Publications (32)
Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness
Tavish McDonald, Bo Lei, Stanislav Fort +2
Test-time reasoning has raised benchmark performances and even shown promise in addressing the historically intractable problem of making models robust to adversarially out-of-dist…
A Deep Image Compression Framework for Face Recognition
Nai Bian, Feng Liang, Haisheng Fu +1
Face recognition technology has advanced rapidly and has been widely used in various applications. Due to the extremely huge amount of data of face images and the large computing r…
Multi-Modal Latent Variables for Cross-Individual Primary Visual Cortex Modeling and Analysis
Yu Zhu, Bo Lei, Chunfeng Song +3
Elucidating the functional mechanisms of the primary visual cortex (V1) remains a fundamental challenge in systems neuroscience. Current computational models face two critical limi…
Overview: Computer vision and machine learning for microstructural characterization and analysis
Elizabeth A. Holm, Ryan Cohn, Nan Gao +4
The characterization and analysis of microstructure is the foundation of microstructural science, connecting the materials structure to its composition, process history, and proper…
Strongly Modulated Ambipolar Characteristics of Few-layer Black Phosphorus in Oxygen
Cheng Han, Zehua Hu, Jialin Zhang +7
Two-dimensional black phosphorus has been configured as field-effect transistors, showing an intrinsic symmetric ambipolar transport characteristic. Here, we demonstrate the strong…
Computing Power Network: A Survey
Yukun Sun, Bo Lei, Junlin Liu +4
With the rapid development of cloud computing, edge computing, and smart devices, computing power resources indicate a trend of ubiquitous deployment. The traditional network archi…
M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations
Bo Lei, Victor M. Castillo, Yeping Hu
Mesh-based graph neural networks (GNNs) have become effective surrogates for PDE simulations, yet their deep message passing incurs high cost and over-smoothing on large, long-rang…
Grand canonical generative diffusion model for crystalline phases and grain boundaries
Bo Lei, Enze Chen, Hyuna Kwon +5
The diffusion model has emerged as a powerful tool for generating atomic structures for materials science. This work calls attention to the deficiency of current particle-based dif…
Triple Memory Networks: a Brain-Inspired Method for Continual Learning
Liyuan Wang, Bo Lei, Qian Li +3
Continual acquisition of novel experience without interfering previously learned knowledge, i.e. continual learning, is critical for artificial neural networks, but limited by cata…
Performance Analysis and Comparison of Non-ideal Wireless PBFT and RAFT Consensus Networks in 6G Communications
Haoxiang Luo, Xiangyue Yang, Hongfang Yu +3
Due to advantages in security and privacy, blockchain is considered a key enabling technology to support 6G communications. Practical Byzantine Fault Tolerance (PBFT) and RAFT are…
Adaptive Multi-Layer Deployment for A Digital Twin Empowered Satellite-Terrestrial Integrated Network
Yihong Tao, Bo Lei, Haoyang Shi +2
With the development of satellite communication technology, satellite-terrestrial integrated networks (STIN), which integrate satellite networks and ground networks, can realize se…
Priority and Stackelberg Game-Based Incentive Task Allocation for Device-Assisted MEC Networks
Yang Li, Xing Zhang, Bo Lei +2
Mobile edge computing (MEC) is a promising computing paradigm that offers users proximity and instant computing services for various applications, and it has become an essential co…
Right Time to Learn:Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation
Guanglong Sun, Hongwei Yan, Liyuan Wang +3
Knowledge distillation (KD) is a powerful strategy for training deep neural networks (DNNs). Although it was originally proposed to train a more compact "student" model from a larg…
Learning from Pattern Completion: Self-supervised Controllable Generation
Zhiqiang Chen, Guofan Fan, Jinying Gao +4
The human brain exhibits a strong ability to spontaneously associate different visual attributes of the same or similar visual scene, such as associating sketches and graffiti with…
Field Driven Pairing State Phase Transition in d_x^2-y^2+id_xy-Wave Superconductors
Bo Lei, S. A. Aruna, Qiang-Hua Wang
Within the framework of the Ginzburg-Landau theory for -wave superconductors, we discuss the pairing state phase transition in the absence of the Zeeman coupli…
Encyclo-K: Evaluating LLMs with Dynamically Composed Knowledge Statements
Yiming Liang, Yizhi Li, Yantao Du +14
Benchmarks play a crucial role in tracking the rapid advancement of large language models (LLMs) and identifying their capability boundaries. However, existing benchmarks predomina…
Spatiotemporal Non-Uniformity-Aware Online Task Scheduling in Collaborative Edge Computing for Industrial Internet of Things
Yang Li, Xing Zhang, Yukun Sun +2
Mobile edge computing mitigates the shortcomings of cloud computing caused by unpredictable wide-area network latency and serves as a critical enabling technology for the Industria…
Improved Hybrid Layered Image Compression using Deep Learning and Traditional Codecs
Haisheng Fu, Feng Liang, Bo Lei +5
Recently deep learning-based methods have been applied in image compression and achieved many promising results. In this paper, we propose an improved hybrid layered image compress…
ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models
Guanglong Sun, Shuang Cui, Bo Lei +6
Test-time adaptation (TTA) of vision-language models (VLMs) is essential for their robust deployment in dynamic, real-world environments. However, existing TTA methods often adapt…
Optimizing Placement and Power Allocation in Reconfigurable Intelligent Sensing Surfaces for Enhanced Sensing and Communication Performance
Cheng Luo, Jie Hu, Luping Xiang +2
In this letter, we investigate the design of multiple reconfigurable intelligent sensing surfaces (RISSs) that enhance both communication and sensing tasks. An RISS incorporates ad…
Exploring Representation Invariance in Finetuning
Wenqiang Zu, Shenghao Xie, Hao Chen +9
Foundation models pretrained on large-scale natural images are widely adapted to various cross-domain low-resource downstream tasks, benefiting from generalizable and transferable…
Incentive-Driven Task Offloading and Collaborative Computing in Device-Assisted MEC Networks
Yang Li, Xing Zhang, Bo Lei +4
Edge computing (EC), positioned near end devices, holds significant potential for delivering low-latency, energy-efficient, and secure services. This makes it a crucial component o…
Communication Efficiency Optimization of Federated Learning for Computing and Network Convergence of 6G Networks
Yizhuo Cai, Bo Lei, Qianying Zhao +4
Federated learning effectively addresses issues such as data privacy by collaborating across participating devices to train global models. However, factors such as network topology…
Spike-driven Large Language Model
Han Xu, Xuerui Qiu, Baiyu Chen +7
Current Large Language Models (LLMs) are primarily based on large-scale dense matrix multiplications. Inspired by the brain's information processing mechanism, we explore the funda…
Computation Rate Maximization for Wireless Powered Edge Computing With Multi-User Cooperation
Yang Li, Xing Zhang, Bo Lei +4
The combination of mobile edge computing (MEC) and radio frequency-based wireless power transfer (WPT) presents a promising technique for providing sustainable energy supply and co…
High throughput quantitative metallography for complex microstructures using deep learning: A case study in ultrahigh carbon steel
Brian L. DeCost, Bo Lei, Toby Francis +1
We apply a deep convolutional neural network segmentation model to enable novel automated microstructure segmentation applications for complex microstructures typically evaluated m…
GLRT-based Detection in Bistatic Sonar under Strong Direct Blast with Multipath Propagation
Bo Lei, Yao Zhang, Yixin Yang
Direct blast is a strong interference in bistatic sonar and difficult to suppress due to multipath propagation for blasts and signals. A generalized likelihood ratio test (GLRT) ba…
Training-Free Representation Guidance for Diffusion Models with a Representation Alignment Projector
Wenqiang Zu, Shenghao Xie, Bo Lei +1
Recent progress in generative modeling has enabled high-quality visual synthesis with diffusion-based frameworks, supporting controllable sampling and large-scale training. Inferen…
RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation
Shihan Wu, Xuecheng Liu, Shaoxuan Xie +81
Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware hete…
Joint Task Partitioning and Parallel Scheduling in Device-Assisted Mobile Edge Networks
Yang Li, Xinlei Ge, Bo Lei +2
With the development of the Internet of Things (IoT), certain IoT devices have the capability to not only accomplish their own tasks but also simultaneously assist other resource-c…
SpikeMLLM: Spike-based Multimodal Large Language Models via Modality-Specific Temporal Scales and Temporal Compression
Han Xu, Zhiyong Qin, Di Shang +6
Multimodal Large Language Models (MLLMs) have achieved remarkable progress but incur substantial computational overhead and energy consumption during inference, limiting deployment…
Extracting Atomic Environments for Machine Learning Interatomic Potentials
Jared C. Stimac, Fei Zhou, Kyle Bushick +4
The paper benchmarks methods for extracting small atomic environments from large-scale simulations to enable DFT calculations for training machine‑learning interatomic potentials,…