zhang

In this paper, we explain the inference logic of large language models (LLMs) as a set of symbolic concepts.


Concept-Level Explanation for the Generalization of a DNN

no code implementations25 Feb 2023 Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang

Therefore, in this paper, we investigate the generalization power of each interactive concept, and we use the generalization power of different interactive concepts to explain the generalization power of the entire DNN.

Defects of Convolutional Decoder Networks in Frequency Representation

no code implementations17 Oct 2022 Ling Tang, Wen Shen, Zhanpeng Zhou, Yuefeng Chen, Quanshi Zhang

In this paper, we prove the representation defects of a cascaded convolutional decoder network, considering the capacity of representing different frequency components of an input sample.

Batch Normalization Is Blind to the First and Second Derivatives of the Loss

no code implementations30 May 2022 Zhanpeng Zhou, Wen Shen, Huixin Chen, Ling Tang, Quanshi Zhang

In this paper, we prove the effects of the BN operation on the back-propagation of the first and second derivatives of the loss.

Why Adversarial Training of ReLU Networks Is Difficult?

no code implementations30 May 2022 Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Jie Ren, Quanshi Zhang

We also prove that adversarial training tends to strengthen the influence of unconfident input samples with large gradient norms in an exponential manner.

Interpreting Representation Quality of DNNs for 3D Point Cloud Processing

no code implementations NeurIPS 2021 Wen Shen, Qihan Ren, Dongrui Liu, Quanshi Zhang

In this paper, we evaluate the quality of knowledge representations encoded in deep neural networks (DNNs) for 3D point cloud processing.


Interpretable Compositional Convolutional Neural Networks

1 code implementation9 Jul 2021 Wen Shen, Zhihua Wei, Shikun Huang, BinBin Zhang, Jiaqi Fan, Ping Zhao, Quanshi Zhang

The reasonable definition of semantic interpretability presents the core challenge in explainable AI.

Automated Segmentation of Brain Gray Matter Nuclei on Quantitative Susceptibility Mapping Using Deep Convolutional Neural Network

no code implementations3 Aug 2020 Chao Chai, Pengchong Qiao, Bin Zhao, Huiying Wang, Guohua Liu, Hong Wu, E Mark Haacke, Wen Shen, Chen Cao, Xinchen Ye, Zhiyang Liu, Shuang Xia

Abnormal iron accumulation in the brain subcortical nuclei has been reported to be correlated to various neurodegenerative diseases, which can be measured through the magnetic susceptibility from the quantitative susceptibility mapping (QSM).

3D-Rotation-Equivariant Quaternion Neural Networks

1 code implementation ECCV 2020 Wen Shen, BinBin Zhang, Shikun Huang, Zhihua Wei, Quanshi Zhang

This paper proposes a set of rules to revise various neural networks for 3D point cloud processing to rotation-equivariant quaternion neural networks (REQNNs).

Verifiability and Predictability: Interpreting Utilities of Network Architectures for Point Cloud Processing

1 code implementation CVPR 2021 Wen Shen, Zhihua Wei, Shikun Huang, BinBin Zhang, Panyue Chen, Ping Zhao, Quanshi Zhang

In this paper, we diagnose deep neural networks for 3D point cloud processing to explore utilities of different intermediate-layer network architectures.

Adversarial Robustness

Information Design in Crowdfunding under Thresholding Policies

no code implementations12 Sep 2017 Wen Shen, Jacob W. Crandall, Ke Yan, Cristina V. Lopes

We introduce a heuristic algorithm to dynamically compute information-disclosure policies for the entrepreneur, followed by an empirical evaluation to demonstrate its competitiveness over the widely-adopted immediate-disclosure policy.

Regulating Highly Automated Robot Ecologies: Insights from Three User Studies

no code implementations7 Aug 2017 Wen Shen, Alanoud Al Khemeiri, Abdulla Almehrezi, Wael Al Enezi, Iyad Rahwan, Jacob W. Crandall

As in the study of political systems in which governments regulate human societies, our studies analyze how interactions between HARE and regulators are impacted by regulatory power and individual (robot or agent) autonomy.

An Online Mechanism for Ridesharing in Autonomous Mobility-on-Demand Systems

no code implementations7 Mar 2016 Wen Shen, Cristina V. Lopes, Jacob W. Crandall

With proper management, Autonomous Mobility-on-Demand (AMoD) systems have great potential to satisfy the transport demands of urban populations by providing safe, convenient, and affordable ridesharing services.


Managing Autonomous Mobility on Demand Systems for Better Passenger Experience

no code implementations9 Jul 2015 Wen Shen, Cristina Lopes

Autonomous mobility on demand systems, though still in their infancy, have very promising prospects in providing urban population with sustainable and safe personal mobility in the near future.

Autonomous Vehicles Scheduling

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