Publications (44)
PolyJailbreak: Cross-Modal Jailbreaking Attacks on Black-Box Multimodal LLMs
Xinkai Wang, Beibei Li, Zerui Shao +3
Multimodal large language models (MLLMs) have become integral to a wide range of real-world applications by jointly reasoning over text and visual inputs. However, despite recent a…
An attention-based deep learning network for predicting Platinum resistance in ovarian cancer
Haoming Zhuang, Beibei Li, Jingtong Ma +4
Background: Ovarian cancer is among the three most frequent gynecologic cancers globally. High-grade serous ovarian cancer (HGSOC) is the most common and aggressive histological ty…
What's a Credit Worth? A Market Framework for Attribution-Aware Compensation in Generative Music
Luyang Zhang, Xirui Jiang, Junwei Deng +3
Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of creators' recordings. This rais…
Weighted Holm Procedures: Theory, Properties, and Recommendations
Beibei Li, Wenge Guo
In many statistical applications, particularly in clinical studies, hypotheses may carry different levels of importance, motivating the use of weighted multiple testing procedures…
The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction
Beibei Li
In this work we propose a unified Fourier Spectral Transformer network that integrates the strengths of classical spectral methods and attention based neural architectures. By tran…
Trading Privacy for the Greater Social Good: How Did America React During COVID-19?
Anindya Ghose, Beibei Li, Meghanath Macha +2
Digital contact tracing and analysis of social distancing from smartphone location data are two prime examples of non-therapeutic interventions used in many countries to mitigate t…
The geomagnetic storm and Kp prediction using Wasserstein transformer
Beibei Li
The accurate forecasting of geomagnetic activity is important. In this work, we present a novel multimodal Transformer based framework for predicting the 3 days and 5 days planetar…
Denoising Long- and Short-term Interests for Sequential Recommendation
Xinyu Zhang, Beibei Li, Beihong Jin
User interests can be viewed over different time scales, mainly including stable long-term preferences and changing short-term intentions, and their combination facilitates the com…
What Makes People Install a COVID-19 Contact-Tracing App? Understanding the Influence of App Design and Individual Difference on Contact-Tracing App Adoption Intention
Tianshi Li, Camille Cobb, Jackie +6
Smartphone-based contact-tracing apps are a promising solution to help scale up the conventional contact-tracing process. However, low adoption rates have become a major issue that…
Do Agents Repair When Challenged -- or Just Reply? Challenge, Repair, and Public Correction in a Deployed Agent Forum
Luyang Zhang, Yi-Yun Chu, Jialu Wang +2
As large language model (LLM) agents are deployed in public interactive settings, a key question is whether their communities can sustain challenge, repair, and public correction,…
CDA: Privacy-Preserving and Provably Secure Cross Domain Authentication Scheme for Internet of Drones
Chengqi Hou, Beibei Li, Ziqing Zhu +2
The paper proposes P³CDA, a privacy-preserving and provably secure cross‑domain authentication scheme for Internet‑of‑Drones that uses adaptive pseudonym management, an enhanced Me…
AsyCo: An Asymmetric Dual-task Co-training Model for Partial-label Learning
Beibei Li, Yiyuan Zheng, Beihong Jin +3
Partial-Label Learning (PLL) is a typical problem of weakly supervised learning, where each training instance is annotated with a set of candidate labels. Self-training PLL models…
Improving Micro-video Recommendation by Controlling Position Bias
Yisong Yu, Beihong Jin, Jiageng Song +3
As the micro-video apps become popular, the numbers of micro-videos and users increase rapidly, which highlights the importance of micro-video recommendation. Although the micro-vi…
Improving Micro-video Recommendation via Contrastive Multiple Interests
Beibei Li, Beihong Jin, Jiageng Song +3
With the rapid increase of micro-video creators and viewers, how to make personalized recommendations from a large number of candidates to viewers begins to attract more and more a…
Look Closer! An Adversarial Parametric Editing Framework for Hallucination Mitigation in VLMs
Jiayu Hu, Beibei Li, Jiangwei Xia +3
While Vision-Language Models (VLMs) have garnered increasing attention in the AI community due to their promising practical applications, they exhibit persistent hallucination issu…
Numerical Simulation for General Relativistic Magnetohydrodynamics in Dynamic Spacetimes
Beibei Li
We present a novel spectral solver for general relativistic magnetohydrodynamics on dynamical spacetimes. By combining a high order discontinuous spectral method on mapped Chebyshe…
SPECTRA: Revealing the Full Spectrum of User Preferences via Distributional LLM Inference
Luyang Zhang, Jialu Wang, Shichao Zhu +4
Large Language Models (LLMs) are increasingly used to model user preferences, with the typical output as a directly-generated ranked item list per user. However, this generative pa…
Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks
Ao Liu, Wenshan Li, Tao Li +3
Graph neural networks (GNNs) have recently been shown to be vulnerable to adversarial attacks, where slight perturbations in the graph structure can lead to erroneous predictions.…
An Economic Framework for Generative Engines: Advertising or Subscription?
Luyang Zhang, Cathy Jiao, Beibei Li +1
Generative Engines (GEs) such as ChatGPT and Google's AI Overviews are rapidly reshaping search economics by delivering synthesized responses that allow users to bypass third-party…
Semantic Gaussian Mixture Variational Autoencoder for Sequential Recommendation
Beibei Li, Tao Xiang, Beihong Jin +2
Variational AutoEncoder (VAE) for Sequential Recommendation (SR), which learns a continuous distribution for each user-item interaction sequence rather than a determinate embedding…
A Vlogger-augmented Graph Neural Network Model for Micro-video Recommendation
Weijiang Lai, Beihong Jin, Beibei Li +2
Existing micro-video recommendation models exploit the interactions between users and micro-videos and/or multi-modal information of micro-videos to predict the next micro-video a…
FedCliP: Federated Learning with Client Pruning
Beibei Li, Zerui Shao, Ao Liu +1
The prevalent communication efficient federated learning (FL) frameworks usually take advantages of model gradient compression or model distillation. However, the unbalanced local…
Fairshare Data Pricing via Data Valuation for Large Language Models
Luyang Zhang, Cathy Jiao, Beibei Li +1
Training data is the backbone of large language models (LLMs), yet today's data markets often operate under exploitative pricing -- sourcing data from marginalized groups with litt…
Inclusive FinTech Lending via Contrastive Learning and Domain Adaptation
Xiyang Hu, Yan Huang, Beibei Li +1
FinTech lending (e.g., micro-lending) has played a significant role in facilitating financial inclusion. It has reduced processing times and costs, enhanced the user experience, an…
Uncovering the Source of Machine Bias
Xiyang Hu, Yan Huang, Beibei Li +1
We develop a structural econometric model to capture the decision dynamics of human evaluators on an online micro-lending platform, and estimate the model parameters using a real-w…
Design for Assurance: Employing Functional Verification Tools for Thwarting Hardware Trojan Threat in 3PIPs
Wei Hu, Beibei Li, Lingjuan Wu +3
Third-party intellectual property cores are essential building blocks of modern system-on-chip and integrated circuit designs. However, these design components usually come from ve…
Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending against Poisoning Attacks
Ao Liu, Wenshan Li, Beibei Li +3
Recent studies have revealed the vulnerability of graph neural networks (GNNs) to adversarial poisoning attacks on node classification tasks. Current defensive methods require subs…
What Makes a Star Teacher? A Hierarchical BERT Model for Evaluating Teacher's Performance in Online Education
Wen Wang, Honglei Zhuang, Mi Zhou +2
Education has a significant impact on both society and personal life. With the development of technology, online education has been growing rapidly over the past decade. While ther…
Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol (MCP) Ecosystem
Hao Song, Yiming Shen, Wenxuan Luo +6
The Model Context Protocol (MCP) is an emerging standard designed to enable seamless interaction between Large Language Model (LLM) applications and external tools or resources. Wi…
Magnetic Field Data Calibration with Transformer Model Using Physical Constraints: A Scalable Method for Satellite Missions, Illustrated by Tianwen-1
Beibei Li, Yutian Chi, Yuming Wang
This study introduces a novel approach that integrates the magnetic field data correction from the Tianwen-1 Mars mission with a neural network architecture constrained by physical…
Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience
Ao Liu, Wenshan Li, Tao Li +5
End-to-end training with global optimization have popularized graph neural networks (GNNs) for node classification, yet inadvertently introduced vulnerabilities to adversarial edge…
Improving Sequential Recommendation with Attribute-augmented Graph Neural Networks
Xinzhou Dong, Beihong Jin, Wei Zhuo +2
Many practical recommender systems provide item recommendation for different users only via mining user-item interactions but totally ignoring the rich attribute information of ite…
AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack
Ao Liu, Beibei Li, Tao Li +2
Recent studies have revealed the vulnerability of graph convolutional networks (GCNs) to edge-perturbing attacks, such as maliciously inserting or deleting graph edges. However, a…
MCICSAM: Monte Carlo-guided Interpolation Consistency Segment Anything Model for Semi-Supervised Prostate Zone Segmentation
Guantian Huang, Beibei Li, Xiaobing Fan +5
Accurate segmentation of various regions within the prostate is pivotal for diagnosing and treating prostate-related diseases. However, the scarcity of labeled data, particularly i…
Tuning Vision-Language Models with Candidate Labels by Prompt Alignment
Zhifang Zhang, Yuwei Niu, Xin Liu +1
Vision-language models (VLMs) can learn high-quality representations from a large-scale training dataset of image-text pairs. Prompt learning is a popular approach to fine-tuning V…
A Behavior-aware Graph Convolution Network Model for Video Recommendation
Wei Zhuo, Kunchi Liu, Taofeng Xue +7
Interactions between users and videos are the major data source of performing video recommendation. Despite lots of existing recommendation methods, user behaviors on videos, which…
Collaborative Interest-aware Graph Learning for Group Identification
Rui Zhao, Beihong Jin, Beibei Li +1
With the popularity of social media, an increasing number of users are joining group activities on online social platforms. This elicits the requirement of group identification (GI…
Enhancing The Open Network: Definition and Automated Detection of Smart Contract Defects
Hao Song, Teng Li, Jiachi Chen +6
The Open Network (TON), designed to support Telegram's extensive user base of hundreds of millions, has garnered considerable attention since its launch in 2022. FunC is the most p…
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes
Jiayu Hu, Senlin Shu, Beibei Li +2
Partial Label Learning (PLL) is a typical weakly supervised learning task, which assumes each training instance is annotated with a set of candidate labels containing the ground-tr…
Empowering Patients Using Smart Mobile Health Platforms: Evidence From A Randomized Field Experiment
Anindya Ghose, Xitong Guo, Beibei Li +1
With today's technological advancements, mobile phones and wearable devices have become extensions of an increasingly diffused and smart digital infrastructure. In this paper, we e…
Multi-Pair Temporal Sentence Grounding via Multi-Thread Knowledge Transfer Network
Xiang Fang, Wanlong Fang, Changshuo Wang +5
Given some video-query pairs with untrimmed videos and sentence queries, temporal sentence grounding (TSG) aims to locate query-relevant segments in these videos. Although previous…
Orthogonal Hyper-category Guided Multi-interest Elicitation for Micro-video Matching
Beibei Li, Beihong Jin, Yisong Yu +4
Watching micro-videos is becoming a part of public daily life. Usually, user watching behaviors are thought to be rooted in their multiple different interests. In the paper, we pro…
The Energy Based Near Singularity for Fourier Spectral 3D Navier-Stokes Equations
Beibei Li
We investigate the three-dimensional incompressible Navier-Stokes equations. The equations are discretized with Fourier spectral method and a fourth-order Runge-Kutta scheme in tim…
Sufficient Control of Complex Networks
Xiang Li, Guoqi Li, Leitao Gao +2
In this paper, we propose to study on sufficient control of complex networks which is to control a sufficiently large portion of the network, where only the quantity of controllabl…