Publications (105)
Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation
Junjie Wang, Xinghua Lou, Jason Li +8
Text-to-Image (T2I) models and Unified Multimodal Models (UMMs) have achieved remarkable progress in visual generation. However, their reliance on a single-pass generation paradigm…
Discriminative Adversarial Domain Generalization with Meta-learning based Cross-domain Validation
Keyu Chen, Di Zhuang, J. Morris Chang
The generalization capability of machine learning models, which refers to generalizing the knowledge for an "unseen" domain via learning from one or multiple seen domain(s), is of…
Facial Expression Retargeting from Human to Avatar Made Easy
Juyong Zhang, Keyu Chen, Jianmin Zheng
Facial expression retargeting from humans to virtual characters is a useful technique in computer graphics and animation. Traditional methods use markers or blendshapes to construc…
Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques
Pohsun Feng, Ziqian Bi, Yizhu Wen +13
A comprehensive guide to Automated Machine Learning (AutoML) is presented, covering fundamental principles, practical implementations, and future trends. The paper is structured to…
Securing Large Language Models: Addressing Bias, Misinformation, and Prompt Attacks
Benji Peng, Keyu Chen, Ming Li +5
Large Language Models (LLMs) demonstrate impressive capabilities across various fields, yet their increasing use raises critical security concerns. This article reviews recent lite…
Unknown Identity Rejection Loss: Utilizing Unlabeled Data for Face Recognition
Haiming Yu, Yin Fan, Keyu Chen +4
Face recognition has advanced considerably with the availability of large-scale labeled datasets. However, how to further improve the performance with the easily accessible unlabel…
Large Language Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challenges
Qian Niu, Junyu Liu, Ziqian Bi +16
This comprehensive review explores the intersection of Large Language Models (LLMs) and cognitive science, examining similarities and differences between LLMs and human cognitive p…
Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing
Ming Li, Ziqian Bi, Tianyang Wang +14
General Purpose Graphics Processing Unit (GPGPU) computing plays a transformative role in deep learning and machine learning by leveraging the computational advantages of parallel…
From In Silico to In Vitro: A Comprehensive Guide to Validating Bioinformatics Findings
Tianyang Wang, Silin Chen, Yunze Wang +18
The integration of bioinformatics predictions and experimental validation plays a pivotal role in advancing biological research, from understanding molecular mechanisms to developi…
Modified-Emergency Index (MEI): A Criticality Metric for Autonomous Driving in Lateral Conflict
Hao Cheng, Yanbo Jiang, Qingyuan Shi +5
Effective, reliable, and efficient evaluation of autonomous driving safety is essential to demonstrate its trustworthiness. Criticality metrics provide an objective means of assess…
DriveCamSim: Generalizable Camera Simulation via Explicit Camera Modeling for Autonomous Driving
Wenchao Sun, Xuewu Lin, Keyu Chen +4
Camera sensor simulation serves as a critical role for autonomous driving (AD), e.g. evaluating vision-based AD algorithms. While existing approaches have leveraged generative mode…
SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Driving
Wenchao Sun, Xuewu Lin, Keyu Chen +4
End-to-end multi-modal planning has been widely adopted to model the uncertainty of driving behavior, typically by scoring candidate trajectories and selecting the optimal one. Exi…
Deep Learning and Machine Learning -- Natural Language Processing: From Theory to Application
Keyu Chen, Cheng Fei, Ziqian Bi +23
With a focus on natural language processing (NLP) and the role of large language models (LLMs), we explore the intersection of machine learning, deep learning, and artificial intel…
HiChunk: Evaluating and Enhancing Retrieval-Augmented Generation with Hierarchical Chunking
Wensheng Lu, Keyu Chen, Ruizhi Qiao +1
Retrieval-Augmented Generation (RAG) enhances the response capabilities of language models by integrating external knowledge sources. However, document chunking as an important par…
From Noise to Nuance: Advances in Deep Generative Image Models
Benji Peng, Chia Xin Liang, Ziqian Bi +6
Deep learning-based image generation has undergone a paradigm shift since 2021, marked by fundamental architectural breakthroughs and computational innovations. Through reviewing a…
Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction
Mingchen Li, Di Zhuang, Keyu Chen +2
Link prediction in graph data uses various algorithms and Graph Nerual Network (GNN) models to predict potential relationships between graph nodes. These techniques have found wide…
Jailbreaking and Mitigation of Vulnerabilities in Large Language Models
Benji Peng, Hanxuan Chen, Keyu Chen +12
Large Language Models (LLMs) have transformed artificial intelligence by advancing natural language understanding and generation, enabling applications across fields beyond healthc…
Training-Free Hashing-Based Attention via Binary Principal Components
Daohai Yu, Zhanpeng Zeng, Keyu Chen +6
Long-context large language models (LLMs) are increasingly deployed in real-world applications, yet self-attention remains a major efficiency bottleneck -- especially during decodi…
Collaborative Noisy Label Cleaner: Learning Scene-aware Trailers for Multi-modal Highlight Detection in Movies
Bei Gan, Xiujun Shu, Ruizhi Qiao +4
Movie highlights stand out of the screenplay for efficient browsing and play a crucial role on social media platforms. Based on existing efforts, this work has two observations: (1…
Deep Learning and Machine Learning -- Object Detection and Semantic Segmentation: From Theory to Applications
Jintao Ren, Ziqian Bi, Qian Niu +16
An in-depth exploration of object detection and semantic segmentation is provided, combining theoretical foundations with practical applications. State-of-the-art advancements in m…
Youtu-LLM: Unlocking the Native Agentic Potential for Lightweight Large Language Models
Junru Lu, Jiarui Qin, Lingfeng Qiao +35
We introduce Youtu-LLM, a lightweight yet powerful language model that harmonizes high computational efficiency with native agentic intelligence. Unlike typical small models that r…
Skill Is Not Document: Query-Conditioned Compatibility for LLM Agent Skill Routing
Zifei Wang, Wei Wen, Qiang Ji +3
Large language model agents increasingly rely on reusable skills, making skill retrieval a critical front-end component of agent systems. Skill retrieval, however, is not ordinary…
Infinite Motion: Extended Motion Generation via Long Text Instructions
Mengtian Li, Chengshuo Zhai, Shengxiang Yao +3
In the realm of motion generation, the creation of long-duration, high-quality motion sequences remains a significant challenge. This paper presents our groundbreaking work on "Inf…
Deep Learning and Machine Learning: Advancing Big Data Analytics and Management with Design Patterns
Keyu Chen, Ziqian Bi, Tianyang Wang +12
This book, Design Patterns in Machine Learning and Deep Learning: Advancing Big Data Analytics Management, presents a comprehensive study of essential design patterns tailored for…
Time-Resolved Coulomb Explosion Imaging Unveils Ultrafast Ring Opening of Furan
Enliang Wang, Surjendu Bhattacharyya, Keyu Chen +10
Following the changes in molecular structure throughout the entirety of a chemical reaction with atomic resolution is a long-term goal in femtochemistry. Although the development o…
AutoSurvey2: Empowering Researchers with Next Level Automated Literature Surveys
Siyi Wu, Chiaxin Liang, Ziqian Bi +7
The rapid growth of research literature, particularly in large language models (LLMs), has made producing comprehensive and current survey papers increasingly difficult. This paper…
Improved Algorithms for Differentially Private Language Model Alignment
Keyu Chen, Hao Tang, Qinglin Liu +1
Language model alignment is crucial for ensuring that large language models (LLMs) align with human preferences, yet it often involves sensitive user data, raising significant priv…
Generative Adversarial Networks Bridging Art and Machine Intelligence
Junhao Song, Yichao Zhang, Ziqian Bi +25
Generative Adversarial Networks (GAN) have greatly influenced the development of computer vision and artificial intelligence in the past decade and also connected art and machine i…
WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset
Jiantao Qiu, Haijun Lv, Zhenjiang Jin +23
This paper presents WanJuan-CC, a safe and high-quality open-sourced English webtext dataset derived from Common Crawl data. The study addresses the challenges of constructing larg…
Parameter-Efficient Fine-Tuning With Adapters
Keyu Chen, Yuan Pang, Zi Yang
In the arena of language model fine-tuning, the traditional approaches, such as Domain-Adaptive Pretraining (DAPT) and Task-Adaptive Pretraining (TAPT), although effective, but com…
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models
Keyu Chen, Ziqian Bi, Qian Niu +12
The application of TensorFlow pre-trained models in deep learning is explored, with an emphasis on practical guidance for tasks such as image classification and object detection. T…
Measurement of surface tension coefficients of liquids based on equal thickness interference
Ziyi Xu, Chongyuan Xu, Liwen Tong +2
The surface tension coefficient is a key parameter in fluid mechanics. The conventional method to measure it is to determine the critical surface tension that causes the rupture of…
Learning Adaptive Loss for Robust Learning with Noisy Labels
Jun Shu, Qian Zhao, Keyu Chen +2
Robust loss minimization is an important strategy for handling robust learning issue on noisy labels. Current robust loss functions, however, inevitably involve hyperparameter(s) t…
From Events to Trending: A Multi-Stage Hotspots Detection Method Based on Generative Query Indexing
Kaichun Wang, Yanguang Chen, Ting Zhang +7
LLM-based conversational systems have become a popular gateway for information access, yet most existing chatbots struggle to handle news-related trending queries effectively. To i…
FREA: Feasibility-Guided Generation of Safety-Critical Scenarios with Reasonable Adversariality
Keyu Chen, Yuheng Lei, Hao Cheng +3
Generating safety-critical scenarios, which are essential yet difficult to collect at scale, offers an effective method to evaluate the robustness of autonomous vehicles (AVs). Exi…
Explainable and High-Performance Hate and Offensive Speech Detection
Marzieh Babaeianjelodar, Gurram Poorna Prudhvi, Stephen Lorenz +4
The spread of information through social media platforms can create environments possibly hostile to vulnerable communities and silence certain groups in society. To mitigate such…
Surveying the MLLM Landscape: A Meta-Review of Current Surveys
Ming Li, Keyu Chen, Ziqian Bi +12
The rise of Multimodal Large Language Models (MLLMs) has become a transformative force in the field of artificial intelligence, enabling machines to process and generate content ac…
From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models
Charles Zhang, Benji Peng, Xintian Sun +14
Word embeddings and language models have transformed natural language processing (NLP) by facilitating the representation of linguistic elements in continuous vector spaces. This r…
Modeling Caricature Expressions by 3D Blendshape and Dynamic Texture
Keyu Chen, Jianmin Zheng, Jianfei Cai +1
The problem of deforming an artist-drawn caricature according to a given normal face expression is of interest in applications such as social media, animation and entertainment. Th…
A Comprehensive Guide to Explainable AI: From Classical Models to LLMs
Weiche Hsieh, Ziqian Bi, Chuanqi Jiang +24
Explainable Artificial Intelligence (XAI) addresses the growing need for transparency and interpretability in AI systems, enabling trust and accountability in decision-making proce…
Evolution of Superatomic-Charge-density-wave and Superconductivity under Pressure in AuTeSe
Xu Chen, Ge Fei, Yanpeng Song +15
Superatomic crystal is a class of hierarchical materials composed of atomically precise clusters assembled via van der Waals or covalent-like interactions. AuTeSe, an a…
Deep Learning and Machine Learning -- Python Data Structures and Mathematics Fundamental: From Theory to Practice
Silin Chen, Ziqian Bi, Junyu Liu +15
This book provides a comprehensive introduction to the foundational concepts of machine learning (ML) and deep learning (DL). It bridges the gap between theoretical mathematics and…
ManimAgent: Self-Evolving Multimodal Agents for Visual Education
Wenjia Jiang, Zongyuan Cai, Yuanhang Shao +7
Multi-round reflection lets agents built on large language models recover from failures within a single task, but each task remains an isolated episode: lessons learned across many…
MAIC-UI: Making Interactive Courseware with Generative UI
Shangqing Tu, Yanjia Li, Keyu Chen +7
Creating interactive STEM courseware traditionally requires HTML/CSS/JavaScript expertise, leaving barriers for educators. While generative AI can produce HTML codes, existing tool…
Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- Blockchain and Applications
Pohsun Feng, Ziqian Bi, Lawrence K. Q. Yan +14
A detailed exploration of blockchain technology and its applications across various fields is provided, beginning with an introduction to cryptography fundamentals, including symme…
ExpertAD: Enhancing Autonomous Driving Systems with Mixture of Experts
Haowen Jiang, Xinyu Huang, You Lu +6
Recent advancements in end-to-end autonomous driving systems (ADSs) underscore their potential for perception and planning capabilities. However, challenges remain. Complex driving…
AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis
Yudong Guo, Keyu Chen, Sen Liang +3
Generating high-fidelity talking head video by fitting with the input audio sequence is a challenging problem that receives considerable attentions recently. In this paper, we addr…
Advanced Deep Learning Methods for Protein Structure Prediction and Design
Yichao Zhang, Ningyuan Deng, Xinyuan Song +25
After AlphaFold won the Nobel Prize, protein prediction with deep learning once again became a hot topic. We comprehensively explore advanced deep learning methods applied to prote…
Microprocessor Design with Dynamic Clock Source and Multi-Width Instructions
Keyu Chen, Xuyi Hu, Robert Killey
This paper introduces a novel 32-bit microprocessor, based on the RISC-V instruction set architecture, is designed,utilising a dynamic clock source to achieve high efficiency, over…
Image Matters: Visually modeling user behaviors using Advanced Model Server
Tiezheng Ge, Liqin Zhao, Guorui Zhou +13
In Taobao, the largest e-commerce platform in China, billions of items are provided and typically displayed with their images. For better user experience and business effectiveness…
From Text to Multimodality: Exploring the Evolution and Impact of Large Language Models in Medical Practice
Qian Niu, Keyu Chen, Ming Li +16
Large Language Models (LLMs) have rapidly evolved from text-based systems to multimodal platforms, significantly impacting various sectors including healthcare. This comprehensive…
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…
Prior Aided Streaming Network for Multi-task Affective Recognitionat the 2nd ABAW2 Competition
Wei Zhang, Zunhu Guo, Keyu Chen +3
Automatic affective recognition has been an important research topic in human computer interaction (HCI) area. With recent development of deep learning techniques and large scale i…
SAIA: Split Artificial Intelligence Architecture for Mobile Healthcare System
Di Zhuang, Nam Nguyen, Keyu Chen +1
As the advancement of deep learning (DL), the Internet of Things and cloud computing techniques for biomedical and healthcare problems, mobile healthcare systems have received unpr…
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models
Junjie Yang, Junhao Song, Xudong Han +9
Knowledge distillation (KD) is a technique for transferring knowledge from complex teacher models to simpler student models, significantly enhancing model efficiency and accuracy.…
Partisan US News Media Representations of Syrian Refugees
Keyu Chen, Marzieh Babaeianjelodar, Yiwen Shi +13
We investigate how representations of Syrian refugees (2011-2021) differ across US partisan news outlets. We analyze 47,388 articles from the online US media about Syrian refugees…
Optimal Transport and Wasserstein Barycenter for Radially Contoured Distributions
Keyu Chen, Yunxin Zhang
The optimal transport and Wasserstein barycenter of Gaussian distributions have been solved. In literature, the closed form formulas of the Monge map, the Wasserstein distance and…
From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing
Xintian Sun, Benji Peng, Charles Zhang +10
Remote sensing has evolved from simple image acquisition to complex systems capable of integrating and processing visual and textual data. This review examines the development and…
DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering
Wei Cheng, Ruixiang Chen, Wanqi Yin +18
Realistic human-centric rendering plays a key role in both computer vision and computer graphics. Rapid progress has been made in the algorithm aspect over the years, yet existing…
Driving risk emerges from the required two-dimensional joint evasive acceleration
Hao Cheng, Yanbo Jiang, Wenhao Yu +9
Most autonomous driving safety benchmarks use time-to-collision (TTC) to assess risk and guide safe behaviour. However, TTC-based methods treat risk as a one-dimensional closing pr…
When should I search more: Adaptive Complex Query Optimization with Reinforcement Learning
Wei Wen, Sihang Deng, Tianjun Wei +3
Query optimization is a crucial component for the efficacy of Retrieval-Augmented Generation (RAG) systems. While reinforcement learning (RL)-based agentic and reasoning methods ha…
See Finer, See More: Implicit Modality Alignment for Text-based Person Retrieval
Xiujun Shu, Wei Wen, Haoqian Wu +5
Text-based person retrieval aims to find the query person based on a textual description. The key is to learn a common latent space mapping between visual-textual modalities. To ac…
Toward Native Multimodal Modeling: A Roadmap
Siyu An, Junru Lu, Junnan Dong +18
Multimodal modeling represents a vital step from modality-agnostic reasoning toward world modeling. While early approaches predominantly rely on late-fusion that assembles encoders…
Probing the structure of cyclic hydrocarbon molecules with X-ray-induced Coulomb explosion imaging
Kurtis D. Borne, Rebecca Boll, Thomas M. Baumann +27
Coulomb explosion imaging (CEI) is a powerful experimental technique that maps a molecule's geometric structure onto the momenta of ionic molecular fragments produced by rapid mult…
Large Language Model Benchmarks in Medical Tasks
Lawrence K. Q. Yan, Qian Niu, Ming Li +16
With the increasing application of large language models (LLMs) in the medical domain, evaluating these models' performance using benchmark datasets has become crucial. This paper…
GaussianBody: Clothed Human Reconstruction via 3d Gaussian Splatting
Mengtian Li, Shengxiang Yao, Zhifeng Xie +1
In this work, we propose a novel clothed human reconstruction method called GaussianBody, based on 3D Gaussian Splatting. Compared with the costly neural radiance based models, 3D…
Scene Consistency Representation Learning for Video Scene Segmentation
Haoqian Wu, Keyu Chen, Yanan Luo +5
A long-term video, such as a movie or TV show, is composed of various scenes, each of which represents a series of shots sharing the same semantic story. Spotting the correct scene…
Adaptive Dual Reasoner: Large Reasoning Models Can Think Efficiently by Hybrid Reasoning
Yujian Zhang, Keyu Chen, Zhifeng Shen +2
Although Long Reasoning Models (LRMs) have achieved superior performance on various reasoning scenarios, they often suffer from increased computational costs and inference latency…
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI's Potential Through Tools, Techniques, and Applications
Pohsun Feng, Ziqian Bi, Yizhu Wen +14
Artificial intelligence (AI), machine learning, and deep learning have become transformative forces in big data analytics and management, enabling groundbreaking advancements acros…
How is Vaping Framed on Online Knowledge Dissemination Platforms?
Keyu Chen, Yiwen Shi, Jun Luo +7
We analyze 1,888 articles and 1,119,453 vaping posts to study how vaping is framed across multiple knowledge dissemination platforms (Wikipedia, Quora, Medium, Reddit, Stack Exchan…
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management
Weiche Hsieh, Ziqian Bi, Keyu Chen +23
Advancements in artificial intelligence, machine learning, and deep learning have catalyzed the transformation of big data analytics and management into pivotal domains for researc…
Beyond Voxel 3D Editing: Learning from 3D Masks and Self-Constructed Data
Yizhao Xu, Hongyuan Zhu, Caiyun Liu +6
3D editing refers to the ability to apply local or global modifications to 3D assets. Effective 3D editing requires maintaining semantic consistency by performing localized changes…
AvatarBrush: Monocular Reconstruction of Gaussian Avatars with Intuitive Local Editing
Mengtian Li, Shengxiang Yao, Yichen Pan +4
The efficient reconstruction of high-quality and intuitively editable human avatars presents a pressing challenge in the field of computer vision. Recent advancements, such as 3DGS…
A Note on a Recent Attempt to Prove the Irrationality of
Keyu Chen, Wei He, Yixin He +7
Recently Shekhar Suman [arXiv: 2407.07121v6 [math.GM] 3 Aug 2024] made an attempt to prove the irrationality of . But unfortunately the proof is not correct. In this note, w…
Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception
Junjie Wang, Keyu Chen, Yulin Li +4
Dense visual perception tasks have been constrained by their reliance on predefined categories, limiting their applicability in real-world scenarios where visual concepts are unbou…
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer
Benji Peng, Xuanhe Pan, Yizhu Wen +13
This book explores the role of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in driving the progress of big data analytics and management. The book fo…
Adaptive Frequency Enhancement Network for Single Image Deraining
Fei Yan, Yuhong He, Keyu Chen +2
Image deraining aims to improve the visibility of images damaged by rainy conditions, targeting the removal of degradation elements such as rain streaks, raindrops, and rain accumu…
Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translation
Keyu Chen, Di Zhuang, Mingchen Li +1
Neural Machine Translation (NMT) models have become successful, but their performance remains poor when translating on new domains with a limited number of data. In this paper, we…
A Relaxed Wasserstein Distance Formulation for Mixtures of Radially Contoured Distributions
Keyu Chen, Zetian Wang, Yunxin Zhang
Recently, a Wasserstein-type distance for Gaussian mixture models has been proposed. However, that framework can only be generalized to identifiable mixtures of general ellipticall…
Pressure-induced superconductivity in itinerant antiferromagnet CrB2
Cuiying Pei, Pengtao Yang, Chunsheng Gong +11
The recent discovery of superconductivity up to 32 K in the pressurized MoB2 revives the interests in exploring novel superconductors in transition-metal diborides isostructural to…
ASPD: Unlocking Adaptive Serial-Parallel Decoding by Exploring Intrinsic Parallelism in LLMs
Keyu Chen, Zhifeng Shen, Daohai Yu +5
The increasing scale and complexity of large language models (LLMs) pose significant inference latency challenges, primarily due to their autoregressive decoding paradigm character…
CoLLiE: Collaborative Training of Large Language Models in an Efficient Way
Kai Lv, Shuo Zhang, Tianle Gu +11
Large language models (LLMs) are increasingly pivotal in a wide range of natural language processing tasks. Access to pre-trained models, courtesy of the open-source community, has…
From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence
Tianyang Wang, Yunze Wang, Jun Zhou +16
Uncertainty quantification (UQ) is a critical aspect of artificial intelligence (AI) systems, particularly in high-risk domains such as healthcare, autonomous systems, and financia…
Is GPT-OSS Good? A Comprehensive Evaluation of OpenAI's Latest Open Source Models
Ziqian Bi, Keyu Chen, Chiung-Yi Tseng +9
In August 2025, OpenAI released GPT-OSS models, its first open weight large language models since GPT-2 in 2019, comprising two mixture of experts architectures with 120B and 20B p…
Enhancing End-to-End Autonomous Driving with Risk Semantic Distillaion from VLM
Jack Qin, Zhitao Wang, Yinan Zheng +4
The autonomous driving (AD) system has exhibited remarkable performance in complex driving scenarios. However, generalization is still a key limitation for the current system, whic…
SuperCon: Supervised Contrastive Learning for Imbalanced Skin Lesion Classification
Keyu Chen, Di Zhuang, J. Morris Chang
Convolutional neural networks (CNNs) have achieved great success in skin lesion classification. A balanced dataset is required to train a good model. However, due to the appearance…
From Bench to Bedside: A Review of Clinical Trials in Drug Discovery and Development
Tianyang Wang, Ming Liu, Benji Peng +17
Clinical trials are an indispensable part of the drug development process, bridging the gap between basic research and clinical application. During the development of new drugs, cl…
RIFT: Group-Relative RL Fine-Tuning for Realistic and Controllable Traffic Simulation
Keyu Chen, Wenchao Sun, Hao Cheng +1
Achieving both realism and controllability in closed-loop traffic simulation remains a key challenge in autonomous driving. Dataset-based methods reproduce realistic trajectories b…
End-to-end Conditional Diffusion for Realistic and Controllable Visual Traffic Scenario Generation
Jingzheng Li, Yufei Ge, Zhijun Chen +8
Generating closed-loop traffic scenarios that are both realistic and controllable is crucial for evaluating autonomous driving systems, especially under rare safety-critical intera…
Disentangled Representation Learning for 3D Face Shape
Zi-Hang Jiang, Qianyi Wu, Keyu Chen +1
In this paper, we present a novel strategy to design disentangled 3D face shape representation. Specifically, a given 3D face shape is decomposed into identity part and expression…
CS-AF: A Cost-sensitive Multi-classifier Active Fusion Framework for Skin Lesion Classification
Di Zhuang, Keyu Chen, J. Morris Chang
Convolutional neural networks (CNNs) have achieved the state-of-the-art performance in skin lesion analysis. Compared with single CNN classifier, combining the results of multiple…
Deep Learning Model Security: Threats and Defenses
Tianyang Wang, Ziqian Bi, Yichao Zhang +24
Deep learning has transformed AI applications but faces critical security challenges, including adversarial attacks, data poisoning, model theft, and privacy leakage. This survey e…
ForSim: Stepwise Forward Simulation for Traffic Policy Fine-Tuning
Keyu Chen, Wenchao Sun, Hao Cheng +2
As the foundation of closed-loop training and evaluation in autonomous driving, traffic simulation still faces two fundamental challenges: covariate shift introduced by open-loop i…
Exploring Efficiency Frontiers of Thinking Budget in Medical Reasoning: Scaling Laws between Computational Resources and Reasoning Quality
Ziqian Bi, Lu Chen, Junhao Song +15
This study presents the first comprehensive evaluation of thinking budget mechanisms in medical reasoning tasks, revealing fundamental scaling laws between computational resources…
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Object-Oriented Programming
Tianyang Wang, Ziqian Bi, Keyu Chen +12
Object-Oriented Programming (OOP) has become a crucial paradigm for managing the growing complexity of modern software systems, particularly in fields like machine learning, deep l…
Pressure-Induced Large Volume Collapse, Plane-to-Chain, Insulator to Metal Transition in CaMnBi
Xin Gui, Gregory J. Finkelstein, Keyu Chen +4
In-situ high pressure single crystal X-ray diffraction study reveals that the quantum material CaMnBi undergoes a unique plane to chain structural transition between 2 and…
Simultaneous imaging of vibrational, rotational, and electronic wave packet dynamics in a triatomic molecule
Huynh Van Sa Lam, Van-Hung Hoang, Anbu Selvam Venkatachalam +9
Light-induced molecular dynamics often involve the excitation of several electronic, vibrational, and rotational states. Since the ensuing electronic and nuclear motion determines…
Differentiating Three-Dimensional Molecular Structures using Laser-induced Coulomb Explosion Imaging
Huynh Van Sa Lam, Anbu Selvam Venkatachalam, Surjendu Bhattacharyya +8
Coulomb explosion imaging (CEI) with x-ray free electron lasers has recently been shown to be a powerful method for obtaining detailed structural information of gas-phase planar ri…
FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging
Ziyang Fan, Keyu Chen, Ruilong Xing +3
Although Video Large Language Models (VLLMs) have shown remarkable capabilities in video understanding, they are required to process high volumes of visual tokens, causing signific…
X-ray Coulomb explosion imaging reveals role of molecular structure in internal conversion
Till Jahnke, Sebastian Mai, Surjendu Bhattacharyya +26
Molecular photoabsorption results in an electronic excitation/ionization which couples to the rearrangement of the nuclei. The resulting intertwined change of nuclear and electroni…