Search Results for author: Rui Chen

Found 75 papers, 26 papers with code

Correlation Preserving Sparse Coding Over Multi-level Dictionaries for Image Denoising

no code implementations23 Dec 2016 Rui Chen, Huizhu Jia, Xiaodong Xie, Wen Gao

In this letter, we propose a novel image denoising method based on correlation preserving sparse coding.

Image Denoising

Bayer Demosaicking Using Optimized Mean Curvature over RGB channels

no code implementations17 May 2017 Rui Chen, Huizhu Jia, Xiange Wen, Xiaodong Xie

Color artifacts of demosaicked images are often found at contours due to interpolation across edges and cross-channel aliasing.

Demosaicking

Noise Level Estimation for Overcomplete Dictionary Learning Based on Tight Asymptotic Bounds

no code implementations9 Dec 2017 Rui Chen, Changshui Yang, Huizhu Jia, Xiaodong Xie

In this letter, we address the problem of estimating Gaussian noise level from the trained dictionaries in update stage.

Dictionary Learning

Extreme Scale FMM-Accelerated Boundary Integral Equation Solver for Wave Scattering

1 code implementation27 Mar 2018 Mustafa Abduljabbar, Mohammed Al Farhan, Noha Al-Harthi, Rui Chen, Rio Yokota, Hakan Bagci, David Keyes

With distributed memory optimizations, on the other hand, we report near-optimal efficiency in the weak scalability study with respect to both the logarithmic communication complexity as well as the theoretical scaling complexity of FMM.

Performance Computational Engineering, Finance, and Science Mathematical Software

A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games

no code implementations20 Aug 2018 Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang

To evaluate the performance of our solution, we collect real-world data from the Samsung Game Launcher platform that includes tens of thousands of games and hundreds of millions of user-app interactions.

Attribute

Streaming Network Embedding through Local Actions

no code implementations14 Nov 2018 Xi Liu, Ping-Chun Hsieh, Nick Duffield, Rui Chen, Muhe Xie, Xidao Wen

Thus the approach of adapting the existing methods to the streaming environment faces non-trivial technical challenges.

Clustering Multi-class Classification +1

Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games

no code implementations14 Jan 2019 Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang

In this paper, we present the first large-scale churn analysis for mobile games that supports both micro-level churn prediction and macro-level churn ranking.

Attribute

GRIP: Generative Robust Inference and Perception for Semantic Robot Manipulation in Adversarial Environments

no code implementations20 Mar 2019 Xiaotong Chen, Rui Chen, Zhiqiang Sui, Zhefan Ye, Yanqi Liu, R. Iris Bahar, Odest Chadwicke Jenkins

In this work, we propose Generative Robust Inference and Perception (GRIP) as a two-stage object detection and pose estimation system that aims to combine relative strengths of discriminative CNNs and generative inference methods to achieve robust estimation.

Object object-detection +3

Deep Shape from Polarization

no code implementations ECCV 2020 Yunhao Ba, Alex Ross Gilbert, Franklin Wang, Jinfa Yang, Rui Chen, Yiqin Wang, Lei Yan, Boxin Shi, Achuta Kadambi

This paper makes a first attempt to bring the Shape from Polarization (SfP) problem to the realm of deep learning.

Active Learning for Risk-Sensitive Inverse Reinforcement Learning

no code implementations14 Sep 2019 Rui Chen, Wenshuo Wang, Zirui Zhao, Ding Zhao

One typical assumption in inverse reinforcement learning (IRL) is that human experts act to optimize the expected utility of a stochastic cost with a fixed distribution.

Active Learning reinforcement-learning +1

Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation

no code implementations20 Sep 2019 Rui Chen, Haizhou Ai, Chong Shang, Long Chen, Zijie Zhuang

It remains very challenging to build a pedestrian detection system for real world applications, which demand for both accuracy and speed.

Knowledge Distillation Pedestrian Detection

S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes

1 code implementation31 Oct 2019 Yuzhe Qin, Rui Chen, Hao Zhu, Meng Song, Jing Xu, Hao Su

Grasping is among the most fundamental and long-lasting problems in robotics study.

Normal Assisted Stereo Depth Estimation

1 code implementation CVPR 2020 Uday Kusupati, Shuo Cheng, Rui Chen, Hao Su

We couple the learning of a multi-view normal estimation module and a multi-view depth estimation module.

Stereo Depth Estimation

Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning

no code implementations27 Jan 2020 Xi Liu, Li Li, Ping-Chun Hsieh, Muhe Xie, Yong Ge, Rui Chen

With the explosive growth of online products and content, recommendation techniques have been considered as an effective tool to overcome information overload, improve user experience, and boost business revenue.

Knowledge Distillation Multi-Task Learning +2

Sex Differences in Severity and Mortality Among Patients With COVID-19: Evidence from Pooled Literature Analysis and Insights from Integrated Bioinformatic Analysis

no code implementations30 Mar 2020 Xiyi Wei, Yu-Tian Xiao, Jian Wang, Rui Chen, Wei zhang, Yue Yang, Daojun Lv, Chao Qin, Di Gu, Bo Zhang, Weidong Chen, Jianquan Hou, Ninghong Song, Guohua Zeng, Shancheng Ren

Objective: To conduct a meta-analysis of current studies that examined sex differences in severity and mortality in patients with COVID-19, and identify potential mechanisms underpinning these differences.

Towards Deeper Graph Neural Networks with Differentiable Group Normalization

1 code implementation NeurIPS 2020 Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu

Graph neural networks (GNNs), which learn the representation of a node by aggregating its neighbors, have become an effective computational tool in downstream applications.

Multi-mode OAM Radio Waves: Generation, Angle of Arrival Estimation and Reception With UCAs

no code implementations2 Jul 2020 Rui Chen, Wen-Xuan Long, Xiaodong Wang, Jiandong Li

To solve these problems, we propose an overall scheme of the line-of-sight multi-carrier and multi-mode OAM (LoS MCMM-OAM) communication based on uniform circular arrays (UCAs).

Explainable Recommender Systems via Resolving Learning Representations

no code implementations21 Aug 2020 Ninghao Liu, Yong Ge, Li Li, Xia Hu, Rui Chen, Soo-Hyun Choi

Different from previous work, in our model, factor discovery and representation learning are simultaneously conducted, and we are able to handle extra attribute information and knowledge.

Attribute Explainable Recommendation +2

Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation

no code implementations4 Dec 2020 Yanan Wang, Yong Ge, Li Li, Rui Chen, Tong Xu

To improve adaptation efficiency, we learn to recover the user policy and reward from only a few interactions via an inverse reinforcement learning method to assist a meta-level recommendation agent.

Model-based Reinforcement Learning Recommendation Systems +2

Energy Efficient Federated Learning over Heterogeneous Mobile Devices via Joint Design of Weight Quantization and Wireless Transmission

no code implementations21 Dec 2020 Rui Chen, Liang Li, Kaiping Xue, Chi Zhang, Miao Pan, Yuguang Fang

To address these challenges, in this paper, we attempt to take FL into the design of future wireless networks and develop a novel joint design of wireless transmission and weight quantization for energy efficient FL over mobile devices.

Edge-computing Federated Learning +1

Towards Energy Efficient Federated Learning over 5G+ Mobile Devices

no code implementations13 Jan 2021 Dian Shi, Liang Li, Rui Chen, Pavana Prakash, Miao Pan, Yuguang Fang

The continuous convergence of machine learning algorithms, 5G and beyond (5G+) wireless communications, and artificial intelligence (AI) hardware implementation hastens the birth of federated learning (FL) over 5G+ mobile devices, which pushes AI functions to mobile devices and initiates a new era of on-device AI applications.

Federated Learning Quantization

Hidden-charm pentaquarks with triple strangeness due to the $Ω_{c}^{(*)}\bar{D}_s^{(*)}$ interactions

no code implementations27 Jan 2021 Fu-Lai Wang, Xin-Dian Yang, Rui Chen, Xiang Liu

Our results suggest that the $\Omega_{c}\bar D_s^*$ state with $J^P={3}/{2}^{-}$ and the $\Omega_{c}^{*}\bar D_s^*$ state with $J^P={5}/{2}^{-}$ can be recommended as the candidates of the hidden-charm molecular pentaquark with triple strangeness.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Integer Programming for Causal Structure Learning in the Presence of Latent Variables

1 code implementation5 Feb 2021 Rui Chen, Sanjeeb Dash, Tian Gao

The problem of finding an ancestral acyclic directed mixed graph (ADMG) that represents the causal relationships between a set of variables is an important area of research on causal inference.

Causal Inference valid

Robust Sample Weighting to Facilitate Individualized Treatment Rule Learning for a Target Population

no code implementations3 May 2021 Rui Chen, Jared D. Huling, Guanhua Chen, Menggang Yu

The aim of this paper is to develop a weighting framework to mitigate the impact of such misspecification and thus facilitate the generalizability of optimal ITRs from a source population to a target population.

HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters

no code implementations25 Jun 2021 Gabriel Appleby, Mateus Espadoto, Rui Chen, Samuel Goree, Alexandru Telea, Erik W Anderson, Remco Chang

Projection algorithms such as t-SNE or UMAP are useful for the visualization of high dimensional data, but depend on hyperparameters which must be tuned carefully.

Dirichlet Energy Constrained Learning for Deep Graph Neural Networks

1 code implementation NeurIPS 2021 Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

To this end, we analyze the bottleneck of deep GNNs by leveraging the Dirichlet energy of node embeddings, and propose a generalizable principle to guide the training of deep GNNs.

S2Looking: A Satellite Side-Looking Dataset for Building Change Detection

1 code implementation20 Jul 2021 Li Shen, Yao Lu, Hao Chen, Hao Wei, Donghai Xie, Jiabao Yue, Rui Chen, Shouye Lv, Bitao Jiang

This paper therefore introduces S2Looking, a building-change-detection dataset that contains large-scale side-looking satellite images captured at various off-nadir angles.

Change Detection Management

Adaptive Label Smoothing To Regularize Large-Scale Graph Training

no code implementations30 Aug 2021 Kaixiong Zhou, Ninghao Liu, Fan Yang, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

Graph neural networks (GNNs), which learn the node representations by recursively aggregating information from its neighbors, have become a predominant computational tool in many domains.

Node Clustering

An Information Fusion Approach to Learning with Instance-Dependent Label Noise

no code implementations ICLR 2022 Zhimeng Jiang, Kaixiong Zhou, Zirui Liu, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

Instance-dependent label noise (IDN) widely exists in real-world datasets and usually misleads the training of deep neural networks.

EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression

no code implementations ICLR 2022 Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu

Based on the implementation, we propose a memory-efficient framework called ``EXACT'', which for the first time demonstrate the potential and evaluate the feasibility of training GNNs with compressed activations.

Graph Learning

Neuron-Enhanced Autoencoder based Collaborative filtering: Theory and Practice

no code implementations29 Sep 2021 Jicong Fan, Rui Chen, Chris Ding

We provide theoretical analysis for NE-AECF to investigate the generalization ability of autoencoder and deep learning in collaborative filtering.

Collaborative Filtering

AoA Estimation for OAM Communication Systems With Mode-Frequency Multi-Time ESPRIT Method

no code implementations18 Oct 2021 Wen-Xuan Long, Rui Chen, Marco Moretti, Jiandong Li

Radio orbital angular momentum (OAM) communications require accurate alignment between the transmit and receive beam directions.

Radio-Frequency Multi-Mode OAM Detection Based on UCA Samples Learning

no code implementations29 Nov 2021 Jiabei Fan, Rui Chen, Wen-Xuan Long, Marco Moretti, Jiandong Li

Orbital angular momentum (OAM) at radio-frequency provides a novel approach of multiplexing a set of orthogonal modes on the same frequency channel to achieve high spectral efficiencies.

ActiveZero: Mixed Domain Learning for Active Stereovision with Zero Annotation

no code implementations CVPR 2022 Isabella Liu, Edward Yang, Jianyu Tao, Rui Chen, Xiaoshuai Zhang, Qing Ran, Zhu Liu, Hao Su

First, we demonstrate the transferability of our method to out-of-distribution real data by using a mixed domain learning strategy.

MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs

no code implementations7 Jan 2022 Qiaoyu Tan, Ninghao Liu, Xiao Huang, Rui Chen, Soo-Hyun Choi, Xia Hu

We introduce a novel masked graph autoencoder (MGAE) framework to perform effective learning on graph structure data.

Link Prediction Node Classification +1

1000x Faster Camera and Machine Vision with Ordinary Devices

no code implementations23 Jan 2022 Tiejun Huang, Yajing Zheng, Zhaofei Yu, Rui Chen, Yuan Li, Ruiqin Xiong, Lei Ma, Junwei Zhao, Siwei Dong, Lin Zhu, Jianing Li, Shanshan Jia, Yihua Fu, Boxin Shi, Si Wu, Yonghong Tian

By treating vidar as spike trains in biological vision, we have further developed a spiking neural network-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1, 000x faster than human vision.

object-detection Object Detection

Learning from Physical Human Feedback: An Object-Centric One-Shot Adaptation Method

1 code implementation9 Mar 2022 Alvin Shek, Bo Ying Su, Rui Chen, Changliu Liu

For robots to be effectively deployed in novel environments and tasks, they must be able to understand the feedback expressed by humans during intervention.

Object

Sequential Cooperative Energy and Time-Optimal Lane Change Maneuvers for Highway Traffic

no code implementations31 Mar 2022 Andres S. Chavez Armijos, Rui Chen, Christos G. Cassandras, Yasir K. Al-Nadawi, Hossein Noukhiz Mahjoub, Hidekazu Araki

We derive optimal control policies for a Connected Automated Vehicle (CAV) and cooperating neighboring CAVs to carry out a lane change maneuver consisting of a longitudinal phase where the CAV properly positions itself relative to the cooperating neighbors and a lateral phase where it safely changes lanes.

Joint OAM Radar-Communication Systems: Target Recognition and Beam Optimization

no code implementations11 May 2022 Wen-Xuan Long, Rui Chen, Marco Moretti, Wei zhang, Jiandong Li

In details, we first propose an OAM-based three-dimensional (3-D) super-resolution position estimation and rotation velocity detection method, which can accurately estimate the 3-D position and rotation velocity of multiple targets.

Position Super-Resolution

Deep Multi-View Semi-Supervised Clustering with Sample Pairwise Constraints

no code implementations10 Jun 2022 Rui Chen, Yongqiang Tang, Wensheng Zhang, Wenlong Feng

Multi-view clustering has attracted much attention thanks to the capacity of multi-source information integration.

Clustering

Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing

1 code implementation8 Oct 2022 Yun Liu, Xiaomeng Xu, Weihang Chen, Haocheng Yuan, He Wang, Jing Xu, Rui Chen, Li Yi

When manipulating an object to accomplish complex tasks, humans rely on both vision and touch to keep track of the object's 6D pose.

hand-object pose Object +1

TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition

1 code implementation20 Oct 2022 Yongwei Chen, Rui Chen, Jiabao Lei, Yabin Zhang, Kui Jia

Creation of 3D content by stylization is a promising yet challenging problem in computer vision and graphics research.

Style Transfer

Adaptive Risk-Aware Bidding with Budget Constraint in Display Advertising

1 code implementation6 Dec 2022 Zhimeng Jiang, Kaixiong Zhou, Mi Zhang, Rui Chen, Xia Hu, Soo-Hyun Choi

In this work, we explicitly factor in the uncertainty of estimated ad impression values and model the risk preference of a DSP under a specific state and market environment via a sequential decision process.

reinforcement-learning Reinforcement Learning (RL)

Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection

1 code implementation23 Dec 2022 Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

To bridge the gap, we introduce a Personalized Subgraph Selector (PS2) as a plug-and-play framework to automatically, personally, and inductively identify optimal subgraphs for different edges when performing GNNLP.

Link Prediction

Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization

no code implementations ICCV 2023 Rui Chen, Qiyu Wan, Pavana Prakash, Lan Zhang, Xu Yuan, Yanmin Gong, Xin Fu, Miao Pan

However, practical deployment of FL over mobile devices is very challenging because (i) conventional FL incurs huge training latency for mobile devices due to interleaved local computing and communications of model updates, (ii) there are heterogeneous training data across mobile devices, and (iii) mobile devices have hardware heterogeneity in terms of computing and communication capabilities.

Federated Learning

State-wise Safe Reinforcement Learning: A Survey

no code implementations6 Feb 2023 WeiYe Zhao, Tairan He, Rui Chen, Tianhao Wei, Changliu Liu

Despite the tremendous success of Reinforcement Learning (RL) algorithms in simulation environments, applying RL to real-world applications still faces many challenges.

Autonomous Driving reinforcement-learning +3

Generalization Ability of Wide Neural Networks on $\mathbb{R}$

no code implementations12 Feb 2023 Jianfa Lai, Manyun Xu, Rui Chen, Qian Lin

We perform a study on the generalization ability of the wide two-layer ReLU neural network on $\mathbb{R}$.

Denoising and Prompt-Tuning for Multi-Behavior Recommendation

1 code implementation12 Feb 2023 Chi Zhang, Rui Chen, Xiangyu Zhao, Qilong Han, Li Li

In practical recommendation scenarios, users often interact with items under multi-typed behaviors (e. g., click, add-to-cart, and purchase).

Collaborative Filtering Denoising

Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach

1 code implementation NeurIPS 2023 Zhimeng Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu

Motivated by these sufficient conditions, we propose robust fairness regularization (RFR) by considering the worst case within the model weight perturbation ball for each sensitive attribute group.

Attribute Fairness

Semi-Supervised Semantic Segmentation With Region Relevance

1 code implementation23 Apr 2023 Rui Chen, Tao Chen, Qiong Wang, Yazhou Yao

The most common approach is to generate pseudo-labels for unlabeled images to augment the training data.

Pseudo Label Pseudo Label Filtering +2

GUARD: A Safe Reinforcement Learning Benchmark

1 code implementation23 May 2023 WeiYe Zhao, Rui Chen, Yifan Sun, Ruixuan Liu, Tianhao Wei, Changliu Liu

Due to the diversity of algorithms and tasks, it remains difficult to compare existing safe RL algorithms.

Autonomous Driving reinforcement-learning +2

Editable Graph Neural Network for Node Classifications

no code implementations24 May 2023 Zirui Liu, Zhimeng Jiang, Shaochen Zhong, Kaixiong Zhou, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

However, model editing for graph neural networks (GNNs) is rarely explored, despite GNNs' widespread applicability.

Fake News Detection Model Editing

State-wise Constrained Policy Optimization

1 code implementation21 Jun 2023 WeiYe Zhao, Rui Chen, Yifan Sun, Tianhao Wei, Changliu Liu

In particular, we introduce the framework of Maximum Markov Decision Process, and prove that the worst-case safety violation is bounded under SCPO.

Autonomous Driving reinforcement-learning +2

Non-line-of-sight reconstruction via structure sparsity regularization

no code implementations5 Aug 2023 Duolan Huang, Quan Chen, Zhun Wei, Rui Chen

Subsequently, the reconstruction is achieved by optimizing a directional albedo model with SS regularization using fast iterative shrinkage-thresholding algorithm.

Autonomous Driving Denoising

Augmented Negative Sampling for Collaborative Filtering

1 code implementation11 Aug 2023 Yuhan Zhao, Rui Chen, Riwei Lai, Qilong Han, Hongtao Song, Li Chen

To balance efficiency and effectiveness, the vast majority of existing methods follow the two-pass approach, in which the first pass samples a fixed number of unobserved items by a simple static distribution and then the second pass selects the final negative items using a more sophisticated negative sampling strategy.

Collaborative Filtering

TransTouch: Learning Transparent Objects Depth Sensing Through Sparse Touches

no code implementations18 Sep 2023 Liuyu Bian, Pengyang Shi, Weihang Chen, Jing Xu, Li Yi, Rui Chen

By approximating and optimizing the utility function, we can optimize the probing locations given a fixed touching budget to better improve the network's performance on real objects.

Transparent objects

Safety Index Synthesis with State-dependent Control Space

no code implementations21 Sep 2023 Rui Chen, WeiYe Zhao, Changliu Liu

This paper introduces an approach for synthesizing feasible safety indices to derive safe control laws under state-dependent control spaces.

An Optimal Control Framework for Influencing Human Driving Behavior in Mixed-Autonomy Traffic

no code implementations23 Sep 2023 Anirudh Chari, Rui Chen, Jaskaran Grover, Changliu Liu

Given these results, the main contribution of our framework is its versatility in a wide spectrum of influence objectives and mixed-autonomy configurations.

Autonomous Vehicles

SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D

1 code implementation4 Oct 2023 Weiyu Li, Rui Chen, Xuelin Chen, Ping Tan

Therefore, we improve the consistency by aligning the 2D geometric priors in diffusion models with well-defined 3D shapes during the lifting, addressing the vast majority of the problem.

Text to 3D

Absolute Policy Optimization

1 code implementation20 Oct 2023 WeiYe Zhao, Feihan Li, Yifan Sun, Rui Chen, Tianhao Wei, Changliu Liu

In recent years, trust region on-policy reinforcement learning has achieved impressive results in addressing complex control tasks and gaming scenarios.

Atari Games Continuous Control

Minimum Snap Trajectory Generation and Control for an Under-actuated Flapping Wing Aerial Vehicle

no code implementations2 Nov 2023 Chen Qian, Rui Chen, Peiyao Shen, Yongchun Fang, Jifu Yan, Tiefeng Li

This work firstly achieves the closed-loop integration of trajectory generation and control for real 3-dimensional flight of an underactuated FWAV to a practical level.

GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and Imitation

no code implementations1 Jan 2024 Zifan Wang, Junyu Chen, Ziqing Chen, Pengwei Xie, Rui Chen, Li Yi

We further introduce a distillation-friendly demonstration generation method that automatically generates a million high-quality demonstrations suitable for learning.

Grasp Generation Imitation Learning

Adaptive Hardness Negative Sampling for Collaborative Filtering

1 code implementation10 Jan 2024 Riwei Lai, Rui Chen, Qilong Han, Chi Zhang, Li Chen

Negative sampling is essential for implicit collaborative filtering to provide proper negative training signals so as to achieve desirable performance.

Collaborative Filtering

A Survey on Data-Centric Recommender Systems

no code implementations31 Jan 2024 Riwei Lai, Li Chen, Rui Chen, Chi Zhang

Recommender systems (RSs) have become an essential tool for mitigating information overload in a range of real-world applications.

Recommendation Systems

LoRA-as-an-Attack! Piercing LLM Safety Under The Share-and-Play Scenario

no code implementations29 Feb 2024 Hongyi Liu, Zirui Liu, Ruixiang Tang, Jiayi Yuan, Shaochen Zhong, Yu-Neng Chuang, Li Li, Rui Chen, Xia Hu

Our aim is to raise awareness of the potential risks under the emerging share-and-play scenario, so as to proactively prevent potential consequences caused by LoRA-as-an-Attack.

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