Tootfinder

Isaiah Pola-Mao looks to bring physicality in the secondary https://www.raiders.com/video/isaiah-pola-mao-defense-secondary-nfl-07272025

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[9/9]:
- Vidar: Embodied Video Diffusion Model for Generalist Bimanual Manipulation
Yao Feng, Hengkai Tan, Xinyi Mao, Guodong Liu, Shuhe Huang, Chendong Xiang, Hang Su, Jun Zhu

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/8]:
- Can Prompt Difficulty be Online Predicted for Accelerating RL Finetuning of Reasoning Models?
Yun Qu, Qi Wang, Yixiu Mao, Vincent Tao Hu, Bj\"orn Ommer, Xiangyang Ji

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[1/2]:
- TrafficMCTS: A Closed-Loop Traffic Flow Generation Framework with Group-Based Monte Carlo Tree Se...
Ze Fu, Licheng Wen, Pinlong Cai, Daocheng Fu, Song Mao, Botian Shi

Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications
Jiacheng Wang, Changyuan Zhao, Zehui Xiong, Tao Xiang, Dusit Niyato, Xianbin Wang, Shiwen Mao, Dong In Kim
https://arxiv.org/abs/2507.19837

Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications
AI-enabled wireless communications have attracted tremendous research interest in recent years, particularly with the rise of novel paradigms such as low-altitude integrated sensing and communication (ISAC) networks. Within these systems, feature engineering plays a pivotal role by transforming raw wireless data into structured representations suitable for AI models. Hence, this paper offers a comprehensive investigation of feature engineering techniques in AI-driven wireless communications. Sp…

What a beautiful smile has the Japanese 🇯🇵 climber Mao Nakamura 🧗‍♀️. I hold an extra pair of fingers crossed 🤞 for her to top just to see her smile. Not to mention that she keeps smiling

Chain-of-Thought for Large Language Model-empowered Wireless Communications
Xudong Wang, Jian Zhu, Ruichen Zhang, Lei Feng, Dusit Niyato, Jiacheng Wang, Hongyang Du, Shiwen Mao, Zhu Han
https://arxiv.org/abs/2505.22320

Chain-of-Thought for Large Language Model-empowered Wireless Communications
Recent advances in large language models (LLMs) have opened new possibilities for automated reasoning and decision-making in wireless networks. However, applying LLMs to wireless communications presents challenges such as limited capability in handling complex logic, generalization, and reasoning. Chain-of-Thought (CoT) prompting, which guides LLMs to generate explicit intermediate reasoning steps, has been shown to significantly improve LLM performance on complex tasks. Inspired by this, this …

Revealing Atomic-Scale Switching Pathways in van der Waals Ferroelectrics
Xinyan Li, Kenna Ashen, Chuqiao Shi, Nannan Mao, Saagar Kolachina, Kaiwen Yang, Tianyi Zhang, Sajid Husain, Ramamoorthy Ramesh, Jing Kong, Xiaofeng Qian, Yimo Han
https://arxiv.org/abs/2507.20543

Revealing Atomic-Scale Switching Pathways in van der Waals Ferroelectrics
Two-dimensional van der Waals (vdW) materials hold the potential for ultra-scaled ferroelectric (FE) devices due to their silicon compatibility and robust polarization down to atomic scale. However, the inherently weak vdW interactions enable facile sliding between layers, introducing complexities beyond those encountered in conventional ferroelectric materials and presenting significant challenges in uncovering intricate switching pathways. Here, we combine atomic-resolution imaging under in-s…

Mass threshold for global existence in chemotaxis systems with critical flux limitation
Xuan Mao, Hengling Wang, Jianlu Yan
https://arxiv.org/abs/2507.19866 https://

Mass threshold for global existence in chemotaxis systems with critical flux limitation
This paper investigates the flux-limited chemotaxis system, proposed by Kohatsu and Senba~(2025), \begin{equation*} \begin{cases} u_t = Δu -\nabla\cdot(u|\nabla v|^{α-2}\nabla v),\\ \:\:0=Δv + u, \end{cases} \end{equation*} posed in the unit ball of $\mathbb{R}^N$ for some $N\geq2$, subject to no-flux and homogeneous Dirichlet boundary conditions. Due to precedents, e.g., Tello (2022) and Winkler (2022), the exponent $α= \frac{N}{N-1}$ is the threshold for finite-time blow-up …

WATCH: Raiders Quarterback Geno Smith Speaks Following Training Camp https://www.si.com/nfl/raiders/las-vegas-training-camp-pete-carroll-isaiah-pola-mao-

STDR: Spatio-Temporal Decoupling for Real-Time Dynamic Scene Rendering
Zehao Li, Hao Jiang, Yujun Cai, Jianing Chen, Baolong Bi, Shuqin Gao, Honglong Zhao, Yiwei Wang, Tianlu Mao, Zhaoqi Wang
https://arxiv.org/abs/2505.22400

STDR: Spatio-Temporal Decoupling for Real-Time Dynamic Scene Rendering
Although dynamic scene reconstruction has long been a fundamental challenge in 3D vision, the recent emergence of 3D Gaussian Splatting (3DGS) offers a promising direction by enabling high-quality, real-time rendering through explicit Gaussian primitives. However, existing 3DGS-based methods for dynamic reconstruction often suffer from \textit{spatio-temporal incoherence} during initialization, where canonical Gaussians are constructed by aggregating observations from multiple frames without te…

Iterative Pretraining Framework for Interatomic Potentials
Taoyong Cui, Zhongyao Wang, Dongzhan Zhou, Yuqiang Li, Lei Bai, Wanli Ouyang, Mao Su, Shufei Zhang
https://arxiv.org/abs/2507.20118

Iterative Pretraining Framework for Interatomic Potentials
Machine learning interatomic potentials (MLIPs) enable efficient molecular dynamics (MD) simulations with ab initio accuracy and have been applied across various domains in physical science. However, their performance often relies on large-scale labeled training data. While existing pretraining strategies can improve model performance, they often suffer from a mismatch between the objectives of pretraining and downstream tasks or rely on extensive labeled datasets and increasingly complex archi…

Replaced article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
[1/1]:
- TrafficMCTS: A Closed-Loop Traffic Flow Generation Framework with Group-Based Monte Carlo Tree Se...
Ze Fu, Licheng Wen, Pinlong Cai, Daocheng Fu, Song Mao, Botian Shi

SPA: Towards More Stealth and Persistent Backdoor Attacks in Federated Learning
Chengcheng Zhu, Ye Li, Bosen Rao, Jiale Zhang, Yunlong Mao, Sheng Zhong
https://arxiv.org/abs/2506.20931

SPA: Towards More Stealth and Persistent Backdoor Attacks in Federated Learning
Federated Learning (FL) has emerged as a leading paradigm for privacy-preserving distributed machine learning, yet the distributed nature of FL introduces unique security challenges, notably the threat of backdoor attacks. Existing backdoor strategies predominantly rely on end-to-end label supervision, which, despite their efficacy, often results in detectable feature disentanglement and limited persistence. In this work, we propose a novel and stealthy backdoor attack framework, named SPA, whi…

RecCoT: Enhancing Recommendation via Chain-of-Thought
Shuo Yang, Jiangxia Cao, Haipeng Li, Yuqi Mao, Shuchao Pang
https://arxiv.org/abs/2506.21032 https://…

RecCoT: Enhancing Recommendation via Chain-of-Thought
In real-world applications, users always interact with items in multiple aspects, such as through implicit binary feedback (e.g., clicks, dislikes, long views) and explicit feedback (e.g., comments, reviews). Modern recommendation systems (RecSys) learn user-item collaborative signals from these implicit feedback signals as a large-scale binary data-streaming, subsequently recommending other highly similar items based on users' personalized historical interactions. However, from this collaborat…

I smoked dope. I read Chairman Mao. I fucked coeds. My life was perfect. And then [title of the movie] happened.
- some damn Seth Rogen thing

Covert Communications in MEC-Based Networked ISAC Systems Towards Low-Altitude Economy
Weihao Mao, Yang Lu, Bo Ai, Tony Q. S. Quek
https://arxiv.org/abs/2507.18194 https://

Covert Communications in MEC-Based Networked ISAC Systems Towards Low-Altitude Economy
Low-altitude economy (LAE) is an emerging business model, which heavily relies on integrated sensing and communications (ISAC), mobile edge computing (MEC), and covert communications. This paper investigates the convert transmission design in MEC-based networked ISAC systems towards LAE, where an MEC server coordinates multiple access points to simultaneously receive computation tasks from multiple unmanned aerial vehicles (UAVs), locate a target in a sensing area, and maintain UAVs' covert tra…

Will Jamal Adams Return to Form with Raiders? https://www.si.com/nfl/raiders/las-vegas-jamal-adams-jeremy-chinn-isaiah-pola-mao-pete-carroll-

Model Reduction of Homogeneous Polynomial Dynamical Systems via Tensor Decomposition
Xin Mao, Can Chen
https://arxiv.org/abs/2506.19165 https://

Model Reduction of Homogeneous Polynomial Dynamical Systems via Tensor Decomposition
Model reduction plays a critical role in system control, with established methods such as balanced truncation widely used for linear systems. However, extending these methods to nonlinear settings, particularly polynomial dynamical systems that are often used to model higher-order interactions in physics, biology, and ecology, remains a significant challenge. In this article, we develop a novel model reduction method for homogeneous polynomial dynamical systems (HPDSs) with linear input and out…

Inhomogeneous plane waves in attenuative anisotropic porous media
Lingli Gao, Weijian Mao, Qianru Xu, Wei Ouyang, Shaokang Yang, Shijun Cheng
https://arxiv.org/abs/2506.20389

Inhomogeneous plane waves in attenuative anisotropic porous media
We investigate the propagation of inhomogeneous plane waves in poro-viscoelastic media, explicitly incorporating both velocity and attenuation anisotropy. Starting from classical Biot theory, we present a fractional differential equation describing wave propagation in attenuative anisotropic porous media that accommodates arbitrary anisotropy in both velocity and attenuation. Then, instead of relying on the traditional complex wave vector approach, we derive new Christoffel and energy balance e…

DeepWriter: A Fact-Grounded Multimodal Writing Assistant Based On Offline Knowledge Base
Song Mao, Lejun Cheng, Pinlong Cai, Guohang Yan, Ding Wang, Botian Shi
https://arxiv.org/abs/2507.14189

DeepWriter: A Fact-Grounded Multimodal Writing Assistant Based On Offline Knowledge Base
Large Language Models (LLMs) have demonstrated remarkable capabilities in various applications. However, their use as writing assistants in specialized domains like finance, medicine, and law is often hampered by a lack of deep domain-specific knowledge and a tendency to hallucinate. Existing solutions, such as Retrieval-Augmented Generation (RAG), can suffer from inconsistency across multiple retrieval steps, while online search-based methods often degrade quality due to unreliable web content…

An ansatz for constructing explicit solutions of Hessian equations
Chung-Jun Tsai, Mao-Pei Tsui, Mu-Tao Wang
https://arxiv.org/abs/2506.17701 https://

An ansatz for constructing explicit solutions of Hessian equations
We introduce a (variation of quadrics) ansatz for constructing explicit, real-valued solutions to broad classes of complex Hessian equations on domains in $\mathbb{C}^{n+1}$ and real Hessian equations on domains in $\mathbb{R}^{n+1}$. In the complex setting, our method simultaneously addresses the deformed Hermitian--Yang--Mills/Leung--Yau--Zaslow (dHYM/LYZ) equation, the Monge--Ampère equation, and the $J$-equation. Under this ansatz each PDE reduces to a second-order system of ordinary diffe…

A new window into the sub-parsec scale magnetic field in the Milky Way? Unveiling small-scale magneto-ionic structures with Faraday complexity
Yik Ki Ma, Amit Seta, N. M. McClure-Griffiths, C. L. Van Eck, S. A. Mao, A. Ordog, J. C. Brown, T. O. Kovacs, Takuya Akahori, K. Kurahara, L. Oberhelman, C. S. Anderson
https://arxiv.org/…

A new window into the sub-parsec scale magnetic field in the Milky Way? Unveiling small-scale magneto-ionic structures with Faraday complexity
Radio broadband spectro-polarimetric observations are sensitive to the spatial fluctuations of the Faraday depth (FD) within the telescope beam. Such FD fluctuations are referred to as "Faraday complexity", and can unveil small-scale magneto-ionic structures in both the synchrotron-emitting and the foreground volumes. We explore the astrophysical origin of the Faraday complexity exhibited by 191 polarised extragalactic radio sources (EGSs) within 5 deg from the Galactic plane in the longitude r…

E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI
Yusen Peng, Shuhua Mao
https://arxiv.org/abs/2507.18004 https://arxiv.org/p…

E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI
How can AI move beyond imitation toward genuine creativity? This paper proposes the E.A.R.T.H. framework, a five-stage generative pipeline that transforms model-generated errors into creative assets through Error generation, Amplification, Refine selection, Transform, and Harness feedback. Drawing on cognitive science and generative modeling, we posit that "creative potential hides in failure" and operationalize this via structured prompts, semantic scoring, and human-in-the-loop evaluation. Im…

Q: How do you get to Chairman Mao Memorial Hall?
A: Praxis, praxis, praxis!

Characterizations of monotone right continuous functions which generate associative functions
Yun-Mao Zhang, Xue-ping Wang
https://arxiv.org/abs/2506.18944

Characterizations of monotone right continuous functions which generate associative functions
Associativity of a two-place function $T: [0,1]^2\rightarrow [0,1]$ defined by $T(x,y)=f^{(-1)}(T^*(f(x),f(y)))$ where $T^*:[0,1]^2\rightarrow[0,1]$ is an associative function with neutral element in $[0,1]$, $f: [0,1]\rightarrow [0,1]$ is a monotone right continuous function and $f^{(-1)}:[0,1]\rightarrow[0,1]$ is the pseudo-inverse of $f$ depends only on properties of the range of $f$. The necessary and sufficient conditions for the $T$ to be associative are presented by applying the properti…

The Trump administration has accomplished something that Hitler, Stalin, Mao, and other dictators desired.
-- It destroyed the Voice of America.
Until mid-March, VOA had been on the air continuously for 83 years.
Starting in 1942 with shortwave broadcasts in German to counter Nazi propaganda,
America’s external voice had expanded to nearly 50 languages,
with a weekly combined audience of more than 350 million people worldwide, watching on TV, listening on radi…

I Fought To Keep VOA Independent. Now It’s Gone.
The Trump administration has accomplished something that Hitler, Stalin, Mao, and other dictators desired. It destroyed the Voice of America. Until mid-March, VOA had been on the air continuously for 83 years. Starting in 1942 with shortwave broadcasts in German to counter Nazi propaganda, America’s...

Yume: An Interactive World Generation Model
Xiaofeng Mao, Shaoheng Lin, Zhen Li, Chuanhao Li, Wenshuo Peng, Tong He, Jiangmiao Pang, Mingmin Chi, Yu Qiao, Kaipeng Zhang
https://arxiv.org/abs/2507.17744

Yume: An Interactive World Generation Model
Yume aims to use images, text, or videos to create an interactive, realistic, and dynamic world, which allows exploration and control using peripheral devices or neural signals. In this report, we present a preview version of \method, which creates a dynamic world from an input image and allows exploration of the world using keyboard actions. To achieve this high-fidelity and interactive video world generation, we introduce a well-designed framework, which consists of four main components, incl…

Detection of subsurface structures with a vehicle-based atom gravity gradiometer
Xiaowei Zhang, Jiaqi Zhong, Muyan Wang, Huilin Wan, Hui Xiong, Dandan Jiang, Zhi Li, Dekai Mao, Bin Gao, Biao Tang, Xi Chen, Jin Wang, Mingsheng Zhan
https://arxiv.org/abs/2506.18506

Detection of subsurface structures with a vehicle-based atom gravity gradiometer
High-precision mobile gravity gradiometers are very useful in geodesy and geophysics. Atom gravity gradiometers (AGGs) could be among the most accurate mobile gravity gradiometers but are currently constrained by the trade-off between portability and sensitivity. Here, we present a high-sensitivity mobile AGG featuring an ultra-compact sensor head with a volume of only 94 L. In the laboratory, it achieves a sensitivity of 77 E/$\sqrt{Hz}$ (1 E=1$\times10^{-9}$/s$^2$) and a long-term stability o…

Delayed Launch of Ultrafast Outflows in the Tidal Disruption Event AT2020afhd
Zikun Lin, Yanan Wang, De-Fu Bu, Junjie Mao, Jifeng Liu
https://arxiv.org/abs/2507.15482

Delayed Launch of Ultrafast Outflows in the Tidal Disruption Event AT2020afhd
We report the detection and characterization of ultrafast outflows (UFOs) in the X-ray spectra of the tidal disruption event (TDE) AT2020afhd, based on observations from NICER, Swift, and XMM. Prominent blueshifted absorption features were detected exclusively during the intermediate phase of the event, occurring between days 172 and 212 within the first 300 days post-discovery. During this period, the UFO appeared no earlier than day 74, strengthened between days 172 and 194, and disappeared a…

ARTreeFormer: A Faster Attention-based Autoregressive Model for Phylogenetic Inference
Tianyu Xie, Yicong Mao, Cheng Zhang
https://arxiv.org/abs/2507.18380 https://

ARTreeFormer: A Faster Attention-based Autoregressive Model for Phylogenetic Inference
Probabilistic modeling over the combinatorially large space of tree topologies remains a central challenge in phylogenetic inference. Previous approaches often necessitate pre-sampled tree topologies, limiting their modeling capability to a subset of the entire tree space. A recent advancement is ARTree, a deep autoregressive model that offers unrestricted distributions for tree topologies. However, its reliance on repetitive tree traversals and inefficient local message passing for computing t…

Improvement on LiDAR-Camera Calibration Using Square Targets
Zhongyuan Li, Honggang Gou, Ping Li, Jiaotong Guo, Mao Ye
https://arxiv.org/abs/2506.18294 htt…

Improvement on LiDAR-Camera Calibration Using Square Targets
Precise sensor calibration is critical for autonomous vehicles as a prerequisite for perception algorithms to function properly. Rotation error of one degree can translate to position error of meters in target object detection at large distance, leading to improper reaction of the system or even safety related issues. Many methods for multi-sensor calibration have been proposed. However, there are very few work that comprehensively consider the challenges of the calibration procedure when appli…

What is Exciting About Raiders Safety Isaiah Pola-Mao? https://www.si.com/nfl/raiders/patrick-graham-las-vegas-isaiah-pola-mao-

CogniQ-H: A Soft Hierarchical Reinforcement Learning Paradigm for Automated Data Preparation
Jing Chang, Chang Liu, Jinbin Huang, Rui Mao, Jianbin Qin
https://arxiv.org/abs/2507.13710

CogniQ-H: A Soft Hierarchical Reinforcement Learning Paradigm for Automated Data Preparation
Data preparation is a foundational yet notoriously challenging component of the machine learning lifecycle, characterized by a vast combinatorial search space of potential operator sequences. While reinforcement learning (RL) offers a promising direction, existing approaches are inefficient as they fail to capture the structured, hierarchical nature of the problem. We argue that Hierarchical Reinforcement Learning (HRL), a paradigm that has been successful in other domains, provides a conceptua…

Trustworthy Tree-based Machine Learning by $MoS_2$ Flash-based Analog CAM with Inherent Soft Boundaries
Bo Wen, Guoyun Gao, Zhicheng Xu, Ruibin Mao, Xiaojuan Qi, X. Sharon Hu, Xunzhao Yin, Can Li
https://arxiv.org/abs/2507.12384

Trustworthy Tree-based Machine Learning by $MoS_2$ Flash-based Analog CAM with Inherent Soft Boundaries
The rapid advancement of artificial intelligence has raised concerns regarding its trustworthiness, especially in terms of interpretability and robustness. Tree-based models like Random Forest and XGBoost excel in interpretability and accuracy for tabular data, but scaling them remains computationally expensive due to poor data locality and high data dependence. Previous efforts to accelerate these models with analog content addressable memory (CAM) have struggled, due to the fact that the diff…

SMARTAPS: Tool-augmented LLMs for Operations Management
Timothy Tin Long Yu, Mahdi Mostajabdaveh, Jabo Serge Byusa, Rindra Ramamonjison, Giuseppe Carenini, Kun Mao, Zirui Zhou, Yong Zhang
https://arxiv.org/abs/2507.17927

SMARTAPS: Tool-augmented LLMs for Operations Management
Large language models (LLMs) present intriguing opportunities to enhance user interaction with traditional algorithms and tools in real-world applications. An advanced planning system (APS) is a sophisticated software that leverages optimization to help operations planners create, interpret, and modify an operational plan. While highly beneficial, many customers are priced out of using an APS due to the ongoing costs of consultants responsible for customization and maintenance. To address the n…

Replaced article(s) found for q-bio.BM. https://arxiv.org/list/q-bio.BM/new
[1/1]:
- Protein folding classes -- High-dimensional geometry of amino acid composition space revisited
Boryeu Mao

Spacecraft Safe Robust Control Using Implicit Neural Representation for Geometrically Complex Targets in Proximity Operations
Hang Zhou, Tao Meng, Kun Wang, Chengrui Shi, Renhao Mao, Weijia Wang, Jiakun Lei
https://arxiv.org/abs/2507.13672

Spacecraft Safe Robust Control Using Implicit Neural Representation for Geometrically Complex Targets in Proximity Operations
This study addresses the challenge of ensuring safe spacecraft proximity operations, focusing on collision avoidance between a chaser spacecraft and a complex-geometry target spacecraft under disturbances. To ensure safety in such scenarios, a safe robust control framework is proposed that leverages implicit neural representations. To handle arbitrary target geometries without explicit modeling, a neural signed distance function (SDF) is learned from point cloud data via a enhanced implicit geo…

MERba: Multi-Receptive Field MambaVision for Micro-Expression Recognition
Xinglong Mao, Shifeng Liu, Sirui Zhao, Tong Xu, Enhong Chen
https://arxiv.org/abs/2506.14468

MERba: Multi-Receptive Field MambaVision for Micro-Expression Recognition
Micro-expressions (MEs) are brief, involuntary facial movements that reveal genuine emotions, holding significant potential in psychological diagnosis and criminal investigations. Despite notable advances in automatic ME recognition (MER), existing methods still struggle to jointly capture localized muscle activations and global facial dependencies, both critical for recognizing subtle emotional cues. To tackle this challenge, we propose MERba, a novel multi-receptive field architecture tailore…

CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios
Shiting Huang, Zhen Fang, Zehui Chen, Siyu Yuan, Junjie Ye, Yu Zeng, Lin Chen, Qi Mao, Feng Zhao
https://arxiv.org/abs/2506.13977

CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios
The ability of large language models (LLMs) to utilize external tools has enabled them to tackle an increasingly diverse range of tasks. However, as the tasks become more complex and long-horizon, the intricate tool utilization process may trigger various unexpected errors. Therefore, how to effectively handle such errors, including identifying, diagnosing, and recovering from them, has emerged as a key research direction for advancing tool learning. In this work, we first extensively analyze t…

Physical-Layer Signal Injection Attacks on EV Charging Ports: Bypassing Authentication via Electrical-Level Exploits
Hetian Shi, Yi He, Shangru Song, Jianwei Zhuge, Jian Mao
https://arxiv.org/abs/2506.16400

Physical-Layer Signal Injection Attacks on EV Charging Ports: Bypassing Authentication via Electrical-Level Exploits
The proliferation of electric vehicles in recent years has significantly expanded the charging infrastructure while introducing new security risks to both vehicles and chargers. In this paper, we investigate the security of major charging protocols such as SAE J1772, CCS, IEC 61851, GB/T 20234, and NACS, uncovering new physical signal spoofing attacks in their authentication mechanisms. By inserting a compact malicious device into the charger connector, attackers can inject fraudulent signals t…

What is Exciting About Raiders Safety Isaiah Pola-Mao? https://www.si.com/nfl/raiders/patrick-graham-las-vegas-isaiah-pola-mao-

Replaced article(s) found for math.GM. https://arxiv.org/list/math.GM/new
[1/1]:
- The characterizations of monotone functions which generate associative functions
Chen Meng, Yun-Mao Zhang, Xue-ping Wang

Colombia presidential hopeful shot in head at rally (Frances Mao/BBC)
https://www.bbc.com/news/articles/c9dq8yxxy8zo
http://www.memeorandum.com/250608/p3#a250608p3

MMStencil: Optimizing High-order Stencils on Multicore CPU using Matrix Unit
Yinuo Wang, Tianqi Mao, Lin Gan, Wubing Wan, Zeyu Song, Jiayu Fu, Lanke He, Wenqiang Wang, Zekun Yin, Wei Xue, Guangwen Yang
https://arxiv.org/abs/2507.11067

MMStencil: Optimizing High-order Stencils on Multicore CPU using Matrix Unit
Matrix-accelerated stencil computation is a hot research topic, yet its application to three-dimensional (3D) high-order stencils and HPC remains underexplored. With the emergence of matrix units on multicore CPUs, we analyze matrix-based acceleration strategies and tailor an optimal approach for 3D high-order stencils. We introduce algorithmic optimizations based on SIMD and matrix units to address strided memory accesses, alignment conflicts, and redundant accesses. We propose memory optimiza…

Reconfigurable Intelligent Surface-Enabled Green and Secure Offloading for Mobile Edge Computing Networks
Tong-Xing Zheng, Xinji Wang, Xin Chen, Di Mao, Jia Shi, Cunhua Pan, Chongwen Huang, Haiyang Ding, Zan Li
https://arxiv.org/abs/2507.16666

Reconfigurable Intelligent Surface-Enabled Green and Secure Offloading for Mobile Edge Computing Networks
This paper investigates a multi-user uplink mobile edge computing (MEC) network, where the users offload partial tasks securely to an access point under the non-orthogonal multiple access policy with the aid of a reconfigurable intelligent surface (RIS) against a multi-antenna eavesdropper. We formulate a non-convex optimization problem of minimizing the total energy consumption subject to secure offloading requirement, and we build an efficient block coordinate descent framework to iteratively…

Feynman Integral Reduction using Syzygy-Constrained Symbolic Reduction Rules
Sid Smith, Mao Zeng
https://arxiv.org/abs/2507.11140 https://

Feynman Integral Reduction using Syzygy-Constrained Symbolic Reduction Rules
We present a new algorithm for integration-by-parts (IBP) reduction of Feynman integrals with high powers of numerators or propagators, a demanding computational step in evaluating multi-loop scattering amplitudes. The algorithm starts with solving syzygy equations in individual sectors to produce IBP operators that turn seed integrals into IBP equations without artificially raised propagator powers. The IBP operators are expressed in terms of index-shift operators and number operators. We perf…

Improved Uncooperative Spacecraft Maneuver Detection with Space-based Optical Observations
Xuejian Mao, Pei Liu, Pei Chen
https://arxiv.org/abs/2506.11435 …

Improved Uncooperative Spacecraft Maneuver Detection with Space-based Optical Observations
Building and maintaining a space object catalog is necessary for space situational awareness. To realize this, one great challenge is uncooperative spacecraft maneuver detection because unknown maneuver events can lead to deviated orbital predictions and losses of tracking. Nowadays, more and more spacecraft equip electric propulsion and perform long-duration maneuvers to realize orbital transfer. Previous studies have investigated impulsive maneuver detection with space surveillance data. But,…

Wi-Fi Sensing Tool Release: Gathering 802.11ax Channel State Information from a Commercial Wi-Fi Access Point
Zisheng Wang, Feng Li, Hangbin Zhao, Zihuan Mao, Yaodong Zhang, Qisheng Huang, Bo Cao, Mingming Cao, Baolin He, Qilin Hou
https://arxiv.org/abs/2506.16957

Wi-Fi Sensing Tool Release: Gathering 802.11ax Channel State Information from a Commercial Wi-Fi Access Point
Wi-Fi sensing has emerged as a powerful technology, leveraging channel state information (CSI) extracted from wireless data packets to enable diverse applications, ranging from human presence detection to gesture recognition and health monitoring. However, CSI extraction from commercial Wi-Fi access point lacks and out of date. This paper introduces ZTECSITool,a toolkit designed to capture high-resolution CSI measurements from commercial Wi-Fi 6 (802.11ax) access points, supporting bandwidths u…

Detecting (emergent) continuous symmetry of criticality via subsystem's entanglement spectrum
Bin-Bin Mao, Zhe Wang, Bin-Bin Chen, Zheng Yan
https://arxiv.org/abs/2506.09889

Detecting (emergent) continuous symmetry of criticality via subsystem's entanglement spectrum
The (emergent) symmetry of a critical point is one of the most important information to identify the universality class and effective field theory, which is fundamental for various critical theories. However, the underlying symmetry so far can only be conjectured indirectly from the dimension of the order parameters in symmetry-breaking phases, and its correctness requires further verifications to avoid overlooking hidden order parameters, which by itself is also a difficult task. In this work,…

Near-field optical mode engineering-enabled freeform nonlocal metasurfaces
Zhongjun Jiang, Tianxiang Dai, Shuwei Guo, Soyaib Sohag, Yixuan Shao, Chenkai Mao, Andrea Al\`u, Jonathan A. Fan, You Zhou
https://arxiv.org/abs/2506.15495

Near-field optical mode engineering-enabled freeform nonlocal metasurfaces
Nanophotonic technologies inherently rely on tailoring light-matter interactions through the excitation and interference of deeply confined optical resonances. However, existing concepts in optical mode engineering remain heuristic and are challenging to extend towards complex and multi-functional resonant phenomena. Here, we introduce an inverse design framework that optimizes near-field distributions, ideally suited to tailor Mie-type modes within dielectric nanophotonic structures, and we de…

What You Think Is What You Get: Bridge User Intent and Transfer Function Design through Multimodal Large Language Models
Yiyao Wang, Bo Pan, Ke Wang, Han Liu, Jinyuan Mao, Yuxin Liu, Minfeng Zhu, Bo Zhang, Weifeng Chen, Xiuqi Huang, Wei Chen
https://arxiv.org/abs/2506.18407

What You Think Is What You Get: Bridge User Intent and Transfer Function Design through Multimodal Large Language Models
Direct volume rendering (DVR) is a fundamental technique for visualizing volumetric data, with transfer functions (TFs) playing a crucial role in extracting meaningful structures. However, designing effective TFs remains unintuitive due to the semantic gap between user intent and TF parameter space. Researchers have developed numerous TF optimization methods to bridge this gap. However, existing methods still face two challenges: large exploration space and weak generalizability. To address the…

Sparse Autoencoders Bridge The Deep Learning Model and The Brain
Ziming Mao, Jia Xu, Zeqi Zheng, Haofang Zheng, Dabing Sheng, Yaochu Jin, Guoyuan Yang
https://arxiv.org/abs/2506.11123

Sparse Autoencoders Bridge The Deep Learning Model and The Brain
We present SAE-BrainMap, a novel framework that directly aligns deep learning visual model representations with voxel-level fMRI responses using sparse autoencoders (SAEs). First, we train layer-wise SAEs on model activations and compute the correlations between SAE unit activations and cortical fMRI signals elicited by the same natural image stimuli with cosine similarity, revealing strong activation correspondence (maximum similarity up to 0.76). Depending on this alignment, we construct a vo…

Replaced article(s) found for cond-mat.mtrl-sci. https://arxiv.org/list/cond-mat.mtrl-sci/new
[1/2]:
- Single-dislocation phonons: atomic-scale measurement and their thermal properties
Li, Han, Yang, Mao, Liu, Shi, Qi, Hao, Li, Liu, Li, Du, Chen, Li, Gao
…

Isaiah Pola-Mao: 'I'm just learning, listening, and taking it all in' https://www.raiders.com/video/isaiah-pola-mao-defense-raiders-minicamp-presser-nfl-offseason-061125

Smooth Games of Configuration in the Linear-Quadratic Setting
Jesse Milzman, Jeffrey Mao, Giuseppe Loianno
https://arxiv.org/abs/2507.16611 https://…

Smooth Games of Configuration in the Linear-Quadratic Setting
Dynamic game theory offers a toolbox for formalizing and solving for both cooperative and non-cooperative strategies in multi-agent scenarios. However, the optimal configuration of such games remains largely unexplored. While there is existing literature on the parametrization of dynamic games, little research examines this parametrization from a strategic perspective where each agent's configuration choice is influenced by the decisions of others. In this work, we introduce the concept of a ga…

On the Hardness of Unsupervised Domain Adaptation: Optimal Learners and Information-Theoretic Perspective
Zhiyi Dong, Zixuan Liu, Yongyi Mao
https://arxiv.org/abs/2507.06552

On the Hardness of Unsupervised Domain Adaptation: Optimal Learners and Information-Theoretic Perspective
This paper studies the hardness of unsupervised domain adaptation (UDA) under covariate shift. We model the uncertainty that the learner faces by a distribution $π$ in the ground-truth triples $(p, q, f)$ -- which we call a UDA class -- where $(p, q)$ is the source -- target distribution pair and $f$ is the classifier. We define the performance of a learner as the overall target domain risk, averaged over the randomness of the ground-truth triple. This formulation couples the source distributi…

UAV-Enabled Wireless-Powered Underground Communication Networks: A Novel Time Allocation Approach
Kaiqiang Lin, Yijie Mao, Onel Luis Alcaraz L\'opez, Mohamed-Slim Alouini
https://arxiv.org/abs/2507.14627

UAV-Enabled Wireless-Powered Underground Communication Networks: A Novel Time Allocation Approach
Wireless-powered underground communication networks (WPUCNs), which allow underground devices (UDs) to harvest energy from wireless signals for battery-free communication, offer a promising solution for sustainable underground monitoring. However, the severe wireless signal attenuation in challenging underground environments and the costly acquisition of channel state information (CSI) make large-scale WPUCNs economically infeasible in practice. To address this challenge, we introduce flexible …

An Interpretable Two-Stage Feature Decomposition Method for Deep Learning-based SAR ATR
Chenwei Wang, Renjie Xu, Congwen Wu, Cunyi Yin, Ziyun Liao, Deqing Mao, Sitong Zhang, Hong Yan
https://arxiv.org/abs/2506.09377

An Interpretable Two-Stage Feature Decomposition Method for Deep Learning-based SAR ATR
Synthetic aperture radar automatic target recognition (SAR ATR) has seen significant performance improvements with deep learning. However, the black-box nature of deep SAR ATR introduces low confidence and high risks in decision-critical SAR applications, hindering practical deployment. To address this issue, deep SAR ATR should provide an interpretable reasoning basis $r_b$ and logic $λ_w$, forming the reasoning logic $\sum_{i} {{r_b^i} \times {λ_w^i}} =pred$ behind the decisions. Therefore,…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[4/7]:
- DualReal: Adaptive Joint Training for Lossless Identity-Motion Fusion in Video Customization
Wenchuan Wang, Mengqi Huang, Yijing Tu, Zhendong Mao

LLaPipe: LLM-Guided Reinforcement Learning for Automated Data Preparation Pipeline Construction
Jing Chang, Chang Liu, Jinbin Huang, Rui Mao, Jianbin Qin
https://arxiv.org/abs/2507.13712

LLaPipe: LLM-Guided Reinforcement Learning for Automated Data Preparation Pipeline Construction
Automated data preparation is crucial for democratizing machine learning, yet existing reinforcement learning (RL) based approaches suffer from inefficient exploration in the vast space of possible preprocessing pipelines. We present LLaPipe, a novel framework that addresses this exploration bottleneck by integrating Large Language Models (LLMs) as intelligent policy advisors. Unlike traditional methods that rely solely on statistical features and blind trial-and-error, LLaPipe leverages the se…

A Survey of Context Engineering for Large Language Models
Lingrui Mei, Jiayu Yao, Yuyao Ge, Yiwei Wang, Baolong Bi, Yujun Cai, Jiazhi Liu, Mingyu Li, Zhong-Zhi Li, Duzhen Zhang, Chenlin Zhou, Jiayi Mao, Tianze Xia, Jiafeng Guo, Shenghua Liu
https://arxiv.org/abs/2507.13334

A Survey of Context Engineering for Large Language Models
The performance of Large Language Models (LLMs) is fundamentally determined by the contextual information provided during inference. This survey introduces Context Engineering, a formal discipline that transcends simple prompt design to encompass the systematic optimization of information payloads for LLMs. We present a comprehensive taxonomy decomposing Context Engineering into its foundational components and the sophisticated implementations that integrate them into intelligent systems. We fi…

WATCH: Raiders S Isaiah Pola-Mao Following Training Camp https://www.si.com/nfl/raiders/las-vegas-tom-mcmahon-ashton-jeanty-isaiah-pola-mao

Raiders minicamp: Jeremy Chinn, Isaiah Pola-Mao part of new-look defensive backfield https://www.nytimes.com/athletic/6419812/2025/06/11/raiders-minicamp-jeremy-chinn-isaiah-pola-mao/

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem
Yanxu Mao, Tiehan Cui, Peipei Liu, Datao You, Hongsong Zhu
https://arxiv.org/abs/2506.15170

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem
Large language models (LLMs) are rapidly evolving from single-modal systems to multimodal LLMs and intelligent agents, significantly expanding their capabilities while introducing increasingly severe security risks. This paper presents a systematic survey of the growing complexity of jailbreak attacks and corresponding defense mechanisms within the expanding LLM ecosystem. We first trace the developmental trajectory from LLMs to MLLMs and Agents, highlighting the core security challenges emergi…

Reconciling Risk-Aversion Paradoxes in the Distribution-Free Newsvendor Problem: Scarf's Rule Meets Dual Utility
Jonathan Yu-Meng Li, Tiantian Mao, Reza Valimoradi
https://arxiv.org/abs/2507.10735

Reconciling Risk-Aversion Paradoxes in the Distribution-Free Newsvendor Problem: Scarf's Rule Meets Dual Utility
How should a risk-averse newsvendor order optimally under distributional ambiguity? Attempts to extend Scarf's celebrated distribution-free ordering rule using risk measures have led to conflicting prescriptions: CVaR-based models invariably recommend ordering less as risk aversion increases, while mean-standard deviation models -- paradoxically -- suggest ordering more, particularly when ordering costs are high. We resolve this behavioral paradox through a coherent generalization of Scarf's di…

The halo magnetic field of a spiral galaxy at z=0.414
Timea Orsolya Kovacs, Sui Ann Mao, Aritra Basu, Yik Ki Ma, B. M. Gaensler
https://arxiv.org/abs/2507.12542

The halo magnetic field of a spiral galaxy at z=0.414
Even though magnetic fields play an important role in galaxy evolution, the redshift evolution of galactic-scale magnetic fields is not well constrained observationally. In this paper we aim to provide an observational constraint on the time-scale of the mean-field dynamo, and derive the magnetic field in a distant galaxy at $z=0.414$. We obtained broadband spectro-polarimetric $1-8$ GHz Very Large Array observation of the lensing system B1600+434, which is a background quasar gravitationally l…

Sequence Modeling for Time-Optimal Quadrotor Trajectory Optimization with Sampling-based Robustness Analysis
Katherine Mao, Hongzhan Yu, Ruipeng Zhang, Igor Spasojevic, M Ani Hsieh, Sicun Gao, Vijay Kumar
https://arxiv.org/abs/2506.13915

Sequence Modeling for Time-Optimal Quadrotor Trajectory Optimization with Sampling-based Robustness Analysis
Time-optimal trajectories drive quadrotors to their dynamic limits, but computing such trajectories involves solving non-convex problems via iterative nonlinear optimization, making them prohibitively costly for real-time applications. In this work, we investigate learning-based models that imitate a model-based time-optimal trajectory planner to accelerate trajectory generation. Given a dataset of collision-free geometric paths, we show that modeling architectures can effectively learn the pat…

Sekai: A Video Dataset towards World Exploration
Zhen Li, Chuanhao Li, Xiaofeng Mao, Shaoheng Lin, Ming Li, Shitian Zhao, Zhaopan Xu, Xinyue Li, Yukang Feng, Jianwen Sun, Zizhen Li, Fanrui Zhang, Jiaxin Ai, Zhixiang Wang, Yuwei Wu, Tong He, Jiangmiao Pang, Yu Qiao, Yunde Jia, Kaipeng Zhang
https://arxiv.org/abs/2506.15675…

Sekai: A Video Dataset towards World Exploration
Video generation techniques have made remarkable progress, promising to be the foundation of interactive world exploration. However, existing video generation datasets are not well-suited for world exploration training as they suffer from some limitations: limited locations, short duration, static scenes, and a lack of annotations about exploration and the world. In this paper, we introduce Sekai (meaning ``world'' in Japanese), a high-quality first-person view worldwide video dataset with rich…

Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning
Yuheng Lei, Sitong Mao, Shunbo Zhou, Hongyuan Zhang, Xuelong Li, Ping Luo
https://arxiv.org/abs/2506.05985

Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning
A generalist agent must continuously learn and adapt throughout its lifetime, achieving efficient forward transfer while minimizing catastrophic forgetting. Previous work within the dominant pretrain-then-finetune paradigm has explored parameter-efficient fine-tuning for single-task adaptation, effectively steering a frozen pretrained model with a small number of parameters. However, in the context of lifelong learning, these methods rely on the impractical assumption of a test-time task identi…

ATRO: A Fast Solver-Free Algorithm for Topology and Routing Optimization of Reconfigurable Datacenter Networks
Yingming Mao, Qiaozhu Zhai, Zhen Yao, Xia Zhu, Ximeng Liu, Xinchi Han
https://arxiv.org/abs/2507.13717

ATRO: A Fast Solver-Free Algorithm for Topology and Routing Optimization of Reconfigurable Datacenter Networks
The growing scale and complexity of reconfigurable data center networks (DCNs) demand more scalable and efficient algorithms for computing logical topologies and routing. Reconfigurable DCNs typically operate in two modes: one-hop configurations that require frequent topology optimization (TO), and multi-hop scenarios that involve joint topology and routing optimization (TRO). In both cases, the combinatorial nature of topology decisions makes it difficult for existing methods to balance soluti…

Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs
Xumeng Wen, Zihan Liu, Shun Zheng, Zhijian Xu, Shengyu Ye, Zhirong Wu, Xiao Liang, Yang Wang, Junjie Li, Ziming Miao, Jiang Bian, Mao Yang
https://arxiv.org/abs/2506.14245

Multiple-Mode Affine Frequency Division Multiplexing with Index Modulation
Guangyao Liu, Tianqi Mao, Yanqun Tang, Jingjing Zhao, Zhenyu Xiao
https://arxiv.org/abs/2507.13037

Multiple-Mode Affine Frequency Division Multiplexing with Index Modulation
Affine frequency division multiplexing (AFDM), a promising multicarrier technique utilizing chirp signals, has been envisioned as an effective solution for high-mobility communication scenarios. In this paper, we develop a multiple-mode index modulation scheme tailored for AFDM, termed as MM-AFDM-IM, which aims to further improve the spectral and energy efficiencies of AFDM. Specifically, multiple constellation alphabets are selected for different chirp-based subcarriers (chirps). Aside from cl…

Raiders Veteran Will Not be Under-the-Radar for Long https://www.si.com/nfl/raiders/news/pete-carroll-jeremy-chinn-washington-commanders-patrick-graham-isaiah-pola-mao

Data-Driven Model Reduction by Moment Matching for Linear and Nonlinear Parametric Systems
Hanqing Zhang, Junyu Mao, Mohammad Fahim Shakib, Giordano Scarciotti
https://arxiv.org/abs/2506.10866

Data-Driven Model Reduction by Moment Matching for Linear and Nonlinear Parametric Systems
Theory and methods to obtain parametric reduced-order models by moment matching are presented. The definition of the parametric moment is introduced, and methods (model-based and data-driven) for the approximation of the parametric moment of linear and nonlinear parametric systems are proposed. These approximations are exploited to construct families of parametric reduced-order models that match the approximate parametric moment of the system to be reduced and preserve key system properties suc…

Rising Raiders Defender is Ready to Take the Next Step https://www.si.com/nfl/raiders/las-vegas-pete-carroll-isaiah-pola-mao-eric-stokes-jeremy-chinn

Catalogue of chiral phonon materials
Yue Yang, Zhenyu Xiao, Yu Mao, Zhanghuan Li, Zhenyang Wang, Tianqi Deng, Yanhao Tang, Zhi-Da Song, Yuan Li, Huiqiu Yuan, Ming Shi, Yuanfeng Xu
https://arxiv.org/abs/2506.13721

Catalogue of chiral phonon materials
Chiral phonons, circularly polarized lattice vibrations carrying intrinsic angular momentum, offer unprecedented opportunities for controlling heat flow, manipulating quantum states through spin-phonon coupling, and realizing exotic transport phenomena. Despite their fundamental importance, a universal framework for identifying and classifying these elusive excitations has remained out of reach. Here, we address this challenge by establishing a comprehensive symmetry-based theory that systemati…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- Gain and phase type multipliers for feedback robustness
Axel Ringh, Xin Mao, Wei Chen, Li Qiu, Sei Zhen Khong

UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations
Fengran Mo, Yifan Gao, Chuan Meng, Xin Liu, Zhuofeng Wu, Kelong Mao, Zhengyang Wang, Pei Chen, Zheng Li, Xian Li, Bing Yin, Meng Jiang
https://arxiv.org/abs/2507.07030

UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations
The rapid advancement of conversational search systems revolutionizes how information is accessed by enabling the multi-turn interaction between the user and the system. Existing conversational search systems are usually built with two different models. This separation restricts the system from leveraging the intrinsic knowledge of the models simultaneously, which cannot ensure the effectiveness of retrieval benefiting the generation. The existing studies for developing unified models cannot fu…

How Many Safeties Will Make Raiders' Roster? https://www.si.com/nfl/raiders/las-vegas-trey-taylor-thomas-harper-isaiah-pola-mao-chris-smith

Intelligent Metasurface-Enabled Integrated Sensing and Communication: Unified Framework and Key Technologies
Shunyu Li, Tianqi Mao, Guangyao Liu, Fan Zhang, Ruiqi Liu, Meng Hua, Zhen Gao, Qingqing Wu, George K. Karagiannidis
https://arxiv.org/abs/2506.13713

Intelligent Metasurface-Enabled Integrated Sensing and Communication: Unified Framework and Key Technologies
As the demand for ubiquitous connectivity and high-precision environmental awareness grows, integrated sensing and communication (ISAC) has emerged as a key technology for sixth-generation (6G) wireless networks. Intelligent metasurfaces (IMs) have also been widely adopted in ISAC scenarios due to their efficient, programmable control over electromagnetic waves. This provides a versatile solution that meets the dual-function requirements of next-generation networks. Although reconfigurable inte…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/4]:
- What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Su...
Yaoqi Huang, Julie Stephany Berrio, Mao Shan, Stewart Worrall

Isaiah Pola-Mao Can’t Wait To Run It Back in 2025 | NFL https://www.youtube.com/watch?v=-_lDR31Gub8

Joint System Modeling Approach for Fault Simulation of Start-er/Generator and Gas Generator in All-Electric APU
Haotian Mao, Yingqing Guo
https://arxiv.org/abs/2506.10562

Joint System Modeling Approach for Fault Simulation of Start-er/Generator and Gas Generator in All-Electric APU
This paper presents a joint system modeling approach for fault simulation of all-electric auxiliary power unit (APU), integrating starter/generator turn-to-turn short circuit (TTSC) faults with gas generator gas-path faults.To address challenges in electromechanical coupling, simulation precision and computational efficiency balance, we propose a multi-rate continuous-discrete hybrid simulation architecture. This architecture treats the starter/generator as a continuous system with variable ste…

The Discovery of Little Red Dots in the Local Universe: Signatures of Cool Gas Envelopes
Xiaojing Lin, Xiaohui Fan, Zheng Cai, Fuyan Bian, Hanpu Liu, Fengwu Sun, Yilun Ma, Jenny E. Greene, Michael A. Strauss, Richard Green, Jianwei Lyu, Jaclyn B. Champagne, Andy D. Goulding, Kohei Inayoshi, Xiangyu Jin, Gene C. K. Leung, Mingyu Li, Yichen Liu, Junjie Mao, Maria Anne Pudoka, Wei Leong Tee, Ben Wang, Feige Wang, Yunjing Wu, Jinyi Yang, Haowen Zhang, Yongda Zhu

The Discovery of Little Red Dots in the Local Universe: Signatures of Cool Gas Envelopes
JWST observations have revealed a population of high-redshift "little red dots" (LRDs) that challenge conventional AGN models. We report the discovery of three local LRDs at $z = 0.1-0.2$, initially selected from the SDSS database, with follow-up optical/near-IR spectroscopy and photometry. They exhibit properties fully consistent with those of high-redshift LRDs, including broad hydrogen and helium emission lines, compact morphologies, V-shaped UV-optical SED, declining near-IR continua, and n…

LEANN: A Low-Storage Vector Index
Yichuan Wang, Shu Liu, Zhifei Li, Yongji Wu, Ziming Mao, Yilong Zhao, Xiao Yan, Zhiying Xu, Yang Zhou, Ion Stoica, Sewon Min, Matei Zaharia, Joseph E. Gonzalez
https://arxiv.org/abs/2506.08276

LEANN: A Low-Storage Vector Index
Embedding-based search is widely used in applications such as recommendation and retrieval-augmented generation (RAG). Recently, there is a growing demand to support these capabilities over personal data stored locally on devices. However, maintaining the necessary data structure associated with the embedding-based search is often infeasible due to its high storage overhead. For example, indexing 100 GB of raw data requires 150 to 700 GB of storage, making local deployment impractical. Reducing…

2025 Position Breakdown: Identity of Raiders secondary revealing itself throughout offseason https://www.raiders.com/news/2025-position-breakdown-cornerbacks-safeties-jeremy-chinn-jakorian-bennett-isaiah-pola-mao

A Survey on Artificial Noise for Physical Layer Security: Opportunities, Technologies, Guidelines, Advances, and Trends
Hong Niu, Yue Xiao, Xia Lei, Jiangong Chen, Zhihan Xiao, Mao Li, Chau Yuen
https://arxiv.org/abs/2507.06500

A Survey on Artificial Noise for Physical Layer Security: Opportunities, Technologies, Guidelines, Advances, and Trends
Due to the broadcast nature of wireless communications, physical-layer security has attracted increasing concerns from both academia and industry. Artificial noise (AN), as one of the promising physical-layer security techniques, is capable of utilizing the spatial degree-of-freedom of channels to effectively enhance the security of wireless communications. In contrast to other physicallayer security techniques, the key distinguishing feature of AN is to generate specific interfering signals ac…

Generalizable 7T T1-map Synthesis from 1.5T and 3T T1 MRI with an Efficient Transformer Model
Zach Eidex, Mojtaba Safari, Tonghe Wang, Vanessa Wildman, David S. Yu, Hui Mao, Erik Middlebrooks, Aparna Kesewala, Xiaofeng Yang
https://arxiv.org/abs/2507.08655

Generalizable 7T T1-map Synthesis from 1.5T and 3T T1 MRI with an Efficient Transformer Model
Purpose: Ultra-high-field 7T MRI offers improved resolution and contrast over standard clinical field strengths (1.5T, 3T). However, 7T scanners are costly, scarce, and introduce additional challenges such as susceptibility artifacts. We propose an efficient transformer-based model (7T-Restormer) to synthesize 7T-quality T1-maps from routine 1.5T or 3T T1-weighted (T1W) images. Methods: Our model was validated on 35 1.5T and 108 3T T1w MRI paired with corresponding 7T T1 maps of patients with c…

From Ground to Sky: Architectures, Applications, and Challenges Shaping Low-Altitude Wireless Networks
Weijie Yuan, Yuanhao Cui, Jiacheng Wang, Fan Liu, Geng Sun, Tao Xiang, Jie Xu, Shi Jin, Dusit Niyato, Sinem Coleri, Sumei Sun, Shiwen Mao, Abbas Jamalipour, Dong In Kim, Mohamed-Slim Alouini, Xuemin Shen
https://arxiv.org/abs/2…

From Ground to Sky: Architectures, Applications, and Challenges Shaping Low-Altitude Wireless Networks
In this article, we introduce a novel low-altitude wireless network (LAWN), which is a reconfigurable, three-dimensional (3D) layered architecture. In particular, the LAWN integrates connectivity, sensing, control, and computing across aerial and terrestrial nodes that enable seamless operation in complex, dynamic, and mission-critical environments. In this article, we introduce a novel low-altitude wireless network (LAWN), which is a reconfigurable, three-dimensional (3D) layered architecture.…

Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition
Wule Mao, Zhouheng Li, Yunhao Luo, Yilun Du, Lei Xie
https://arxiv.org/abs/2507.04384

Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition
Safe trajectory planning remains a significant challenge in complex environments, where traditional methods often trade off computational efficiency for safety. Comprehensive obstacle modeling improves safety but is computationally expensive, while approximate methods are more efficient but may compromise safety. To address this issue, this paper introduces a rapid and safe trajectory planning framework based on state-based diffusion models. Leveraging only low-dimensional vehicle states, the d…

WATCH: Raiders RB Raheem Mostert Following Minicamp https://www.si.com/nfl/raiders/las-vegas-minicamp-raheem-mostert-pete-carroll-isaiah-pola-mao

Raiders' New Look Secondary Taking Shape https://www.si.com/nfl/raiders/las-vegas-jeremy-chinn-pete-carroll-patrick-graham-isaiah-pola-mao

One Raiders Play Worth Rooting for This Season https://www.si.com/nfl/raiders/isaiah-pola-mao-las-vetas-troy-polamalu-pete-carroll

OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding
JingLi Lin, Chenming Zhu, Runsen Xu, Xiaohan Mao, Xihui Liu, Tai Wang, Jiangmiao Pang
https://arxiv.org/abs/2507.07984

OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding
Recent advances in multimodal large language models (MLLMs) have shown remarkable capabilities in integrating vision and language for complex reasoning. While most existing benchmarks evaluate models under offline settings with a fixed set of pre-recorded inputs, we introduce OST-Bench, a benchmark designed to evaluate Online Spatio-Temporal understanding from the perspective of an agent actively exploring a scene. The Online aspect emphasizes the need to process and reason over incrementally a…

The Raiders' Many Unknowns Make Them Exciting Heading into 2025 https://www.si.com/nfl/raiders/chip-kelly-las-vegas-eric-stokes-isaiah-pola-mao

What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies
Yaoqi Huang, Julie Stephany Berrio, Mao Shan, Stewart Worrall
https://arxiv.org/abs/2507.06513

What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies
Advances in vision-based sensors and computer vision algorithms have significantly improved the analysis and understanding of traffic scenarios. To facilitate the use of these improvements for road safety, this survey systematically categorizes the critical elements that demand attention in traffic scenarios and comprehensively analyzes available vision-driven tasks and datasets. Compared to existing surveys that focus on isolated domains, our taxonomy categorizes attention-worthy traffic entit…

Raiders Who Will Earn Expanded Roles in 2025 https://www.si.com/nfl/raiders/las-vegas-tyree-wilson-decamerion-richardson-isaiah-pola-mao

LongAnimation: Long Animation Generation with Dynamic Global-Local Memory
Nan Chen, Mengqi Huang, Yihao Meng, Zhendong Mao
https://arxiv.org/abs/2507.01945

LongAnimation: Long Animation Generation with Dynamic Global-Local Memory
Animation colorization is a crucial part of real animation industry production. Long animation colorization has high labor costs. Therefore, automated long animation colorization based on the video generation model has significant research value. Existing studies are limited to short-term colorization. These studies adopt a local paradigm, fusing overlapping features to achieve smooth transitions between local segments. However, the local paradigm neglects global information, failing to maintai…